CUSTOMER LOYALTY
Content
Aarhus School of Business, Denmark Faculty of Business Performance Management
Joanna Waligóra Student ID 254 581 Robert Waligóra Student ID 254 582
MEASURING CUSTOMER SATISFACTION AND LOYALTY IN THE AUTOMOTIVE INDUSTRY A CASE OF PREMIUM BRAND OF PASSENGER CARS
Master Thesis Advisor: Jacob Kjær Eskildsen Department of Marketing and Statistics
Aarhus, 2007
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CONTENTS EXECUTIVE SUMMARY ..................................................................................................5 INTRODUCTION – A NEED FOR THE STUDY..............................................................7 MAIN OBJECTIVES OF THE PAPER..............................................................................8 1. THE IMPORTANCE OF CUSTOMER SATISFACTION FOR BUSINESS PERFORMANCE ................................................................................................................9 1.1. Customer satisfaction in customer orientation model .................................................10 1.2. Customer satisfaction in The EFQM Excellence Model .............................................13 1.3. The evidence of positive impact of satisfaction on business results ............................15 1.3.1. Satisfaction influence on ROI, stock prices and shareholder value.......................16 1.3.2. Customer retention impact on business results.....................................................17 1.3.3. Dissatisfaction influence on business performance ..............................................18 2. THE THEORY OF CUSTOMER SATISFACTION....................................................22 2.1. The definition of customer satisfaction.......................................................................22 2.2. Antecedents of customer satisfaction .........................................................................22 2.3. Consequences of customer satisfaction. .....................................................................25 3. CUSTOMER SATISFACTION MEASUREMENT SYSTEMS ..................................29 3.1. Antecedents of satisfaction measurement system implementation – customer’s personal values research .................................................................................................................29 3.2. Rationale for development and use of industry or nation universal customer satisfaction measurement indexes........................................................................................................32 3.3. National Customer Satisfaction Indexes .....................................................................33 3.3.1. Swedish Customer Satisfaction Barometer ..........................................................33 3.3.2. American Customer Satisfaction Index ...............................................................36 3.3.3. European Customer Satisfaction Index................................................................39 3.3.4. Automotive industry specific customer satisfaction indexes ................................43 4. COMPANY X CUSTOMER’S PROFILE ....................................................................47 4.1. Company X customers – demographics .....................................................................47 4.2. Company X customers – benefits driving the car purchase.........................................53 4.3. Company X customers – attitudes to vehicle ..............................................................58 4.4. Summary of Company X customer’s profile ..............................................................59 5. STRUCTURAL EQUATION MODELING AND PARTIAL LEAST SQUARES .....61 5.1. Structural Equation Modeling – covariance-based approach.......................................61 5.2. Partial Least Squares..................................................................................................62 5.2.1. Specification of the model...................................................................................62 5.2.2. Estimation...........................................................................................................64 5.2.3. Validation of model ............................................................................................67 6. MEASURING CUSTOMER SATISFACTION AT COMPANY X IN POLAND ......71 6.1. Customer Satisfaction Index at Company X – Sales Service Quality..........................72 6.2. Customer Satisfaction Index at Company X – After - Sales Service Quality...............74 6.3. Brand Satisfaction Model at Company X in Poland – history, underpinnings and structure ...........................................................................................................................75 6.3.1. Questionnaire development .................................................................................79 6.3.2. Computer software for Partial Least Squares models...........................................84 6.3.3. Working out the structure of the model ...............................................................85 6.3.4. Discussion on BSM structure ..............................................................................89 6.3.5. Quality criteria evaluation ...................................................................................92 7. RESULTS OF BRAND SATISFACTION MODEL FOR COMPANY X ...................95 7.1. Sample description.....................................................................................................95
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7.2. Estimation results for Brand Satisfaction Model – Total Brand ................................101 7.3. Estimation results – Total brand - detailed analysis of performance..........................108 7.4. Estimation results for Brand Satisfaction Model – 3 segments of customers.............115 7.4.1. General estimation results for 3 customer segments...........................................115 7.4.2. Total effects analysis – 3 customer segments .....................................................119 7.4.3. Satisfaction vs. importance analysis - 3 clients segments - inner model .............123 7.4.4. Satisfaction vs. importance analysis - 3 customer segments –outer model..........127 7.4.5. Summary of analysis for 3 customer segments...................................................135 CONCLUSIONS AND RECOMMENDATIONS ...........................................................137 REFERENCES .................................................................................................................139 APPENDICES ..................................................................................................................142 Appendix 1. ....................................................................................................................142 Appendix 2. ....................................................................................................................143 Appendix 3. ....................................................................................................................149 Appendix 4. ....................................................................................................................163 Appendix 5. ....................................................................................................................182 Appendix 6. ....................................................................................................................203
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EXECUTIVE SUMMARY The new method of customer satisfaction and loyalty measurement has been developed for Company X in Poland. The method is called Brand Satisfaction Model. The Company X is operating on the automotive market representing premium brand of passenger vehicles in Poland. The model has been created based on customer satisfaction and loyalty theories and so far implemented and practically adopted models. The Brand Satisfaction Model is mainly built on the ACSI, ECSI and JD Power CSI studies with particular use of satisfaction theories presented in the paper. The BSM structure is adjusted to industry specific requirements which have been verified by customer focus groups and statistical validity tests. Therefore unique, industry specific method for measuring satisfaction of passenger vehicles clients has been developed and is presented below:
Practical research on a group of 346 customers of Company X in Poland has been conducted. After analysis of satisfaction scores and importance levels for all the areas included in the study four areas that need to be definitely improved have been revealed: After Sales service quality, Value for money, Costs of ownership and Brand Image. The results of the study have been made well-known across the entire organization. The reparation program has been developed and implemented and as a result of it the next After
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Sales service satisfaction study presented the increase in overall score by 2 percentage points. Further actions concentrating on improvement of the other three mentioned areas have been implemented but their results were not known yet when the paper was written. Therefore the knowledge gained with Brand Satisfaction Model helped Company X prioritize its actions and concentrate on those areas that need to be taken care of in a first place. Furthermore the study analyzed three customer groups separately: Compact, Mid-size and Full-size and Large vehicles owners in order to discover differences in their definition of satisfaction and loyalty. Compact vehicles users are much more price and costs sensitive. They also pay stronger attention to the image of a brand and post-purchase service they receive. Mid-size vehicles users are definitely closer in terms of their profile to the third group of customers however they are more vehicle comfort and quality oriented while at the same time do not expect so high value for money as other clients. The full-size and large vehicles owners are definitely the least price and costs sensitive. Vehicle quality, comfort and functionality and sales service quality are the most important elements strongly affecting the level of their loyalty. The knowledge gained from the analysis of three customer segments helped the sales and marketing as well as PR departments adjust its operations and strategy to specific requirements of different customer groups in order to improve their overall satisfaction and loyalty to a brand. Developed model proved to be very explanatory with regard to the type of knowledge received after application of the structure to the dataset gathered during interviews with Company X customers. The BSM is also an effective tool that not only helps to understand customers better but also answers the question: how to improve customers’ satisfaction and loyalty. The Polish Automotive Market Research Institute presented interest in the model with the aim to make the Brand Satisfaction Model the uniform platform for measuring and comparing customer satisfaction and loyalty across whole polish automotive sector.
Successful
implementation of Brand Satisfaction Model by all brands of passenger vehicles operating in Poland would definitely supply automotive companies in Poland with knowledge comparisons of brands performance on the Polish market.
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INTRODUCTION – A NEED FOR THE STUDY There is a need for the comprehensive study at Company X in Poland which would cover all aspects of customer satisfaction and loyalty. The need was recognized by the marketing and sales department and the board of directors due to the fact that so far the knowledge about Company X clients was limited to their demographic and social profile and customer’s evaluation of sales and after-sales service quality. All other areas such as vehicle quality, design, comfort and functionality, cost of ownership, value for money etc. have been so far neglected and not measured. Therefore the Brand Satisfaction Model has been created in order to close the gap in knowledge about Company X clients. Customer Satisfaction can be measured and monitored on many levels of advancement. First of all, customer orientation concept, means-end chain theory, expectations disconfirmation and performance models, Hirschman’s exit theory are important theories which define clients’ satisfaction and loyalty concepts and their influence on company business results. Than, the EFQM Excellence Model takes the satisfaction studies to the next level and measures customer satisfaction importance and influence on company’s profitability and success. Finally, there are those customer satisfaction measurement nation-wide studies such as SCSB, ECSI and ACSI, which define the satisfaction concept empirically and help understand the relationships between antecedents of satisfaction and its consequences such as loyalty and retention. Additionally, there are industry specific types of researches such as JD Power automotive CSI that measure clients’ satisfaction with different aspects of product usage which are usually applicable to only one industry. Taking into consideration all the above mentioned satisfaction theories, the Brand Satisfaction Model has been built up based on the above mentioned theories and researches as a complete and comprehensive measurement method of clients’ satisfaction and loyalty for Company X in Poland. Although its structure is similar to ECSI, the BSM includes some of the JD Power CSI study elements. Such combination of the theories and the two researches offers a valuable tool that combines most of theoretical and empirical knowledge so far possessed by academic and professional environment. The Brand Satisfaction Model may be useful sales and marketing tool not only for Company X but also for other automotive companies operating on Polish market. If the study was applied to other firms, than a great portion of knowledge could be added to the whole 7
automotive sector in Poland by allowing for cross industry comparisons. Provided that the BSM is well grounded in terms of its statistical properties as well as satisfaction theories, there is high probability that the same structure could be applied to other automotive brands. So far there has been no other unified measurement model of customer satisfaction and loyalty created and used in the polish automotive sector. There are different researches covering some aspects of company’s performance but the unified and complete approach allowing for comparison between different brands is not available. Therefore the study that is comprehensive and at the same time industry specific – such as Brand Satisfaction Model would be a huge contribution to the Polish automotive sector. MAIN OBJECTIVES OF THE PAPER The main objective of the study is: -
Creation of complete satisfaction measurement model for Company X selling premium passenger vehicles in Poland and assessment of Company X customers’ satisfaction and loyalty based on the new methodology. Up till now the Company X has been only using its own Customer Satisfaction Index study as the measure for sales company performance. However such approach leads to severe limitations of the study results, as the Customer Satisfaction Index concentrates only on measurement of satisfaction with sales and after-sales service quality. Therefore more comprehensive approach covering all aspects of customer experience with product, brand and dealerships is needed.
In order to support the main goal some sub objectives shall be fulfilled: -
Creation of theoretical satisfaction measurement model and statistical validation of the model. The model shall be based on customer satisfaction theories and measurement models described in this paper.
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Application of the theoretical model into the practical research - measurement of Company X customers’ satisfaction and loyalty using the new methodology.
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Analysis of the research results and comparison of the differences between Company X customer segments. The Company X clientele shall be segmented into three groups based on existing Customer Profile study: Compact vehicles, Mid-size vehicles, Full-size and Large vehicles owners. 8
1. THE IMPORTANCE OF CUSTOMER SATISFACTION FOR BUSINESS PERFORMANCE Satisfaction understood as emotional state shall be held by people, who are willing to develop successfully personal relations, but has also been of utmost importance in business and professional situations. The latter will be of our interest in the further course of this work. In general, satisfied customers, satisfied employees and satisfied shareholders all have one common characteristic – they are positive and enthusiastic about the company they are dealing with. Talking in more detail, they shall behave in a way desired and understood by a firm, when it comes to making decision about further cooperation with the company. Specifically, they will be making repeat purchases, delivering best quality of work and investing additional funds in the company stocks. Such behavior of satisfied customers, employees and shareholders will contribute to business growth. Therefore satisfaction, understood in such a wide context, shall definitely be on the top of board of directors’ list as it has strong positive impact on business results. Although satisfaction is applicable to organization’s customers, employees and shareholders, within the course of this work customer satisfaction will be discussed. Specifically, customer as the ultimate judge of products or service quality and his or her satisfaction with the delivered products or services will be taken into account. Customer satisfaction is crucial for business performance, as it is the driver of customer loyalty and consecutive retention. This statement, although intuitively true, could be argued with. On one side, it could be said, that there is no need to dedicate time and funds to make the customer’s satisfied, but it is less expensive and sufficient to deliver high quality offerings, which will certainly be purchased by some clients. Furthermore, one could argue that even though customers are not loyal and will not stay with the company, new clients can be easily found. On the other side it can be argued, that even though customers will buy the product, they will not repurchase unless the offering meets customers’ needs. Moreover, it may turn out, that despite product’s quality is high it does not fill client’s expectations, as it misses some of required benefits. Finally, one could say that it is much more expensive to acquire new customers than retain current ones, as the costs associated with the customer recruitment are higher than those connected with customer retention. 9
The above arguments connected with customer satisfaction concept have been widely measured and discussed in the literature. As a result there is lots of evidence supporting the initial statement: customer satisfaction is crucial for business performance, as it is the driver of customer loyalty and consecutive retention the importance of customer satisfaction for business results. Within the course of this chapter, we will focus on only few supportive theories. First of all, the importance of customer satisfaction for business performance has been justified within the customer orientation concept. Secondly, the actual importance of customer satisfaction for business performance versus importance of other factors has been quantified within the EFQM Excellence Model. Finally, also the impact of increased satisfaction on business results was researched and quantified within the literature. 1.1. Customer satisfaction in customer orientation model Customer satisfaction concept has been placed at the heart of customer orientation model. Based on this model, there are two kinds of companies;
on the one side, there are product oriented companies, who are trying to sell the products which they produce regardless of the level, to which those products satisfy their customers’ needs. To simplify it, product oriented companies are searching for customers, whose needs can be matched with the products, that the company is offering. Very often those companies end up in the business stagnation phase, as they are not be able to follow the natural development of customer needs – they continue to offer what they think is desired by the consumers instead of delivering what is actually desired.
on the opposite side, there are customer oriented companies, who are focused on meeting customer’s needs and satisfying him or her, as they know that satisfaction is a prerequisite to retention, which in turn has positive impact on the long-term health of their business.
Customer orientation is an ongoing process, during which organizations pursue three goals: 1. attain customer information, 2. disseminate and use that information when making decisions 3. implement change (Johnson, Herrmann, Huber, Gustafsson, 1997).
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First goal - “attain customer information” - means that a firm must collect information about its customers. This is done through various research techniques in order to find out, what are the needs and values of customers and how they are served by current products and services. The information attained shall also point out future customer’s needs and the direction into which they will be developing. Secondly, a customer oriented company needs to ensure, that the “disseminate and use the information” goal is met. Therefore it is necessary to make sure that the information collected is shared between all departments involved in production and delivery of products or services to customers. For that to be possible, tight cooperation between market research and other departments is necessary. Moreover, organization’s leadership must understand the necessity of and support the facts-based decision process. Finally, there is no use of information, which is collected and stored in databases. To fulfill the third goal – “implement the change” - it is necessary to translate the conclusions and recommendations from the research into actions, which will enable the company to deliver improved products and services. To summarize, a customer oriented company has one primary goal – to satisfy its customers, which is realized by getting to know customer needs and values, sharing this knowledge throughout the company and translating it into improved products and services, which are able to satisfy the customer to largest possible extent. Satisfying the customers is a never ending process. As the customer grows up, gets older and ages, his or her needs and values change. Moreover, as the economies develop, mature and decline, the wants of human beings also change. As a result, companies are forced to follow or even be ahead of customer’s needs in order ensure business growth. Customer orientation process never comes to an end – it is a sequence of repetitive stages. The theory of customer orientation distinguishes four major phases, which a customer oriented company has to go through all over again to ensure growth in customer orientation (Johnson, Herrmann, Huber, Gustafsson, 1997): 1. Customer strategy and focus 2. Customer satisfaction measurement 3. Analysis and priority setting 4. Implementation.
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Figure 1.1. The four phases of customer orientation
Phase I: Customer Strategy and Focus
Phase II: Customer Satisfaction Measuremen t
Phase III: Analysis and Priority Setting
Phase IV: Implementation
Source: Johnson, Herrmann, Huber, Gustafsson, 1997 In the first phase of the process, companies should answer the question, how important is the customer for their business performance and to what extent is the customer orientation their business priority. In other words, it shall be clearly stated, to what extent company shall and can adjust their strategy to consumers needs. Furthermore, phase 1 is the right time to specify, which customer segments shall be in the center of organizations attention – e.g. referring to automotive industry, shall the company focus on premium or mass cars’ users, shall the company target young and dynamic or adult and affluent customers? During phase two of customer orientation process, organization shall develop a measurement system, which will enable to evaluate the level of customers’ satisfaction of particular target groups with currently delivered products or services. In more detail, the measurement system shall answer the question, which needs, values and benefits are key for consumers within customer segments. Specifically, the research shall evaluate, to what extent current products and services’ attributes deliver the desired benefits and therefore fill customers’ needs. As the second phase provides the company with the assessment of benefits’ importance and the extent to which current offerings fill those benefits, during third phase organization shall analyze the information gathered and set priorities for further actions. In other words, organization shall spot for product benefits, which are very important for target customers, however not delivered by current products or services. Such benefits shall be the key priority for company and a main focus in order to make the customers more satisfied and therefore more prone to repeat purchases.
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Fourth phase of the customer orientation process requires that all the priorities set in phase three are translated into specific actions and process, which will be conducted. Those actions shall result in making the customer more satisfied through delivery of improved product or service. This customer orientation process shall never end and shall be repeated – after fourth phase, phase one shall start, which shall verify, if the improved product really satisfied customer to larger extent. To summarize the customer orientation model, it is entirely focused on customer satisfaction. Based on this model, only customer oriented company, which tries to deliver offerings tailored to customer’ needs may expect returns from their actions. Returns equal higher satisfaction levels being observed, which in turn shall increase the probability of repeat purchases and as a result, increasing returns for the organization. Customer orientation model undoubtedly has the customer focus and customer orientation in its hearth and stresses the importance of customer satisfaction for the business performance. Although customer orientation model has stressed the importance of customer satisfaction for business performance, it has not quantified the importance. This leads us to the next theory, which has taken the discussion to next level and quantified the importance of customer satisfaction to business performance – The EFQM Excellence Model. 1.2. Customer satisfaction in The EFQM Excellence Model The authors of The EFQM Excellence Model have not only acknowledged the importance of customer satisfaction for organizations, but also measured the importance for the business performance. The EFQM Excellence Model was introduced in 1992 and is a practical tool, which in midterm helps organizations to evaluate and improve their performance, and in long term enables them to strive for excellence. The organizations are evaluated based on nine criteria, which are included in The EFQM Model. Five of them are “enablers” – they cover, what an organization does, and remaining four are “results”, which include what an organization achieves. There is relation between two groups – the “results” are driven by “enablers”. The structure of the model is presented in the below figure.
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Figure 1.2. The EFQM Excellence Model
Source: www.efqm.org The EFQM Excellence Model, similarly as customer orientation model, puts customer and his satisfaction in the heart of the theory. Specifically, it discusses the concept of customer satisfaction within three of its nine criteria: 1. firstly, it is stressed within “Leadership” criterion, that company leaders need to meet, understand and respond to needs and expectations of stakeholders, which also include customers as one of most important groups. 2. secondly, also “Processes” criterion concentrates on satisfaction. Processes in the organization shall be designed in such manner that they support organizations’ policy and strategy, fully satisfy and generate value for its customers and other stakeholders (The EFQM Excellence Model 1999 manual). 3. lastly, “Customer results” criterion is completely dedicated to customers’ satisfaction. Measures within this criterion are supposed to assess customer’s perception of overall organization’s
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image,
his or
her
satisfaction with
products/services, sales and after sales support and evaluate customer loyalty to the organization. The focus on customer and his or her satisfaction in three out of nine criteria in The EFQM Excellence Model is the evidence supporting the importance of customer satisfaction for the business performance. The authors of the model have established importance weights for each criterion in the model. It is necessary to stress, that “Customer results”, called also customer satisfaction criterion, is the weightiest criterion in the model and accounts for twenty percent of the total scoring system when companies assess and measure their own excellence (Gronholdt, Kristensen, Martensen, 2002). To put it differently, customer satisfaction has not only the largest impact on evaluation of organization excellence, but most importantly understanding the customers and measuring their satisfaction is important step in quality improvement, which than results in higher satisfaction levels, improved business results and business excellence. To summarize, based on the EFQM Excellence Model, customer satisfaction is the most important factor driving the organization towards excellent performance and increasing financial results. Having in mind that customer satisfaction is important for business performance, that it is the most important factor in driving business towards excellence, it is important to quantify the influence of increased satisfaction on the company performance. 1.3. The evidence of positive impact of satisfaction on business results In literature, there have been lots of empirical studies conducted on satisfaction influence on company’s performance, as well as effect on the influence of customer dissatisfaction on the firm’s results. The satisfaction or dissatisfaction influence on organization’s performance may be discussed in three aspects: 1. positive impact of growing satisfaction on return on investments (ROI), prices of stocks and shareholder value 2. positive impact of satisfaction on customer retention and as a result lower costs or higher returns resulting from long term relationship with the customers 3. negative impact of customer dissatisfaction on business performance and business results
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There is strong evidence within those three aspects for positive correlation between growing customer satisfaction and business results. 1.3.1. Satisfaction influence on ROI, stock prices and shareholder value The empirical studies were conducted based on customer satisfaction measurement models and using the data acquired during models testing and implementation in order to evaluate if there is positive correlation between increased satisfaction and ROI, stock prices and shareholder value. Starting with Swedish Customer Satisfaction Barometer index (which will be described in detail in further course of this paper), it was analyzed, what is the effect of increased satisfaction on ROI. The results of the study conducted by Anderson, Fornell and Lehmann (1994) are the first, large sample evidence, that customer satisfaction is related with company performance. The study revealed that as the satisfaction changes by one percent, ROI changes by 0.4 percent. Further studies conducted on SCSB by Anderson, Fornell and Rust (1997) proved that average elasticity of ROI is higher for goods – 0.265 than for services – 0.14. This implies that it is much more difficult for service companies to satisfy their clients than it is for production companies. Such difference may be related to the fact, that it is much easier for a consumer to distinguish between and objectively evaluate the quality of the product rather than the service. Referring further to the Swedish example, Ittner and Larcker have taken the analysis to the next level, and examined the correlation between satisfaction and stock prices. The results of their study prove that a one percent change in the satisfaction index translate into about seven percent change in shareholder value (Gronholdt, Kristensen, Martensen, 2002). The same authors carried the analysis based on American Customer Satisfaction Index (ACSI). The study results were in line with the Swedish results and they confirmed that there is relation between satisfaction levels and stock prices; companies with highest customer satisfaction indexes earn return on stock price of 1-2 percent per month above the average return on the market (Gronholdt, Kristensen, Martensen, 2002). To summarize, there is solid evidence in the form of results of various empirical studies, that customer satisfaction is correlated with financial results in following manner: 16
1. increasing customer satisfaction positively influences return on investments (ROI) 2. the higher the customer satisfaction, the higher earnings on stocks for shareholders 3. increasing satisfaction drives positive change in shareholder value 1.3.2. Customer retention impact on business results Satisfaction is a prerequisite for customer loyalty and retention. In other words, if customers are satisfied with the product, it is probable, that they will be loyal to the company and that the loyalty will be translated into repeated purchases. Repeated purchases are in turn prerequisite to increasing financial results for the company, what implies that customer retention is profitable to the organization. Going further, the benefits from retaining the customers are larger than from acquiring new one and the costs associated with current customer are lower and declining as compared to new customer. This thesis has been supported by Reichheld (Johnson, Herrmann, Huber, Gustafsson, 1997), who has been discussing effects of customer retention on business performance and he defined areas – both cost and revenue, which are strongly impacted by customer retention: 1. Acquisition costs; all costs related with attracting customer to the company, such as incentive program, creation of customer accounts, customer training. As these costs appear in the early stage of relationship with the customer, customer retention allows for avoiding them. 2. Start-up costs; costs, they are related to the beginning of cooperation with the customer, egg. set up of customer bank account. With time, the account is maintained and some costs are associated with that, but one time set up costs do not happen again. 3. Base revenues; the revenue, which a company accounts for regularly during each following period, e.g. base revenue from monthly payment for mobile phones. When customer is retained, the base revenue is guaranteed cash flow for a firm. 4. Volume effects; the surplus revenue, which company earns as the relation with a customer is developing. Customers, if satisfied, tend to increase their spending with a company by either buying larger quantities of a product. 5. Spin-off effects; with time, customers have a tendency to purchase complementary products or services, e.g. satisfied car owner shall buy second car for his family members or will acquire a car gadgets from the company, e.g. watch from Company X collection 6. General efficiency effects; operation costs are expected to decrease with time, as the company gets to know its customers better and therefore is capable of delivering the 17
products or services in the required manner. On the other hand, customers get to know the structure of the company and the requirements from the company side, which enable for delivery of higher quality offerings. In other words, cooperation between both sides becomes smoother. 7. Referral effects; satisfied customer shall talk to two persons about his or her positive purchase experience, however dissatisfied customer will talk to and discourage ten persons from potential cooperation with the organization. Nowadays, this factor is becoming of extreme importance – as the traditional marketing tools have become well known and understood by customers, customer referrals and so called word of mouth has a great power. 8. Price- sensitivity effects; loyal customers are less price sensitive than new customers. If the relationship with the company is satisfactory for the customer, he is willing to pay more for the same products. Moreover, if the customer is acquired in his early stage of life, as he grows older and becomes more affluent, he is also willing to trade for premium products within the same supplier. If customer is satisfied, he is probable to continue the relationship with the company. If that is the case, the above described effects shall happen – they will either lead to lower costs or higher returns. In the end, as the relationship with customer is continued, profit per customer shall grow over time. 1.3.3. Dissatisfaction influence on business performance We have already explained the importance of customer satisfaction for business performance and proved that there is measurable, positive impact of increased customer satisfaction on business results. This implies that companies, which enjoy increasing satisfaction of its customers, at the same time note increasing business results. However, there are those companies, who observe declining satisfaction. The question is therefore what are the results of customer satisfaction decline? Based on Hirschman’s theory (Johnson, 1996), dissatisfied customers may react in two ways – they may either voice or exit. Customer exit is the worse consequence of customer evaluation of product offering. In such situation, the organization looses customers, what results in declining sales and revenues for 18
the company. Moreover, such customer, called “dissatisfied switcher”, will most probably express his or her dissatisfaction through word of mouth to other potential customers. In other words, dissatisfaction has not only direct effect on organization business measured as lost potential sales, but may also have indirect effect on the business in the form of negative word of mouth. Therefore it is of extreme importance for the company to handle in the right manner second possible reaction of dissatisfied customer –customer voice. If a customer is dissatisfied, before he or she exits, he or she may also complain to the company. Depending on how his or her complaint is handled – whether in satisfactory or nonsatisfactory manner, he or she will either exit or retain with a company. Therefore it is extremely crucial for the company to establish effective complaint management system which will ensure, that two actions happen: a) listening to complaints and b) reaction to the complaints. The establishment of complaint system is important due to three reasons: 1. effective complaint handling system may prevent from customer exit and therefore business loss 2. it may prevent from negative word of mouth from dissatisfied switchers 3. dissatisfied customers, who are potential “dissatisfied switchers” and whose complaints are handled in satisfactory manner, may become even more satisfied and loyal clients – so called “satisfied repeaters”. As a result, they shall not only repurchase from the company, but shall also convert the negative word of mouth into the positive one. Apart from dissatisfaction consequences described by Hirschman – exit or voice, it may also happen that a dissatisfied customer will not voice and will not exit. In such case the dissatisfied customer will not voice a complaint, as he or she believes that there will be no benefit from such action – no positive response from the company. At the same time, he or she will retain with the company, as there is no other available or no better product or service provider. Such consumers are called dissatisfied repeaters. They are most often acting in the low competition or even monopoly markets – e.g. state-owned services, where a choice is limited or none, therefore despite dissatisfaction, consumers need to repeat the purchase. However, if the economic environment changes, competition increases and more interesting offerings appear, dissatisfied repeaters are likely to switch to those new options. Therefore those customers shall also be in the loop and actions shall be taken to increase their satisfaction levels so as to prevent them from switching to other companies. 19
The below table presents four types of customers, out of which two were described above – dissatisfied switchers and dissatisfied repeaters. Figure 1.3. Four customer types
Repurchase Behaviour Repeat
Switch
High
Satisfied Repeaters
Satisfied Switchers
Low
Dissatisfied Repeaters
Dissatisfied Switchers
Customer Satisfaction
Source: Johnson 1996 The empirical studies on satisfaction and dissatisfaction influence on business performance in general confirm and support the conclusions, that;
satisfaction is of crucial importance for business performance
satisfaction has positive impact on business results
retention, as a result of satisfaction, has positive influence on lower costs and higher returns
dissatisfaction may lead to customer base decline and therefore generate lower return
In more detail, the discussed studies justify organizations’ choice of customer orientation strategy. Starting from positive influence of customer retention on lower costs and higher, increasing profits and ending with higher return on investment for companies, who are able to raise customer satisfaction levels – these are all undeniable evidences, that investment in customer satisfaction and retention shall be the key area of focus for managers. In particular in maturing economies, where market dynamics presents a one-digit quote or even zero number, where markets are saturated with competing, comparable products or services, it is important to adopt defensive strategy. Defensive marketing concentrates on customer retention by either increasing customer satisfaction or building switching barriers and is opposite to offensive marketing, which focuses on increasing market size and building market
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share. Majority of companies adopt balanced mix of both strategies - acquiring new customers and retaining the current ones. However, in maturing economies, the skewness is towards defensive strategies, as it becomes more and more difficult and costly to acquire new clients. Therefore, increasing customer satisfaction has become a key focus area for managers in today’s organizations. In the course of this chapter we have proven the undeniable importance of customer satisfaction for increasing business excellence and described the studies, which measure the impact of customer satisfaction on ROI and on stock prices. We came to the conclusion that as increasing customer satisfaction has positive effects on business growth, it shall be the top priority for the management. However, we have also discussed that in order to satisfy the customers better, it is necessary to diagnose current level of satisfaction by establishment and implementation of customer satisfaction measurement model. Thank to such model, the weaknesses of current offerings can be spotted and eliminated to deliver products capable of satisfying the customer to larger extent. However, to build the satisfaction measurement system, it is necessary to understand the concept of satisfaction, its drivers and consequences. Therefore next chapter will focus on theoretical framework of satisfaction, its antecedents and consequences.
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2. THE THEORY OF CUSTOMER SATISFACTION 2.1. The definition of customer satisfaction In the literature, there has been discussion about two major concepts of satisfaction; transaction-specific satisfaction and cumulative satisfaction (Gustafsson, Herrmann, Huber, Johnson, 1997). The first one is described as customer evaluation of single experience with a product or service – therefore how happy the customer is with the offering at given point of time, during concrete transaction. Transaction-specific concept refers to satisfaction as the evaluation of single experience. Opposite to transaction specific satisfaction is the concept of cumulative satisfaction, which understands satisfaction as customer’s up to date experience with a product or service. In such comprehension, satisfaction is the sum of evaluations of all purchase and consumption experiences with a product during whole relationship. During the course of this paper, cumulative satisfaction concept will be used, as it is more appropriate for automotive industry. In this durables business, purchases are infrequent and satisfaction is understood as a long term experience. The owners of the cars, if asked about satisfaction with the particular brand, refer to cumulative satisfaction – they talk about purchase experience, vehicle use experience, ending with after-sales service experience. 2.2. Antecedents of customer satisfaction Satisfaction has its antecedents or drivers – factors, which influence the satisfaction levels. In general, there are two major drivers of customer satisfaction – product’s performance, which includes both product’s quality and product’s value (relation of price and quality). In more detail, satisfaction drivers were initially defined in two models in the literature – disconfirmation model, which is often associated with transaction-specific satisfaction and performance model used in studies of cumulative satisfaction. Specifically, the theory of the models and the differences between them are described below: a) Disconfirmation model Referring to disconfirmation model, the difference between perceived product’s performance and expected performance is a driver of satisfaction. 22
Disconfirmation model assumes that satisfaction increases if performance exceeds expectations – in such case we talk about positive disconfirmation. In the opposite case, when product or service performs below expectations, there is negative disconfirmation effect, which leads to decline in satisfaction. The figure below graphically presents the reasoning of disconfirmation model. It assumes that expectations may have both positive and negative influence on satisfaction. If performance increases over constant expectations, there is positive disconfirmation, which positively influences satisfaction. However, if expectations grow above constant performance, there is negative disconfirmation of expectations and satisfaction decreases. Such transaction specific gaps are than aggregated into an overall customer satisfaction (Johnson, M.D., 1996). Figure 2.1 The Disconfirmation Model
Performance minus expectations
+
Customer satisfaction
Source: Johnson, M.D., 1996 b) Performance model Within the performance model, expectations of product or service performance are similar to product’s image, which is based on either personal experiences with the product or information and opinions heard and learned from other users. As opposite to disconfirmation model, expectations have only positive influence on satisfaction. Moreover, expectations shall have positive impact on perceived performance, what means that expectations are able to predict current level of performance. In addition, if expectations are strong, than they shall positively influence the perceived performance – therefore in such case the evaluation of performance may be far from real performance level.
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Figure 2.2. The Performance Model
Expectations
+
+ + Customer satisfaction
Performance
Source: Johnson, M.D., 1996 Despite the expectations importance in the performance model, it is the performance, which is main driver of customer satisfaction. Based on the model, performance has positive effect on satisfaction level. The graph below represents the performance model (Johnson, M.D., 1996). Comparing disconfirmation and performance models, it is necessary to say, that the second one has been evaluated as more appropriate model for predicting customer satisfaction. In general, empirical studies of satisfaction confirm that expectations have rather positive than negative influence on satisfaction. Moreover, disconfirmation model is adjusted to studies of transaction specific satisfaction, while majority of empirical studies understand satisfaction as cumulative, not transaction specific. As an effect of the above arguments, performance model is evaluated as superior to disconfirmation model in the studies of customer satisfaction. Such conclusion will be also valid in the practical part of this work, as the satisfaction measurement model will be assessing up to date experience and therefore satisfaction with the automobiles, rather than single transaction satisfaction.
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2.3. Consequences of customer satisfaction. Satisfaction has not only its drivers – performance and expectations, but also its results – loyalty and retention. Those two consequences are correlated with each other, but are at the same time distinct results of customer satisfaction. Loyalty is only expressed psychological predisposition toward purchasing and/or using a particular product/service once again, however it does not guarantee a success to an organization measured as customer retention. In other words, loyalty is a high perceived or expressed likelihood of repurchase or willingness to pay a higher price, but does not mean, that customer will repurchase from an organization (Johnson, M.D., 1996). It is the retention, which is ultimate consequence of satisfaction and which is the actual act of repurchase. There are various reasons, due to which loyal customer – or the one, who expresses the loyalty attitude, in the end switches to competition. The Customer Experience Model (presented in the figure below) explains why loyalty does not necessarily end up with retention. Figure 2.3. The Customer Experience Model
Customer’s internal knowledge database
Customer perceptions, judgements and choice
Consumption, customer satisfaction and loyalty
External market infomation
Source: Johnson, M.D., 1996
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The model separates the consumption experience and resulting satisfaction and loyalty from the repurchase decisions and explains, what happens, when potentially satisfied consumer does not repeat the purchase with the same company. Based on the model, there are three aspects of product or service consumption and the consecutive satisfaction and loyalty. First of all, customer relation with the company starts with the decision about the product or service purchase and the consumption. As a result of consumption experience, customer forms the evaluation, perception and expectation towards the product and at the same time, he or she becomes more or less satisfied with the product. Secondly, during the consumption process, consumer stores in mind all the information learned regarding experience with the product. He or she uses those experiences and information when making decision about the future repurchase. Supposing that he or she is satisfied with the product, this makes him or her more predisposed towards repeated purchase. Finally, the consumer comes to the decision about repurchase of the product. He or she will most probably make the decision based on the knowledge and experience gained so far. However, as the world is changing, customer is exposed to new information during the consumption – repurchase process. He or she receives information about new offerings, is exposed to word-of-mouth information. As a result, even though customer is satisfied with the current product and expresses to be loyal, external markets conditions may influence his decisions and he or she may switch. Such customers are called satisfied switchers – they may switch e.g. from Audi to BMW, because BMW will offer better priced offer – therefore customer will perceive BMW as higher value car, or BMW will offer technological advancements, that Audi is not able to deliver. On the other side, the above described scenario may not happen. Even though a customer is exposed to external information and knows other options, he may stick with the current brand and repurchase. But such case will most often happen by habitual, daily purchases. In case of durables – and such is the automotive industry, companies need to make sure, that they have the absolute competitive advantage and that no other brand is capable of attracting current customers. Both satisfaction drivers and results are linked in a theoretical framework, which helps to understand the relations between drivers and effects of satisfaction. The framework is presented in the below figure. 26
Figure 2.4. A framework for linking quality, satisfaction and retention
Internal product and service production and maintenance process
Perceived value, quality, and expectations
Customer satisfaction
Customer loyalty and complaint behavior
C O N T E X T
Customer retention
Source: Johnson, Herrmann, Huber, Gustafsson, 1997 At the beginning of the whole process is the actual production of product or service and placing an offer to the consumer. Providing that the product matches consumers needs, the consumption process starts. During that process, consumers evaluate the product with regard to its performance – understood as evaluation of quality, value (equal to quality versus price paid and price paid versus quality) and confront the performance versus expectations. Such evaluation lays ground for perception of satisfaction – the extent to which product or service met customers needs. The level of satisfaction or dissatisfaction strongly affects and predicts customer loyalty and as a result customer retention, however it guarantees nothing, as even satisfied customers may switch to competition. Therefore in order to retain customers, companies need to continuously improve current offering, present revolutionary and innovative products and constantly deliver higher customer value. In other words, satisfying a customer is a constant process, which means that new and better ways need to be found to customer needs. To summarize, customer satisfaction is important concept for business performance and has measurable impact on business results. It is due to the fact that satisfaction influences loyalty and consecutive retention. In other words, dissatisfied consumers may substantially negatively impact business results. Therefore, it is of extreme importance to measure the current satisfaction levels to be able to spot problems, eliminate them and deliver improved products and services to customers in order to lift current satisfaction levels.
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Having discussed the theory of satisfaction, its importance and impact on business performance, we will now discuss satisfaction measurement systems developed so far within the literature.
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3. CUSTOMER SATISFACTION MEASUREMENT SYSTEMS 3.1. Antecedents of satisfaction measurement system implementation – customer’s personal values research Referring to customer orientation strategy, an organization, which recognizes the need to make its customers more satisfied, shall first develop the customer satisfaction measurement system in order to evaluate current level of satisfaction and be able to translate findings of the study into the specific improvement plans. Therefore, for each organization, which is customer focused, settlement and implementation of customer satisfaction measurement system is a must and a major step towards customer satisfaction growth. However, customer satisfaction measurement systems are just part of overall customer research. Before any satisfaction measurement system is implemented, an organization shall get to know its customers better. This includes knowledge of demographic characteristics, such as age, gender, income, but most of all the set of customer’s personal values. The theory, which justifies the importance of the knowledge of customer’s values is the means-end theory. The theory explains how the choice of concrete product enables the consumer to satisfy his or her personal values. In other words, how the “means” – products lead to desired end states – called “ends”. Referring to the theory, customers consider products as bundles of attributes (Johnson, Herrmann, Huber, Gustafsson, 1997). During the decision - making process, they do not analyze the attributes of the offering separately, but they analyze all product attributes together as a set, and based on their perceived utility, customers make decision about the offering purchase. As a result, these are those attributes, which enable the customer to fill his or her wants. What drives customer perception of attributes utility and ability to satisfy his or her wants are the personal values in life, which the customer is trying to satisfy and which guide his or her decision-making process. The central hypothesis of the means-end theory is that customers consider bundles of products attributes to be the instrument (means) for fulfilling desirable goals or values (ends) (Johnson, Herrmann, Huber, Gustafsson, 1997). The means-end theory argues, that customers make their decisions about the product purchase based on the knowledge gained during up to date consumption process, which is structured into so called means-end chains. These chains link product’s attributes, utility components
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and set of personal values into a process, which explains, what drives customer decision about the purchase and how the process is being conducted. Figure 3.1. The means-end model
attributes
concrete
abstract
utility components
functional
socio-psychological
set of values
instrumental
terminal
Figure 3.1. Johnson, Herrmann, Huber, Gustafsson, 1997 Attributes, which are products characteristics, can be divided into:
Concrete attributes – which include physical, chemical or technical properties of the product
Abstract attributes – which are as opposite to concrete attributes, non-measurable ones, they are one’s subjective perceptions about the products, e.g. aggressive line of the vehicle
Based on concrete or abstract attributes of the product, consumer evaluates its utility. There are two types of utility assessment, which are connected with two kinds of attributes:
functional utility is the assessment of the concrete attributes – therefore of physical characteristics of the product.
socio-psychological utility is connected with abstract attributes – usefulness and results of non-measurable attributes, e.g. thank to aggressive line of the vehicle customer will feel much younger, when driving the car.
Finally, the set of values is understood as series of individual standards, which remain constant over period of time and serve to formulate goals in life and put them into practice in everyday behaviour (Johnson, Herrmann, Huber, Gustafsson, 1997). In other words, personal
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values are the ultimate drivers of consumers’ behaviour and decisions. The values are split into two distinct types:
instrumental goals consist of moral (tolerance, responsibility, honesty) and achievement-oriented values (logical, intellectual and imaginative)
terminal values include desirable goals in life, which can be divided into personal values (inner harmony, maturity in love) and social values (global peace, national security).
Based on the means-end theory, consumers will choose products with attributes, which will produce desirable consequences – therefore will offer desirable utility components and will respond to customer’s personal values. For example, if social acceptability value is core to customer, than he or she will choose a car with high brand image, e.g. BMW, as driving the BMW will confirm his or her membership in a high class of society and will impress family, friends and colleagues and as a result will lead to feeling of social acceptability. Such customer will under any circumstance choose e.g. a Fiat brand, as this is brand has value or mass image and will not impress the others and therefore will not lead to social acceptability feeling or state. In general, consumers hold different personal values in their lives and based on those values, they make choices between offerings. Knowledge of customers’ values helps the organization to tailor its offerings to those needs and by that respond to them better than competitors. As the end result, such action will ensure that organizations’ product, not the competitors’ is chosen and that customers’ satisfaction is brought to higher levels. In more detail, all customers of a particular company have diverse values and needs. As a result of such heterogeneity between customers, only differentiated offerings are able to satisfy customer’s diverse needs. Specifically, based on the knowledge of customers’ personal values and needs, a firm’s clientele shall be divided into groups, which will be homogenous inside and heterogeneous between the groups. Only such segmentation will enable to:
deliver products tailored to needs of each customer segment
lead to higher satisfaction of firm’s clientele.
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Therefore before satisfaction measurement system is implemented, creative and flexible research methods shall be used to discover the hidden needs and values of customers. Most often qualitative methods used for this part of research are focus groups, face to face interviews, surveys, laddering methods etc. After knowledge of customer personal values is gained, satisfaction measurement system shall be implemented, as it is the most informative tool to measure the extent, to which product attributes are able to respond to customer needs. 3.2. Rationale for development and use of industry or nation universal customer satisfaction measurement indexes Thank to knowledge of customer’s needs, company is able to evaluate, how well its current offerings serve customer needs. Such evaluation shall be done with use of customer satisfaction measurement system. Satisfaction measurement system is a crucial part of customer research helpful in diagnosing customers’ satisfaction levels. Such findings are good guidance about areas of products performance, which shall be improved in order to lift the satisfaction to the next level. Many companies have been measuring satisfaction levels on continuous basis. It has been done in more or less advanced manner and most probably many tools – mainly qualitative - were developed to measure customer satisfaction. However regardless of the advancement of methodology used by single companies, satisfaction measurement systems developed for a single organization have major limitations. First of all, measurement systems of that kind can not verify whether satisfaction index equal to 80 is a “high” or “low” result, as there is no benchmark. As companies build satisfaction measurement systems based on different methodologies and measurement indexes, which are tailored to only this organization’s competitive environment, results are not comparable between the organizations. It means that satisfaction index of 70 scored by company A’s may be in reality higher result than index of 80 reached by company B provided that both companies use different satisfaction measurement systems. Secondly, such indexes deliver results, which are not comparable within the industry. It implies that it is not possible to say, whether index of 80 is “good” or “bad” result on industry level, as there is no average for industry available. Therefore, it can not be assessed if companies in industry A satisfy their customers better than companies in industry B. 32
Finally, without unified, industry or even nation wide index, satisfaction levels can not be compared across companies from other industries, sectors or other countries. To summarize, without usage of industry universal index, an organization can only monitor progress and dynamics of its customer’s satisfaction over time. Such firm is even not able to say, whether the score is on high or low level. What is more, there is no benchmark to competition, not to mention industry or other economies. In order to respond to such limitation and enable comparisons, nation and industry wide measurement models were developed in various countries and continents. The ones that are perceived as pioneering ones and which laid ground for further development of satisfaction models were: 1. Swedish Customer Satisfaction Barometer – SCSB 2. American Customer Satisfaction Index – ACSI 3. European Customer Satisfaction Index – ECSI
3.3. National Customer Satisfaction Indexes 3.3.1. Swedish Customer Satisfaction Barometer First national customer satisfaction index was developed in Sweden in 1989. It was designed in such a manner, that it enabled for estimating satisfaction index on the level of company and total industry. As a result, it enabled to make comparisons of satisfaction measurement results between companies, but also industries. Since SCSB establishment, data was collected annually. Every year customers of about 100 companies from 30 leading industries were contacted for the interview, what resulted in ca. 25 000 respondents answering to the survey questionnaire every year. Respondents were contacted via telephone and during ca. eight minute survey they were answering to the questions using 10 point scale (Fornell, 1992). The customers evaluated their satisfaction with organizations offerings on the brand level. However, if a company was selling multiple brands, only the largest brand was chosen to represent the company.
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After data collection results of the survey were analyzed using partial least squares methodology, which details will be described in further chapters of this paper. The structure of the original SCSB model is presented in the below figure. Figure 3.2. The SCSB (Swedish Customer Satisfaction Index)
Perceived Performance (Value)
Customer Complaints
Customer Satisfaction (SCSB)
Customer Expectations
Customer Loyalty
Source: Fornell, 1992 In each satisfaction measurement model, which will be discussed within the course of this work, satisfaction is central variable and has its antecedents and consequences. What is more, usually all or majority of variables in the model are latent variables – variables, which can not be observed separately. Each of the latent variables is described by set of observable variables. Within the SCSB model, satisfaction is a function of only two antecedents – expectations and perceived performance. This part of the model is based on the performance model described in the chapter 2.2 of this paper. Expectations are defined as what customers expect regarding the product performance – how well, they believe, the product or service will perform. In the SCSB model, expectations play an important role as determinants of satisfaction. According to the model, they shall positively influence the perceived performance, as customers learn from experience and based on the knowledge form expectations towards a product performance. Moreover, as
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expectations forecast firm’s ability to provide future performance, it is argued that expectations shall have positive impact on satisfaction (Andreassen, Cha, Gustafsson, Johnson, Lervik, 2001). The SCSB model lays heavy importance on confirmation / disconfirmation of expectations, as driver of satisfaction. Expectations are not only included as a separate construct, which influences perceived performance and satisfaction, but discrepancy of expectations is also part of definition of satisfaction construct. In the SCBS index expectations are the observable variable, operationalised by just one question. Second driver of customer satisfaction in the SCSB model - perceived performance (value) is defined as relation of product price to product quality. This variable is described by two measures:
quality given price
price given quality.
In other words, authors of the SCSB model believe, that customers evaluate product’s performance by comparing the quality of the offering versus price paid and price paid versus quality of the offering. Perceived performance is expected to positively influence customer satisfaction – when it increases, so does the satisfaction. Satisfaction variable in the SCSB index described by three measures: 1) general satisfaction, 2) confirmation of expectations, 3) the distance from the customer’s hypothetical ideal product or service (Fornell, 1992). Such defined satisfaction is expected to have two immediate consequences – customer complaint and customer loyalty. Customer complaints are measured by two variables – complaint to personnel and complaints to management. Similarly, customer loyalty is also operationalized by two variables: (1) tolerance to price increase – how much more the customer is ready to pay provided that he or she is likely to repurchase, (2) declared repurchase intention. Such consequences of satisfaction are derived from previously discussed Hirschman’s exit – voice theory. Based on it, if a customer is dissatisfied, he or she may either stop the relationship with a company (exit) or complain (voice). Within the SCSB model, there is 35
relation between customer complaint and customer loyalty. The authors of the model suggest that, if the company develops proper complaint handling system, the complaining customers may turn into loyal ones. However, if the company does not handle complaints, customer exit is likely. The SCBS model, as the first national satisfaction measurement system, delivered few key findings, which were later often discussed in the literature. Firstly, the SCSB index turned out to be higher for industries, where: 1. offerings were differentiated and customer demand was also such, therefore match between supply and demand was possible. An example is an automobiles industry, where heterogeneous demand was satisfied by differentiated offerings and this industry in 1991 scored 78 on satisfaction index. 2. needs and supply were homogenous – basic foods (milk, sugar) scored also highest results in 1991 – 78 as in case of automobile. Secondly, lowest satisfaction levels were visible for industries, where heterogeneous demand could not be matched by supply, which was not differentiated. Good example of such industry is television broadcasting, which received one of the lowest scores of SCSB index – 48. Finally, it was apparent, that services received lower scores on satisfaction index than products (Fornell, 1992). The Swedish Customer Satisfaction Index, as the first truly national satisfaction measurement system, laid ground for development of the indexes in other countries, as well as other continents. 3.3.2. American Customer Satisfaction Index Second national satisfaction measurement index was developed in United States in 1994 and was named The American Customer Satisfaction Index. The methodology of the ACSI was based on the SCSB, however due to size of American economy, was applied to larger number of companies, industries and sectors. The largest companies from industries representative to major industry groups, which were chosen from seven major economic sectors were included in the design of the sample used in ACSI research. As a result, in 1994 ACSI research covered more than two hundred companies from over forty industries in the seven major consumer sectors of the economy (Anderson, 36
Bryant, Cha, Fornell, Johnson, 1996). Within each company approximately 250 interviews with company customers were conducted. Respondents were supposed to answer brand or model level questions using 10 point scale. As in case of SCSB, partial least squares methodology was applied to the analysis of the results from the survey. The structure of the ACSI model was based on the SCSB, however there were few differences regarding model structure, but also measurement properties of the model. Figure 3.3. The American Customer Satisfaction Index (ACSI) Model
Perceived quality
Customer Complaints
+
-
+ Customer Satisfaction (ACSI)
Perceived value
+
+
+ Customer expectations
+
Customer Loyalty
Source: Anderson, Bryant, Cha, Fornell, Johnson, 1996 The major improvements in the ACSI versus SCSB models are as follows: 1. Expectations variable is explained by three observable variables - as opposite to SCSB, where it was measured by only one construct. 2. Perceived performance (value) construct used in SCSB model was replaced with two separate constructs – perceived quality and perceived value. The first one measures the influence of the quality and the second one the influence of the price on
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customer satisfaction. Such modification enables to evaluate, whether satisfaction in certain companies or industries is more driven by price or by quality of the offering. Perceived value variable was described by two questions – quality relative to price and price relative to quality. Perceived quality variable is measured by three questions, which enable to confront the product or service actual performance versus expectations held by customer before the purchase. 3. Customer loyalty is described by one extra variable as compared to SCSB index – the additional variable is supposed the give answer to the questions, of how much the price would need to be discounted to encourage the customers to repurchase, provided that they are unlikely to repurchase. Findings from ACSI index contributed greatly to explanation of satisfaction concept and its consecutive driver - loyalty. In general, in line with findings from SCSB index, the ACSI Model confirmed, that satisfaction is greatest in goods, lower in services and definitely lowest in public administration. However, satisfaction scores for goods and services were higher in ACSI than in SCSB. Referring to literature, satisfaction levels are expected to be higher when competition, differentiation, involvement, or experience is high or when switching cost, difficulty of standardization or ease of evaluating quality is low (Anderson, Bryant, Cha, Fornell, Johnson, 1996). Authors of ACSI model used those findings to conclude, that satisfaction is higher in U.S. compared to Sweden due to higher differentiation and competitiveness in U.S. To comment further on that conclusion, it shall be also taken into consideration, that cultural and psychological conditions may to large extent explain those differences. As Americans are much more optimistic than Europeans on average and Swedes in particular, this shall in general predispose Americans to choose higher scores on the scale, when responding to survey questionnaire. Furthermore, the ACSI model delivered important findings, which explain the complex theory of satisfaction and loyalty. Specifically, there were three major conclusions from the ACSI Model (Anderson, Bryant, Cha, Fornell, Johnson, 1996): 1. Customization of an offering (how well does the offering fit the personal needs?) is more important than reliability of the offering (how often has the things gone wrong?). Naturally, customization is more important for services than manufactured goods, however it still implies that tailoring the product or service to customer’s needs shall have larger impact on perceived quality and satisfaction than standardizing the 38
offerings in order to ensure greater reliability. 2. Expectations have stronger influence on perceived quality and perceived value for industries, where there is relatively low variance in consumption and production – and where customers make routine purchases. Once the variance in offerings is large and so is variance in consumption, than expectations shall have weaker impact on perceived quality and price. As a result, expectations impact turned out to be lowest in manufacturing durables, finance/insurance and services. The same conclusions were valid with regards to expectations influence on satisfaction – lowest impact was observed in manufacturing durables and finance/insurance. Simplifying, the latest quality experiences with an automobile or insurance play more central role to satisfaction than expectations held before purchase. If a customer is more engaged in the decision process and the purchase, product performance will influence to larger extent his or her satisfaction than the expectations held before the purchase and before the experience with the offering. 3. Based on ACSI Model, quality has larger impact on customer satisfaction than value. As long as value concept plays important role in customer attraction and during decision-making process, quality is more important in satisfying the customer and therefore predisposing him to be loyal and retain with a company. There were industry differences visible; price-driven satisfaction was highest for non-durables, while lowest for durables, services, retail and government agencies. Implication from this finding is such, that in maturing economies, where industries are saturated, where supply is heterogeneous where acquiring the customer is extremely difficult and in practice very often equals taking over competitor’s customer base, quality is crucial and is much stronger predictor of customer loyalty and therefore probable repeated purchase than price. The ACSI Index was widely commented after its creation and it was also tested and applied in many empirical studies. It also laid ground for development of European based index called the European Customer Satisfaction Index (ECSI). 3.3.3. European Customer Satisfaction Index The goal of ECSI development was to supply European companies and countries with similar diagnostic tool as American counterparts have been using since 1994. Moreover, development 39
of similar index enabled the comparisons between countries within Europe, but also between Europe and North America. The ECSI model was developed and tested for the first time in 1999, while second round of research was carried out in 2000 with minor changes implemented to the original model. Twelve European countries participated in the 1999 project. In terms of industries covered by ECSI model, telecommunication was included in the research in all markets, while retail banking and supermarkets in almost all participating countries (Juhl, Kristensen, Ostergaard, 2002). It was also possible to include sectors of special interest in single markets, as it was in case of Denmark. For majority of companies in each country, about 250 of their customers responded to the telephone survey. As a result, almost 55 000 interviews were held in 1999. The ten point scale was used in the survey however results were afterwards adjusted to ACSI 1-100 points scale to enable comparisons between ACSI and ECSI index. Figure 3.4. The European Customer Satisfaction Index (ECSI) Model
Image
Expectations
Perceived quality of „hard ware”
Perceived value
Customer satisfaction
Perceived quality of „human ware”
Source: Juhl, Kristensen, Ostergaard, 2002
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Customer loyalty
As discussed previously, ECSI methodology was based on ACSI model. As in case of SCSB and ACSI models, partial least squares methodology is used for estimation of the model. Furthermore, as in case of ACSI, all variables are latent ones operationalized by few measurement variables – specifically by two to six variables (indicators), which are translated into specific questions asked during the survey. With regard to ECSI model structure, ACSI was an exemplar for ECSI construction, however the latter one is different due to three constructs: 1. within ECSI model, image variable was included, which is expected to influence perceived value, satisfaction and customer loyalty variables 2. perceived quality was divided into separate variables;
a product quality – so called “hard ware quality” – which describes performance of the product/service attributes
a service quality – so called “human ware quality” – the quality of service delivered to the customer (Juhl, Kristensen, Ostergaard, 2002)
3. Customer complaint variable was excluded from the ECSI model as compared to ACSI index. There are also differences compared to ACSI model with regard to variables measuring loyalty construct, which is the ultimate variable explained by the model. Within ECSI model, loyalty is measured by following questions: (1) the product repurchase likelihood, (2) the probability of buying another product from the same company, (3) intention to switch to competitor – price tolerance (4) intention to recommend the offering to other consumers (Gronholdt, Kristensen, Martensen, 2000). The difference in loyalty variable compared to ACSI lies in second and fourth question. Within ACSI first question was the same as in ECSI, however the other two questions in ACSI regarded price tolerance, while in ECSI only third question is dedicated to price tolerance. The remaining ones in ECSI examine the probability of purchase extension to other offerings within the same company, probability of positive word of mouth and probability of product repurchase.
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Among results of ECSI pilot study from 1999 several key conclusions were drawn, from which there is one applicable to Polish economy and business environment in which Company X is operating. The analysis of results for Denmark revealed that the link between satisfaction and loyalty is stronger in competitive industries. In other words, the positive effect of customer satisfaction on loyalty increases with the degree of competition in the market (Gronholdt, Kristensen, Martensen, 2000). This conclusion is extremely crucial for Company X, which operates in highly competitive automotive industry. Based on this finding, it is important, that Company X tries to increase customer satisfaction as such increases shall be strongly reflected in growing customer loyalty. In general, increasing loyalty has measurable, positive effects for business performance. Specifically, there are few key results of increasing customer loyalty for company results: 1. Increasing revenues due to customer retention and repeated purchases 2. Costs decline, as there is no need to acquire new customers, because the current ones stay with the company, so the costs connected with new customers acquisition decrease 3. Employee retention increases as a result of job pride and job satisfaction. As the relationship with customers and familiarity of their needs is sustained customers are served better and therefore their satisfaction and retention increases. Increase productivity results from increasing employee tenure (Hopton, Markey, Reichheld, 2000) As the increased loyalty has such strong influence on business performance, and satisfaction influence on loyalty is stronger in competitive industries, therefore it is of utmost importance for Company X in Poland to make customer satisfaction its priority goal. The Customer Satisfaction Indexes described so far in this chapter – SCSB, ACSI and ECSI are the most important indexes developed so far and used for measuring customer satisfaction and customer loyalty. They are universal methodologies and can be applied to various industries, sectors and on various markets. As a result they allow for comparisons of results and benchmarking between companies, industries and results. However, specific industries often tailor satisfaction measurement studies to the specifics of the concrete industry or even company.
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3.3.4. Automotive industry specific customer satisfaction indexes Within automotive industry, which lies at the heart of this paper, J.D. Power and Associates is the most important and most referred to marketing information organization, which measures the customer satisfaction in the automotive industry. J.D. Power is an independent and unbiased source of customer satisfaction, product quality and buyer behaviour researches. As it is global company, it measures customer satisfaction with brands in many countries what enables companies to compare results on local and regional level. J.D. Power provides following syndicated reports, which deliver information for automotive industry and which are widely used within automotive companies: 1. Initial Quality Study (IQS) 2. Sales Satisfaction Index (SSI) 3. Customer Satisfaction Index (CSI) 4. Automotive Performance, Execution and Layout (APEAL) 5. Vehicle Dependability Index (VDI)
Initial Quality Study Initial Quality Study (IQS) is a research, which is supposed to evaluate the automotive quality after three months of usage. During the study respondents are asked to asses the quality of the car with regard to:
design – problems with design include car components or features, which may be working right, however they may be perceived as difficult to use or understand
defects / malfunctions – this kind of problems include complete breakdown of any component or car feature.
In the course of the study 217 car attributes are evaluated with regards to its functionality and reliability. As a result, the study reports number of defects and malfunctions per 100 cars at the level of whole brand, but also at the model level. IQS study is conducted annually and has been is use for the past twenty years – since 1987. It serves as benchmark for evaluating new vehicles quality. 43
In the latest, 2007 release of the study, 97 000 purchasers and lessees of new car models launched in 2007 were surveyed ninety days after the purchase. Within this study, Company X scored enormous improvement as a total brand with regard to quality of the vehicles. In the ranking of the brands with lowest rate of faults, it advanced by more than 10 positions. Moreover, such substantial increase was driven by all models and such results have been described by Neal Oddes, director of product research and analysis at J.D. Power and Associates as Company X commitment to quality (http://www.jdpower.com ). Company X as a whole brand received the highest quality ratings with regard to: body and interior quality – mechanical, overall quality – mechanical and power train quality – design. Sales Satisfaction Index Another important J.D Power study, widely used within automotive industry, is Sales Satisfaction Index (SSI). It has also been in use for the past twenty years. As opposite to IQS, which measures automotive quality itself – therefore referring to ECSI it measures “human ware quality”, SSI evaluates the customer satisfaction with dealers and vehicles, therefore so called “hard ware quality” as defined in ECSI. In more detail, it covers the area of sales moment – therefore this is an evaluation of customers’ first experience with the company. Specifically, it evaluates customer satisfaction in five dimensions: dealership facility, salesperson, paperwork/finance process, delivery process and vehicle price (http://www.jdpower.com). This implies that SSI results in evaluation of “human ware quality” to larger extent than “hard ware quality”. The 2007 results of SSI study are not available however in 2006 Company X was positioned in top ten in ranking of automotive brands, whose customers are most satisfied with the car purchase process. Company X scored much above the average for the industry, which in 2006 amounted to 847 points (http://www.jdpower.com ). APPEAL Automotive Performance, Execution and Layout Study (APEAL) is the latest study offered by J.D. Power, as it is in use only since 1996. This is also the only study, which measures the emotional side of car ownership – it examines what customers feel about their cars. The study was designed to complement the IQS study, which concentrates on the quality, while APPEAL on the owners delight with car design, content, layout and performance. 44
The respondent in the study are car owners, who have been using their car for only 90 days. During the research, respondents are supposed to evaluate their cars on more than 100 attributes,
which
engine/transmission;
cover
eight
ride,
categories
handling
and
of
vehicle
braking;
performance
and
design:
comfort/convenience;
seats;
cockpit/instrument panel; heating, ventilation and cooling; sound system; and styling/exterior. The 2007 survey was based on responses from more than 91 000 car purchases and lessees of new 2007 model-year cars and trucks, who purchased their vehicles ninety days earlier. The results of the APEAL study were extremely satisfactory to Company X brand. The brand received highest scores in four out of five measured areas. Such result can be translated into high profitability of the brand, as based on the results from the 2007 study results, manufacturers and dealers of models with higher APEAL scores can offer lower incentives to new-buyers (http://www.jdpower.com). Vehicle Dependability Index One more study offered by J.D. Power and Associates is the Vehicle Dependability Index (VDI). The study is designed to evaluate the long-term experience with a vehicle, as it measures the quality after three years of car ownership. The study covers such areas as durability of specific items, frequency of warranty work, ratings of the work performed and the amount spent on non-routine repairs during the past year (Johnson, Herrmann, Huber, Gustafsson, 1997). Therefore the index is a solid insight for the consumers of the model’s reliability and dependability within the warranty period. Customer Satisfaction Index Finally, J.D. Power could not lack customer satisfaction index in its portfolio - it is called Customer Satisfaction Index (CSI). As all indexes described in previous chapters, the J.D. Power CSI index is supposed to measure the level of customer satisfaction with the car usage during the first three years of the automotive use. The CSI index is composed of variables, while each of them is measured by few questions. Based on results released for German market in 2005, the four variables explaining customer satisfaction are:
quality and reliability of vehicle - covers problems with vehicle,
vehicle appeal – means satisfaction with the vehicle’s performance, design, 45
function and styling
service satisfaction – is understood as customer satisfaction with dealership and service
ownership costs – cover costs of car use, insurance and repairs
J.D. Power vehicle quality and satisfaction measurement studies are used widely among automotive industry organizations. They enable to evaluate satisfaction levels and benchmark them against competitors. Moreover, J.D. Power methodologies, as external ones, are objective in measuring and evaluating satisfaction levels. Therefore they are good indicator of direction, into which automotive firm is heading in terms of vehicle quality, performance, brand image and sales services, which are prerequisites for customer satisfaction, which in turn impacts organizations financial results.
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4. COMPANY X CUSTOMER’S PROFILE Nowadays, majority of companies are conducting mainly qualitative research which measures customer’s values, needs and beliefs. Such qualitative methods are also used to measure consumer demographics. Company X in Poland conducts an annual research with the external agency, which supplies the company with following information: 1. consumer demographics and interests 2. benefits driving the car purchase 3. reasons for vehicle purchase and attitudes towards the car The research is conducted on yearly basis since 2002 by the same research agency, what allows for results comparisons and trends observations. The study, which results will be cited in the next chapters, was conducted in autumn 2006. The research uses mail questionnaires as a data collection methodology. In last year wave there were 326 respondents, who returned the filled questionnaire. Within this chapter, we will present analysis of the results of 2006 wave, which will describe the demographic profile, but also personal needs and values of Company X car owners. 4.1. Company X customers – demographics In general, the analysis of demographics from the 2006 survey allows for customer segmentation into groups, which are homogenous inside, while they differ between the groups:
Compact cars – users of smallest cars and at the same time the most affordable among all Company X models belong to this group,
Mid size cars – cars within this segment are larger and more comfortable than compact cars, and at the same time more expensive as well as more luxurious.
Full size and large cars – these are definitely the most expensive cars, largest ones and most prestigious and luxurious ones.
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Each of the segments can be described by seven dimensions: gender, age, size of household, occupation, income of the owner, previous experience with Company X cars, interests and hobby. Starting with gender, among Company X car owners, 75% of clients is male. Across the segments, there is correlation visible between gender and car size – the larger the car, the larger percentage of men owners versus women. Therefore, largest percentage of women owners is in the compact cars segment, where 32% of the car owners are women versus 25% for the total brand. Contrary, in full size cars segment, 89% of car owners are men. Such results are very natural – the smaller the car, the more appealing to women. As a result compact cars are most often in the possession of women, while only few of them (11% of total population of full size cars owners) own models from full size segment. As Company X cars are premium ones, they are sold at correspondingly high prices and therefore younger consumers in majority can not afford them. This is reflected in the age structure of Company X owners – 78% of respondents are in the age of 29 to 58 years. Another conclusion applicable in the analysis of age structure of respondents is that the smaller the car and therefore more affordable, the youngest and the oldest consumers are driving it. Within the owners of compact cars, there is largest percentage of youngest (below 29 years old) and oldest respondents (above 59 years old) as compared to other segments – 7% and 16% respectively. Such observation is related not only to the fact that disposable income of youngest and oldest consumers is relatively lower than of mid age consumers, but also to the fact, that compact cars are proper size cars at youngest and oldest stage of life, as respondents at this stage of life usually don’t have the children yet or already don’t have children dependent on them. The Company X car owners most often have four members in the family (over 50% of respondents). However, within compact cars segment, 2-persons families are statistically more often. This finding is in line with the analysis of age structure – the youngest and oldest customers are most often driving compact cars, as they are of comfortable size for their twoperson household. The largest group among Company X customers are managers - entrepreneurs (private companies’ owners), managers, directors and business owners – 45% of respondents. Second 48
largest group is intellectuals (doctors, lawyers, scientists) – 22% of respondents belonged to this group. There were significant differences visible among segments; among compact cars owners, intellectuals were much more visible than in mid size and full size car owners. On the other hand, managers are largest group among owners of full size cars as compared to other segments. Such relation has its background in the income – as the managers are on average most affluent group, they are most likely to purchase full size car as opposite to less affluent intellectuals. The size of the car is reflected in its price, therefore the larger the car, the higher the price and as a result higher income of the owners. Such relation was observed in the analysis of income among Company X car owners. Respondents, who are driving compact cars, have on average lower income than mid size car owners and much lower than full size car drivers. Company X customers are split in half in terms of previous experience with the brand – 51% of respondents confirmed, that they have had a Company X car before the current one. On average more often men and persons working on managerial positions are within this group. Among customers, who had Company X car before, 30% had one car before, while remaining 70% had more than one Company X car before the current one. There were significant differences visible between customer segments with regard to previous experience with the brand. For compact cars owners, statistically more often current car is a first Company X car – this is valid for 62% of compact car respondents, who claim that compact car is their first one. This is opposite to full size cars owners, where for only 22% of respondents this is first Company X vehicle. Moreover, among full size cars owners, 77% of them have had more than two cars of this brand previously. Among those compact car owners, who had Company X before, only 51% had more than one such car before the current one. With regards to interests and hobbies, in general Company X customers are most interested with movies (56% of respondents), house and garden (56%), winter sports (40%), travelling (36%) and music (35%). It is important to note, that during the past four years (2002 – 2006), increasing interest with tennis was noted, while fewer respondents claimed, that they are interested in cooking. This observation is in line with the changes within culture and style of living in Poland and with increasing purchasing power of Polish consumers.
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With regards to differences between models owned and interests, the higher the car model, the more expensive the hobby. Compact car users statistically more often claimed that they are interested in cooking, house and garden, while they claimed lower interest in winter sports and golf. On the opposite side, full size car owners responded, that they are most interested in travelling, tennis, water sports and golf. Such differences are related to financial and social status – travelling or water sports definitely require more investments that interest in cooking, house or garden. On the other hand, sports such as tennis or golf are regarded as sports for people from upper classes of society, those with higher income and such hobbies are regarded as prestigious ones. Therefore full size car owners will more often declare interest in golf or tennis, than in cooking, house and garden. Summing up the analysis of demographic characteristics of Company X car owners, the main conclusions from analysis are:
Company X cars are more appealing to men, as every 3 out of 4 respondents is men. Female respondents are most often driving the smallest models of Company X – compact cars. This implies that if Company X wants to target women, it shall concentrate on offering smaller cars, while the larger cars shall be offered rather to male customers.
As Company X cars are premium ones, therefore they are affordable at maturity stage of life, when disposable income is relatively larger – 78% of respondents are in the age of 29 to 58 years. Therefore marketing efforts such as communication, marketing campaigns shall be focused on places, media channels, which are most often used by respondents in such age. However, if there is desire to attract younger customers, than smaller models shall be offered to them, as these are the ones that this target group can afford.
As Company X cars are premium cars, customers most often purchase compact car as their first car of this brand – 62% of compact cars owners declare, that this is their first vehicle of Company X, while only 22% of full size cars owners confirm this statement. This implies that to gain new customers, compact cars will be the best incentive. Furthermore, to overcome high price barrier, promotional tools shall be used with the offer of smallest cars, as they shall be most effective in case of new customers. On the contrary, clients who decide to purchase larger models as their first Company X car are affluent enough and as a result price incentives will rather not 50
be effective tool to attract their attention.
Company X shall target mainly managers and intellectuals with its offerings – 67% of respondents belong to those two occupation groups. It shall be noted however, that offerings which will meet intellectuals’ needs are those placed in the compact car segment, as they are the affordable ones for this group. Contrary, managers shall rather be targeted with mid-size and full size cars, as these are the ones affordable by this group, but also the ones, which are more prestigious to drive.
As owners of Company X cars are mainly in their mature life stage, most often four persons live in their household – two adults and two children. This implies, that Company X shall offer solutions friendly to families – comfortable sizes of trunks, foldable back seats to fit more luggage if necessary.
With regard to income of respondents, compact car owners are on average less affluent than respondents, who drive mid size and full size cars. Therefore offerings for compact cars customers shall deliver more value for money, as these customers will be more price sensitive than owners of mid size of full size models.
The analysis of Company X customers’ demographics showed also, that there is justification for segmentation of respondents into three groups – compact cars, mid size cars and full size cars, as respondents within these groups are homogenous. The differences between respondents within each group and the average for total Company X are as below:
The average Company X client is male (75% of respondents) in the middle age – from 28 to 58 years old. Every second respondent lives in a four persons households (50% of customers). Almost half of Company X clients are managers, while almost 20% of them represent intellectuals’ group. Company X customers most often agree that their hobbies are movies, house and garden, winter sports, travelling and music.
Compact cars owners – in general, this group differs a lot from mid and full size car owners. Compact car drivers are mainly youngest or oldest customers (below 29 years old or above 59 years old). Majority of this group belongs to intellectuals, pensioners and students. Within this group, two person households are much more often present than in other groups. Compact car drivers have also the lowest income compared to other groups – as they are either youngest or oldest persons, therefore least affluent. Statistically, women more often drive and own compact cars than other
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models. Respondents within this group have only started their adventure with Company X brand – within compact cars owners there is largest percentage of customers who declare, that this is their first Company X car. In terms of interest and hobbies, respondents within this group declared more often than customers within other groups that their hobbies are those least demanding in terms of financial input – cooking, house and garden.
The profile of mid size car owners is most similar to average demographic profile of Company X customer. 80% of customers within this group are men. They are in their maturity stage of life, being between 39 to 58 years old (64% of respondents). Their households are of traditional size – three of four persons. Almost half of the customers in the mid size car segment are managers (45%) followed by intellectuals. Their income is on the level of average income observed for Company X customers. For 50% of customers within this group current Company X car is not the first one – they have had a car of such brand previously. In terms of interests, customers within this group statistically more often claim interest in pop music, tennis and soccer.
The owners of full size models differ a lot compared to compact car drivers, but there are similarities to mid size cars owners. The owners of full size Company X cars are in almost 90% men. As in case of mid size car owners, they are most often in the age of 39 to 58 years old – within this group there is lowest percentage of youngest (below 29 years old) and oldest (above 59 years old) respondents. They are well settled in life – in majority they work as managers and their income is the highest among Company X customers. Customers within this group have larger families – most often four persons within the household. Furthermore, as they are the wealthiest group, they have largest experience with the Company X cars – 78% of customers from this group have had Company X car before. Customers within this group statistically more often declare, that they have either expensive or prestigious hobbies and interests – they are more often than other customers interested in travelling, tennis, water sports and golf.
The differences between three core groups of Company X customers deliver important knowledge to the management, which enables to target each customer segment with such offer, that it is adjusted to each customer profile and by doing so maximize the probability of satisfying the customer. The analysis of factors, which drive the decision of car purchase,
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shall deliver more detail knowledge of customer needs and values, which shall further enhance the knowledge of differences between customer segments.
4.2. Company X customers – benefits driving the car purchase During the annual customer research, not only customer profile is measured, but also Company X customers are questioned to point out three most important benefits, as well as factors, which are crucial in their car purchase decision making process. Respondents are asked to choose three most important benefits from the list of fourteen, which are the most important for them when deciding about the car purchase. The benefits and factors used in the survey are: 1. Safety of the vehicle 2. Comfort of the vehicle and delight from driving 3. The technological advancement of the car 4. The brand image 5. The unique design of the car 6. Previous experience with the brand 7. High expected return if car is sold after few years 8. Functionality and economy of the car 9. Prestige due to car ownership 10. Recommendation from a friend regarding the car 11. Promotion or advertising influence 12. The environment friendliness of the car 13. After sales services 14. Other reasons The results of 2006 survey revealed, that in general there are four benefits, which where chosen most often as the crucial ones for Company X customers:
safety of the car – 59% of respondents pointed this factor as one of most important, when purchasing the car
comfort of the vehicle and delight from driving – 56% of those asked pointed this benefit as very important 53
technological advancement of the vehicle – 28% of respondents believe, that this benefit is crucial factor, when purchasing the car
brand image – this benefit was chosen by 27% of Company X customers
On the other hand, the least important factors for Company X customers, which are able to influence the decision about car purchase, were:
after sales service – only 1% of respondents believes, that this is important factor, which is taken into account while making decision about car purchase
the environment friendliness of the car – was also chosen by only 1% of customers
promotion or advertising – this factor was taken into account by only 2% of Company X car owners, when making the decision about the brand they want to drive
These results have crucial implications and are important advices for Company X managers. First of all, based on the survey, safety of the car, comfort and delight from driving are the key benefits that Company X cars shall deliver to their owners. These are also the key car features, which if performed on high level, are able to attract future consumers and retain current clientele. Furthermore, these features shall be claimed in any promotional materials and advertising, as their importance is so high to Company X clients. Secondly, if Company X has any issues with quality, which leads to lower safety, less comfort or lack of technological advancements, than it can expect declining number of customers attracted or the customer exit to happen, as the most important benefits will not be delivered to the customers. Finally, as promotion and advertising factors are least important for Company X customers, those tools shall not communicate promotional activities – attractive pricing or discounts. The advertising shall rather be used for image building, as image is one of the most important factors for Company X clientele. Therefore, instead of communication of promotional incentives in media, advertising shall communicate brand benefits and in this manner enhance the brand image further as the factor taken into account by 27% of respondents during car purchase decision making process.
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The 2006 study revealed the differences between various models owners – other benefits were pointed out as the most important by different model owners. As a result, three customer segments divided based on demographic characteristics may be described by other benefits, which are on average more important for them during decision-making process. Compact car owners pointed out more often than other models owners to safety of the vehicle, brand image and functionality and economy of the car as benefits important to them during the car purchase decision process. The larger sensitivity to those factors is related to demographic profile of compact cars customer segment: 1. Functionality and economy of the car; as discussed before, compact car owners are the group with smallest disposable income. Therefore functionality and economy of the car is on average more important to them than to any other customer segment, as their funds are more limited than funds of other Company X customers. 2. Safety; Company X cars score five stars in the Euro NCAP safety ranking and are perceived as safest cars. Safety benefit does differentiate Company X from other brands and has been pointed out by 59% of Company X customers as very important. However, safety benefit was chosen more often by compact car owners, than mid size and full size car drivers. Such difference is also related to demographics. Compact car owners are the youngest and the oldest customers of Company X and very often compact car is their first Company X car. While comparing the options on the market, they are searching for safe vehicles and if a car is described as very safe, this feature may be decisive for them to choose this particular brand. Therefore Company X cars are more appealing to them than any other brand, as they are perceived as the safest. For mid size or full size cars owners’ safety is more of a granted benefit, as they most often have been driving Company X before. Furthermore, as they are more wealthy customers and they are driving more expensive cars than compact ones, they are searching for other benefits than just safety, which is important, but basic one for them. For the same reason safety is more important for compact car users – as they have the smallest income, they can afford smallest Company X cars and those delivering basic benefits, such as safety. On the other hand, those basic benefits are the ones that compact cars owners are searching for – safety, but also reliability and economy of the vehicle. 3. Image; this benefit is more important to compact size owners than other segments for 55
several reasons. First of all, compact car customers are the youngest and the oldest groups and very often they did not have previous experience with Company X. Therefore, image benefit acts as strong differentiating feature, which makes Company X car more attractive than other brands. Than, as this may be the customer first Company X car, the desire to drive a high image, admired brand car is larger than for customers, who are driving Company X for longer time. For such clients, the desire to drive high image brand has been fulfilled before and therefore is not perceived as important now. Contrary, for compact cars owners, image benefit may be very important, as this may be their first premium brand car. To summarize, customers within compact cars segment perceive safety, functionality and economy of the vehicle, as well as image of the brand as more important factors than mid size and full size cars segments. The skewness towards such benefits is partly related to demographics of the compact car owners; 1) lower income of compact car owners, therefore more focus on basic benefits such as safety, reliability and economy, 2) as the compact cars owners are the youngest or oldest customers, it is very often their first Company X car. As a result safety and image of the car, which strongly differentiates Company X from other brands, push this group towards purchase of Company X, 3) as this may be their first Company X car, the desire to drive high image car may be stronger than for mid and full size car owners, for which this is next Company X model and they are used to such high image cars. Based on the benefits, which are on average more important for compact car owners, this customer segment can be described as functional segment. Mid size cars owners on average pointed more often to comfort and pleasure of driving than other customer segments. At the same time, functionality and economy of the vehicle was chosen very seldom by this customer segment. Such discrepancies are also related to demographic characteristics of this customer segment. Customers within this group have higher income than compact car users and are better settled in life. They are also more often managers, therefore handling high positions within the company, which are associated with higher standard of life. As a result, mid size car owners can choose vehicles, which offer comfort, delight of drive and some portion of image to the users. Those customers take functionality of the vehicle for granted and do not put so much 56
attention into economy of the vehicle, as they can afford higher expenses. They are searching for pleasure, comfort and delight when driving. As a result, mid size car segment can be called pleasure segment, as customers within this group value the delight higher than the functionality. The benefits which were on average more often chosen as the most important ones by full size cars owners were pleasure and comfort of driving, previous experience with the brand and prestige of car ownership. The full size car owners are most affluent customers of Company X. Therefore pleasure and excitement of driving is very important for them and this is why they choose the largest, most expensive and most luxurious models. Furthermore, prestige is important for this group, as these customers are mainly managers, well settled and affluent, therefore they need to be surrounded by prestigious products - with cars between them. Lastly, the current model is not their first Company X car. Those customers have experience with other Company X cars and as a result it influences their decisions about the car purchase. The full size car owners may be called as prestige segment due to benefits, which were pointed by them on average more often than by other customers. The analysis of key benefits, which are most important for Company X customers during the decision about car purchase, revealed that Company X customers can not only be segmented due to demographic characteristics, but also based on key benefits which they are searching for. Company X clientele can be segmented into three distinct groups: 1. compact car owners – so called functional segment. Customers within this group are more often than other customers searching for cars, which are safe, functional and economical and have high image. 2. mid size car owners – so called pleasure segment. Such customers focus more often on pleasure and comfort of driving than customers within remaining segments. 3. full size and large car owners – so called prestige segment. Clients within this segment are those most experienced with Company X and those searching for pleasure of car driving and prestige of car ownership The knowledge of key benefits, which are important for particular customer segments, enables the company to target each customer group with different car attributes which will 57
respond to different benefits. Such knowledge is of inestimable value in creating offerings tailored to customer needs, what in turn drives higher satisfaction and loyalty. 4.3. Company X customers – attitudes to vehicle During the survey, not only demographic characteristics of consumers and benefits driving car purchase were examined, but also general attitude to vehicle. Respondents were asked to agree or disagree with twelve statements describing their attitude to cars. The statements were ranging from “My car shall express my personality” to “I take care of my car myself”. The respondents were supposed to evaluate whether they agree with the statement (4) or disagree (1) or they have no opinion. In general, the statements, with which customers agreed to largest extent, corresponded with most important benefits taken into account during the car purchase process. Respondents to largest extent agreed with following statements:
“The vehicle shall guarantee maximum safety” – 97% of respondents agreed completely with this statement. This is in line with safety benefit, which was pointed out by largest percentage of respondents as important benefit taken into account during purchase decisions.
“I would like to have a feeling, that all latest technical advancements were used in the car” – 94% of those questioned agreed with this statement. This is in line with the technological advancements benefit, which was chosen 28% of Company X customers are key while making car purchase decision.
“I like the vehicles with unique design” and “The car gives me feeling of freedom and independence” – 92% of respondents agreed with both statements completely. This statement corresponds with two benefits; comfort and pleasure of driving, which was chosen by 56% of respondents as important for them and unique design, which is perceived as important factor during car purchase process by 27% of Company X customers.
There were some differences between customers’ demographics and their attitude to vehicle. In general, women are searching for cars, who give them sense of freedom and independence, which have unique design and which express their personality.
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When it comes to age groups, youngest consumers (up to 39 years old) enjoy dynamic driving more than any other group. On the opposite side are customers above 49 years old, who more often treat their car as locomotion only. With regards to differences between various customer segments, they were no strong differences. The only exception is the full size segment (prestige segment). Customers within this segment believe that the car shall reflect their social status and that it shall attract others attention. This is in line with the list of key benefits which are important for this customer group. As discussed before, customers from this segment are on average more often taking into account the prestige of the car ownership when they are making their purchase decisions. As customers within this group are most affluent ones and are most often on high managerial positions, naturally they will be searching for cars, which are prestigious because they believe that the car shall reflect their social status. 4.4. Summary of Company X customer’s profile To summarize the customer profile research study results from 2006, the analysis revealed, that Company X customers can be divided into three major groups. Customers within those groups are alike taking into account their demographic profile, their needs and attitudes towards vehicle. Moreover, those groups are similar in terms of car models that they choose. Contrary, the groups differ significantly between them. The characteristics of average Company X customer and specifics of the three customer segments are: 1. Company X customers in majority are men (75% of respondents) in the middle age – from 28 to 58 years old. 50% of respondent lives in a four persons households. In terms of occupations, almost half of Company X clients are managers, while almost 20% of them represent intellectuals’ group. Company X customers are most often interested in movies, house and garden, winter sports, travelling and music. The most often cited benefits or factors, which are important for Company X customers during car purchase are safety of the car, comfort of the vehicle and delight from driving and technological advancement of the vehicle and brand image. 2. Compact cars owners – functional segment. Among this segment, there is larger percentage of youngest and oldest customers (below 29 years old or above 59 years 59
old) than in remaining segments. Women are also driving compact cars than other models. Majority of this group belongs to intellectuals, pensioners and students and live in two person households more than customers from remaining segments. Compact car drivers have the lowest income compared to other groups and within this segment there is largest percentage of customers who declare, that this is their first Company X car. In terms of interest and hobbies, respondents within this group declared more often than customers within other groups that their hobbies are those least demanding in terms of financial input – cooking, house and garden. Customers within this group are more often than other customers searching for cars, which are safe, functional and economical and have high image. 3. Mid size cars owners – pleasure segment. 80% of customers within this group are men in the age between 39 to 58 years old (64% of respondents). They have households with three or four persons. Almost half of the customers in the mid size car segment are managers (45%) followed by intellectuals. Their income is on the level of average income observed for Company X customers. 50% of customers within this group have had a Company X car previously. In terms of interests, customers within this group statistically more often claim interest in pop music, tennis and soccer. Mid size car owners focus more often on pleasure and comfort of driving than customers within remaining segments. 4. Full size and large cars owners – prestige segment. Customers within this segment are almost only men (90%), in the age of 39 to 58 years old – within this group there is lowest percentage of youngest (below 29 years old) and oldest (above 59 years old) respondents. Full size car owners are in majority managers and their income is the highest among Company X customers. They also have larger families than average Company X customer – four persons within the household. Car owners within this group have largest experience with the Company X cars – 78% of them have had Company X car before. Customers within this group statistically more often than other segments declare, that they are interested in travelling, tennis, water sports and golf. They are also those most experienced owners of Company X and are searching for pleasure of car driving and prestige of car ownership. Furthermore, they more often than other customers believe that the car shall reflect their social status and that it shall attract others attention.
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5. STRUCTURAL EQUATION MODELING AND PARTIAL LEAST SQUARES Partial Least Squares approach is one of the data analysis techniques that is applied to similar problems as Structural Equation Modeling. PLS has been mainly developed by Herman Wold (Wold, 1985), Jan-Bernd Lohmöller (1984, 1989) and by Wynne W. Chin (1998, 1999, 2001). Some researchers claim that PLS is not one of the SEM methods due to different estimation procedures and objectives of the methods as well as different strengths and weaknesses of both techniques. On the other hand beside many differences both methods can be grouped under one set of techniques used to analyze similar problems with conceptually continuous latent constructs. 5.1. Structural Equation Modeling – covariance-based approach Many researchers identify SEM mainly with covariance-based approaches represented by such computer software programs as for example LISREL. This kind of approach is an evaluation of sample covariance or correlation matrix consistence with a theoretical model specified by the researcher. Therefore it concentrates on maximizing fit between sample correlations matrix and parameter estimates meaning that the estimating procedure changes the estimates to improve the fit function until no improvement is possible. The covariance-based techniques optimize parameters by maximizing fit but not variance explained. Therefore estimated models can have very good fit to sample data set which is crucial to interpretation however with low explanatory power. One of important limitations of this methodology is the assumption that the observations are independent and all indicators follow normal distribution which in most customer satisfaction studies is not fulfilled due to strong negative skewness of satisfaction scores. Furthermore SEM does not allow to predict value of latent variables specified in the structure of the model. This property is of high importance especially in customer satisfaction researches where calculation of latent scores is essential to further interpretation of the subject. To sum up covariance-based approaches are very demanding if it comes to distribution of the sample data set plus they concentrate on explaining covariation of all used indicators to prove the theory lying behind the research while not allowing for calculation of latent variable scores. Therefore if created structure of the model is proper in terms of explaining covariation structure of all manifest variables the SEM techniques produce optimal parameters. However there is certain amount of risk involved in the covariance-based 61
technique as under conditions of small sample size or data set violating assumptions about distribution incorrect solutions can result. Furthermore latent variable values are never calculated at the same time eliminating the possibility to predict observed variables. 5.2. Partial Least Squares On the other hand researchers can use PLS technique which is definitely less demanding in terms of assumptions about data distribution, measurement scales and size of sample. Parameter estimates are obtained by minimizing the variance of dependent variables therefore producing the best fit of collected sample data set to defined model structure proved by theory or research assumptions. PLS is aimed at obtaining determinate values of all unobservable constructs that are approximated by their respective set of manifest variables thus avoiding factor indeterminacy. Weighting scheme for each latent variable depends on the kind of relationship assumed between the construct and its indicators. It can be either reflective or formative while other SEM techniques allow only for reflective mode – the modes will be explained further in this chapter. Therefore having all the above mentioned arguments in hand the researchers can view PLS technique more suitable in cases where properties of sample data do not meet assumptions of multivariate normal distribution, where sample size is relatively small, where there is a certain amount of uncertainty between theory and data creating need for theory confirmation or where project requires calculation of scores for unobservable factors defined in the structure of the model for predictive purposes. 5.2.1. Specification of the model Before explaining PLS estimation technique some background on possible model structures as well as names of constructs used in this technique is needed. Let’s consider Figure 5.1. Circles named A and B represent latent (not observable) constructs. Rectangles named ax, ay and bx, by represent manifest variables (observable indicators) that form latent constructs A and B respectively. Arrow scheme represents inner relations of the model (relationships between latent variables) and outer relations (relationships between latent constructs and their respective indicators). Figure 5.1 represents one inner relation of A influencing B and two sets of outer relations – reflective mode of connection
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between A and its respective manifest variables ax, ay and formative mode of connection between B and its respective indicators bx, by. In the reflective mode indicators measure the same unobservable phenomenon in a way that if the level of the latent construct changes than all observable variables should also change in the same direction. The strength of change is dependent on how strong is the Figure 5.1. Structure of latent blocks model with formative and reflective modes
A
xa
B
ya
xb
yb
relationship between the indicator and the latent construct. The strength in the reflective mode is represented by loading (the amount of variance in the indicator that the respective latent phenomenon accounts for). Loadings of manifest variables on their latent construct represent the correlation between them. The question whether researcher should use reflective mode depends on several considerations: -
theory behind the measurement model – if researcher conceptualizes latent construct as a phenomenon influencing responses to the indicators scores the reflective mode should be used
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objective of the study – reflective specification should be used if the objective of the study is to explain and predict the observed variables (maximize variance of indicators)
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empirical conditions – reflective mode assures stable estimates in situations where either sample size is small or there is suspicion about multicollinearity among indicators.
The weights in the reflective specification are calculated in order to create LV that explains as much variance as possible in all its observed indicators. In the formative mode indicators do not represent the same unobserved factor and they are also not correlated to each other. The latter condition arises from the fact that in case of significant correlation of formative indicators the problem of multicollinearity may cause unstable estimates of multivariate regression of latent construct on its manifest variables. Therefore formative variables provide some kind of conditions under which the LV is being created. The aim of formative mode is to maximize the variance explained at the LV level. Therefore all indicators are weighted with the aim to maximize correlations in the inner structure of the model. The decision as to whether researcher should use the formative specification depends on the same 3 considerations as in reflective mode: knowledge on investigated theory, purpose of the research and empirical conditions. If the sample size is large enough, the indicators are not related to each other (no multicollinearity) and are conceptualized as the ones that form the latent construct meaning that the change in the level of latent phenomenon does not necessarily means changes in the same direction for all its indicators the formative mode should be used. Furthermore if the aim of the researcher is to maximize the variance explained in the latent abstracts level not the outer part of the model and there is a substantive theory confirming formative relationships the choice of formative specification is well-grounded. 5.2.2. Estimation PLS estimation procedure consists of 3 stages. In the first stage each block of indicators is assigned some weights to obtain latent variable estimates by performing iterations of simple and/or multiple regressions (outside approximation). Then the proxies for each latent construct are created based on its relations to other LVs (inside approximation). With the proxy estimates the regressions specified by the structure of the model are 64
performed in order to calculate new weights. For formative indicators the multivariate regression with their latent construct is performed opposed to individual regressions for reflective mode. The regressions’ estimates form a base for new weights to start another outside approximation. The whole procedure stops when next iteration does not produce better estimates according to applied stopping rule meaning that the percentage change in all estimated weights is for example less than 0,001. Therefore PLS iteratively performs estimation of latent variable scores in two ways. One mode is an outside approximation which calculates LVs by weighting their respective indicators. When researcher is operating on a set of observed measures representing unobservable construct without additional information it is advised to start approximation of LV by summation of its indicators. Next part of PLS estimation procedure is an inside approximation that concentrates on calculating LV scores by combining LVs most closely related to the LV in question. The inner weights can be calculated according to three schemes: the centroid scheme, the path weighting scheme and the factor weighting scheme. Assume that Ai and Aj are the estimated standardized latent variables representing real latent constructs Ei and Ej in the outside approximation and wij are the inner weights. The centroid scheme assumes that wij have the same signs as the correlation coefficient between Ai and Aj. The factor weighting scheme calculates inner weights wij as correlation coefficients between Ai and Aj. In the path weighting scheme the latent constructs are divided into predecessors of Ej meaning latent variables explaining Ej and successors of Ej , latent variables explained by Ej . For a predecessor Ei the inner weight wij is the regression coefficient of Ai from the regression of Aj on all Ai’s influencing predecessors of Ej. For a successor Ei the inner weight wij is equal to the correlation coefficient of Ai and Aj. To sum up the estimation procedure PLS operates and uses the information at both levels to estimate the next possible score of LV while maximizing variance explained of all dependent variables. PLS minimizes residual variance for a set of estimated parameters given fixed estimates or proxies for other parameters being estimated. Therefore it is partial in this sense that only part of the model is estimated in each iteration.
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Sample size requirements One important advantage of PLS modeling is small to medium sample size required for estimation. Taking a close look at all three stages of estimation procedure the requirements for sample size appears to be obvious and clear. PLS consists of simple and multiple regressions depending on the specification of latent constructs (formative vs. reflective) and inner relations of the model. As it has been mentioned before PLS is a partial procedure meaning that only part of the model is estimated at one time. Therefore the requirement of sample size for overall model comes down to the requirement for the sample size of the largest multiple regression. Therefore assuming that model consists of formative and reflective indicators the researchers has to find the biggest of the two possibilities: a) the latent phenomenon with the largest number of formative indicators b) the dependent latent construct with the largest number of independent other latent variables influencing it. Assuming well known rule for regression sample size requirements of ten cases for predicted variable the researcher has to make sure that ten times a) or b) cases are gathered (choosing greater value). If the model consists of only reflective indicators the sample size requirement is then limited to condition b). Standardization of manifest variables Lohmöller designed METRIC parameter for standardization of variables. It has 4 variants depending on 3 conditions put on the data: Condition 1: Comparability of the manifest variables’ scales. For example Satisfaction scores measured on the same scale 1-10 are comparable however height and weight are not comparable. Condition 2: Interpretability of the means of the manifest variables. Condition 3: The variances of the manifest variables reflect their importance. If variable scales are not comparable, meaning that condition 1 does not hold (METRIC 1) than standardization of variables is necessary (mean=0 with variance = 1). Standardization is also obligatory if scales are comparable but the other conditions do not hold (METRIC 66
2). In this case after standardization for the estimation phase the manifest variables are then rescaled to the original means and variances. If conditions number 1 and 2 hold but not condition 3 (METRIC 3) than the variables have to be standardized to unit variance but are not centered to the same mean equal to 0 for the estimation phase. After that the variables are rescaled to their original variances. In the last case of METRIC all conditions hold (METRIC 4). In this case the original values of variables are used in the whole process of estimation. 5.2.3. Validation of model In order to evaluate model estimated by PLS method researchers have to apply an approach which is consistent with assumptions of PLS estimation such as no distributional demands and prediction oriented specification. Therefore traditional parametric statistical tests are not appropriate for PLS model validation. Traditional R-square, the Stone Geisser test (Stone, 1974, Geiser, 1975) , average variance extracted measure (AVE) assesses predictiveness while bootstrapping and jackknifing validate the stability of estimates. R-square The R-square can be used as a first indicator of predictive power of specified model. Its interpretation is the same as in traditional regression. The indicator measures how much variance of dependent variable is explained by its predictors. It is possible to calculate R square for latent variables due to their determinacy during PLS estimation. Stone Geisser Q2 The technique is a combination of function fitting and cross-validation. It assumes that prediction of observed measures used in the estimation is of more importance than the artificial constructs’ parameters estimation.
The cornerstone of the methodology is the
blindfolding procedure that estimates parameters without part of the data for a particular set of manifest variables and then uses estimated parameters for estimating the omitted block. Such iteration is repeated until every data point has been withdrew and estimated. Let’s consider a data set and assume that N and K are omission numbers for cases and indicators respectively, and D is an omission distance. Wold (1982) suggests that D 67
should be an integer between K and N. Blindfolding procedure takes out NxK data points starting with first point and omitting every other D data point moving across all columns and rows until the end of matrix. All missing values are then replaced using pairwise deletion, mean replacement or procedure of imputation.
The sum of squares for
prediction error E is calculated and the withdrawn data points are predicted. The sum of squares errors based on the mean for prediction O is also calculated. The whole process is being repeated by returning omitted data points to the matrix and moving to the next data point - case 1 and indicator 2 – as a beginning of new round of withdrawal. During this iterative procedure D sets of Es and Os are calculated. The Stone-Geisser measure is defined as follows: Q2 = 1 – (ΣDED) / (ΣDOD)
(1)
Therefore Q2 represents a measure of how ell the specified model is able to reproduce the observable variables. If Q2 > 0 than the model is predictive and opposite when Q2 < 0. Jackknifing Jackknifing is a procedure that allows researchers to evaluate stability of particular statistic by measuring variability of data set used for calculations instead of using parametric assumptions. The technique provides estimates as well as confidence intervals for the estimates. Contrary to the blindfolding procedure it uses the algorithm of deleting n cases while estimating parameters in each iteration. Finally it examines variation of all obtained estimates. Detailed description of Jackknife procedure is for example described in Chin W.W. (1998). Bootstrapping Bootstrapping is the more advanced methodology. It is also the nonparametric approach that measures the stability of parameter estimates. Jackknifing is usually treated as an approximation to bootstrapping which is in most cases more efficient. Bootstrapping is aimed at obtaining N estimates for every parameter by creating N sample sets. By sampling with replacement from the original data set the N samples are created. The higher the number of resamples the more reasonable standard error estimates can be 68
usually obtained. The default number of bootstrap runs is usually 100, (Tenehaus et. al. 2005) however, the t-values obtained with a bootstrap of 500 runs tend to be quite similar each time the bootstrap is performed. Only rarely does the significance-level of an estimate change in between different bootstrap runs with 500 iterations. The literature also suggests choosing the bootstrap sample size equal to the number of cases in the dataset, because the standard error estimates are dependent upon the number of observations in each replication. Significance is determined against an ordinary t-statistic table, using the number of bootstrap runs as the degrees of freedom (df=500). For a typical one-sided test, the following t-values correspond to a given level of significance (df=500): 3.107 ~ p<0.001 2.334 ~ p<0.010 1.648 ~ p<0.050 1.283 ~ p<0.100 Generally the methodology is more time consuming than the jackknife procedure under the assumption that the number of resamples for bootstrapping is greater. Composite Reliability Composite reliability is a measure of internal consistency applicable only to reflective indicators which has been developed by Werts, Linn and Jöreskog (1974). It is similar in interpretation to Cronbach’s alpha which is usually lower estimate of composite reliability under the assumptions of parameter accuracy. The property is due to the fact that the composite reliability does not assume all indicators to be equally weighted. AVE –Average Variance Extracted Fornell and Larcker (1981) developed another measure applicable only to reflective specification called AVE. It represents the amount of variance that the latent construct in question captures from its manifest, observable variables. It is advised that AVE is greater than 50% meaning that the particular latent construct captures more than 50% of variance of its indicators. It is also suggested that AVE of each LV should be greater than the
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square of correlations between LVs confirming that more variance is shared between chosen LV and its respective manifest variables than with another latent phenomenon. Cross-Loadings Another measure for validating latent constructs and the structure of the model specified by researcher is the test of cross-loadings. It is obtained by calculating correlation coefficients between every set of indicators and every latent construct used in the model. Each block of indicators is expected to load higher on its respective latent component. If the condition is not met than the researcher should reconsider the structure of relationships between the set of manifest variables and latent components. Summary To sum-up PLS avoids serious problems with data distribution and sample size requirements which are crucial in covariance-based approaches. Furthermore its determinate nature allowing for calculation of unobservable components gives PLS the predictive sense and power and avoids parameter identification problems that may occur for covariance-based approaches. Finally PLS does not limit specification of models only to reflective mode allowing for formative specification where weights of indicators are estimated in order to maximize prediction of particular LV. All the arguments and advantages presented above prove PLS as the most suitable method for estimating Customer Satisfaction models such as Brand Satisfaction Model designed for Company X in Poland.
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6. MEASURING CUSTOMER SATISFACTION AT COMPANY X IN POLAND Until the Brand Satisfaction Model based on PLS methodology has been introduced at Company X in Poland as a complete measurement of customer satisfaction and loyalty there have been two unified approaches to exploring satisfaction of its customers. First one, Sales Service Quality CSI concentrates on measuring satisfaction with the sales service quality while the second one – After Sales Service CSI - measures satisfaction with after-sales service. These are two separate researches deeply investigating all aspects connected with the two areas which are the main responsibility of sales companies in different countries. While for example product quality is the sole responsibility of headquarter, the sales and after-sales service constitute the core business of the company locally. Therefore based on the Company X Global Board of Directors’ decision, the two above mentioned studies have been approved as the main measures of sales companies performance in particular markets. The methodology has been unified on every market meaning that research questionnaire is the same in all countries. Thus each sales company in every market is using sales service quality CSI and after-sales service quality CSI researches. Both measures has become extremely important for the whole company and became part of upper-level management bonus system in order to make sure that all respective employees are devoted to achieve the best possible score in both areas. Based on all the information written above it seems there has been no place for additional research investigating customers satisfaction beyond sales and after-sales service. Especially bearing in mind the fact that the CSI has been introduced as a global, obligatory project. However the authors realized that although both existing measurement methods are necessary and important for the organization, they do not allow for creating a local and complete picture of Company X customers’ feelings about the brand with regard to all the areas of their experience with the vehicle. Therefore the authors decided to propose the Brand Satisfaction Model methodology to the Board of Directors in Poland as the unique, complete measurement method for receiving comprehensive picture of Company X customers’ needs, wants and satisfaction. The comprehensive picture means not only investigating satisfaction in other areas of customer experience with vehicle such as: product quality, image, ownership costs etc. but also measuring importance of particular areas in generating satisfaction and loyalty. By introducing the new research the company could gain knowledge of the strength of particular areas influence on
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satisfaction and loyalty and thus would be able to make better sales, marketing and PR decisions. To better understand the advantages of BSM over CSI researches used currently at Company X, it is necessary to familiarize with assumptions and structure of both methodologies. 6.1. Customer Satisfaction Index at Company X – Sales Service Quality The main objective of the research is to deliver better knowledge about customers’ satisfaction with the process of purchase of the vehicle. Core aspects under investigation are: purchase situation process, quality of sales personnel, timing of vehicle delivery, vehicle reception by the customer and general satisfaction with the service provided by the dealer. Over 2 000 questionnaires are being sent to the customers twice a year by mail. The effective rate is around 20-30%. The study covers only those customers who bought the vehicle not earlier than 3 months before the research is actually conducted and at the same time not later than 4 years of vehicle usage. Structure consists of scaled, non-scaled as well as sociodemographic questions. Description of purchasing process, choice factors, willingness of next purchase and recommendation are the non-scaled parameters. Sociodemographic part is standard as in every other study. The most important part of the research is of course the one that measures satisfaction of customers with different elements constituting every-day business for sales companies in different countries. In case of CSI it is the section with scaled questions. It consists of inquires about: -
Satisfaction with overall dealer service o Satisfaction with visit to the dealer o Credibility of the dealer o Honesty and reliability of the dealer o Time spend during vehicle purchase o Ability to agree on vehicle pick-up based on customer needs and schedule
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Showroom atmosphere o Overall satisfaction with the showroom (design and atmosphere) o Completeness of customers’ care (coffee, tea, resting sofas etc.) o Availability of sales materials 72
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Telephone contact o Possibility of receiving trading information through the telephone
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Sales representative o Easiness in dealing with purchase situations o Honesty o Clarity of information given to the customer o Customers’ time respectfulness o Knowledge about product offer o Helpfulness in choosing the right vehicle o Service provided between contract conclusion and vehicle delivery o Frequency of salesman contact o Behaviour of sales representative o Explanation of vehicle or leasing price o Credibility of salesman promises during purchase of the vehicle o Helpfulness of salesman in dealing with formalities.
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Test drives o
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Availability of test drives
Timing of delivery and basic instruction o Satisfaction with timing of delivery o Explanation of warranty conditions o Explanation of after-sales service conditions o Information given on principles of vehicle usage
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Overall condition of the vehicle during receipt o Cleanliness of interior o Cleanliness of exterior
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After purchase contact o Thankfulness expression after purchase o Contact of salesman after purchase and receipt of the vehicle
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Complaints handling o Overall dealing with complaints
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Loyalty o Willingness to recommend the dealer o Willingness to purchase a vehicle at the same dealer o Evaluation of the dealer comparing to other brands’ dealers
6.2. Customer Satisfaction Index at Company X – After - Sales Service Quality The main purpose of the CSI-after-sales research is to measure performance of each aftersales service point in Poland. It concentrates on such areas as customers’ first contact with the reception and services advisor, quality of facility operation and infrastructure, competence of service advisor, transparency of service provided, timing, general vehicle reception process and overall quality of service provided. Over 2 000 questionnaires are being sent to the customers twice a year by mail. The effective rate is around 15-25%. The questionnaires are sent only to those customers who bought the vehicle not earlier than 3 months before the research and at the same time have not used the vehicle longer than 4 years. Below is the description of the areas under investigation: -
Booking in process o Schedule service within reasonable time o Effort to help you maintain normal schedule o Amount of time spent waiting to speak to someone
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Facilities o Convenience of opening days and hours o Convenience of location o Ease of parking o Provision of comfortable waiting area o Overall cleanliness of waiting area o Amenities available
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Service advisor o Provision of advice with regard to service needs o Courtesy and respectfulness of service staff against customers o Honesty of service staff o Display of knowledge and expertise o Attentiveness to your inquiries o Extent to which they clarified your needs o Degree to which they understood problems with your car o Extent to which they kept their promises
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Vehicles reception process o Promptness in having car ready when promised o Explanation of work performed on your car o Explaining charges for work performed o Process of paying for the service o Cleanliness and appearance of car o Amount of time for payment and collection of the vehicle
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Quality of after-sales service o Amount of time spent waiting for service o Ability to diagnose problems o Quality of work performed o Thoroughness in fulfilling your requests o Availability of parts required o Extent to which they stand behind service
6.3. Brand Satisfaction Model at Company X in Poland – history, underpinnings and structure The need for more complete approach to measuring customer satisfaction and loyalty arisen together with the need of product management, marketing and PR departments of Company X in Poland for better knowledge about clients behavior and their way of thinking and making purchasing decisions. So far the two existing CSI studies offered a 75
limited amount of knowledge, which covered two areas: sales service quality and aftersales service quality. Until the Brand Satisfaction Model has been introduced there has been no official representative information on how Polish customers perceive Company X in terms of product quality, image, design, expectations, costs of ownership, comfort and functionality, value/price ratio etc. There was also no measurement of customers’ loyalty against dealers, against brand or their willingness for recommendation. But defining the areas of clients’ feelings about a particular brand is not that complex and is in fact easy to possess. The sales and marketing staff of each automotive company is definitely well experienced to define all the areas which should be investigated and those defined constructs can then be verified by focus groups or individual interviews with customers giving them a chance to add those important elements that are not covered in the research. After such process, researcher can be sure that his study covers all the important elements creating overall picture of customers’ brand perception. However there is also one more and very important aspect of knowledge about your customers. The sole satisfaction scores for all significant areas creating overall satisfaction and loyalty of the end-users have limited power for practical application in real business life unless the importance of all the elements is calculated. Computation of each element’s weight is crucial for creating complete picture of customers’ perception and the way they evaluate the brand performance. If the whole process ensures that (1) satisfaction areas definition is properly conducted internally in the company, (2) then the structure is verified and supplemented by the sample of customers and (3) the importance scores for all attributes are calculated, then it is guaranteed, that the whole approach is complete and offers number of advantages which help better understand the clients. One important aspect is the computation of importance weights. The question arises whether the weights should be calculated by asking customers straight questions about the importance of particular attributes or they should be computed statistically. Many researches proved that the latter one is a better approach as it is resistant to one important disadvantage of the first approach. Usually in case of having customers declare the importance of the areas of their satisfaction the distribution of answers is for most areas strongly negatively skewed meaning that all the elements are equally and very important. Such methodology in most cases creates a picture of equal importance of the elements by 76
limiting the distinction of the ones that are really important and that create the most significant part of customers’ satisfaction and loyalty from those which are not important and can be almost eliminated from the research. By statistical computation the importance weights are more reliable and less biased by human factor. Moreover, statistical computation allows for segmenting the results in satisfaction – importance matrix, as the weight are spread wider as opposed to importance weights declared by respondents. The satisfaction – importance matrix is presented in Figure 6.1.
High
Satisfaction
Figure 6.1. Segmentation of satisfaction with attributes according to their importance.
Potential for savings
Low
Needs improvement
Attribute’s importance
Low
High
Importance
The figure divides all attributes into four groups. Taking into account the importance declaration, all the elements would be almost equally important and as a result all of them would lie close to the middle of Importance axis. Thus the distinction of the real drivers of customers’ satisfaction would not be possible. On the other hand statistical computation of real importance scores of all areas included in the customer satisfaction study by using for example PLS approach offers the researcher practical ability to discover elements that need improvement and those where company can save some money. The most important
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field in the matrix presented in Figure 6.1. is the one with low satisfaction and high importance attributes. This quarter of the matrix is the starting point of every analysis as improvement of the areas which lie in this field has the biggest influence on overall satisfaction score improvement. The field, where company can save some money, is the one containing high satisfaction and low importance attributes meaning that customers evaluation of these areas is too high relative to their importance. In general, for business to be most effective, all measured variables should lie close to the diagonal - with some tolerance which is calculated by confidence intervals. This kind of satisfaction/importance analysis can be conducted for both overall satisfaction and customers’ loyalty. Thus first figure would present all attributes satisfaction scores and their influence (importance) on the overall satisfaction score while the second one would present the influence of these elements on customers’ loyalty. The two steps analysis is crucial for practical interpretation of the results. Although overall customers satisfaction plays an important role in every company strategy it may be useless if it does not create loyal customers. Loyal customers are the source of company’s higher incomes and form the strong and stable base for sales performance. Therefore company with quite satisfied but not loyal customers is definitely exposed for higher risk of loosing business and has to constantly seek for other customers, explore new segments by for example introducing new products which is extremely costly and may be successful only in a short term as the number of market opportunities is usually limited. One important aspect here is the definition of areas of responsibility for a company. Global companies operate with a structure led by headquarter and represented by sales companies or agents in different countries. In case of automotive sector the headquarter is usually responsible for inventing, designing and producing a certain product with very limited influence of sales companies on this process. Therefore such areas as product quality, comfort and functionality of vehicle are not dependent on sales companies’ performance locally in different countries. On the other hand, it is sales company that creates particular level of sales and after-sales service quality for customers in particular country. In this case, the headquarter has very limited influence on what level of service is provided beside producing some guidelines and pushing for their implementation. Therefore some areas lie mainly in the responsibility of the headquarter while sales companies are responsible for the other areas. Thus when conducting importance vs. 78
satisfaction analysis the researcher needs to remember about the aim of the study whether its objective is to analyze and improve total business or local performance of a brand. To sum up Brand Satisfaction Model has been designed in order to create a complete measurement method that would not only explore all the areas of customers satisfaction but would also measure their influence on customers’ satisfaction and loyalty. This kind of approach allows for confirmation and verification of different theories on customer satisfaction in the automotive market by understanding customers perception of Company X brand locally in Poland. It also forms a solid base for making practical recommendations useful for making tactical, operational and strategic decisions in sales, marketing and PR departments. Thus BSM is an universal tool that offers significant amount of knowledge with limited amount of effort. It would have more advantages when applied to most of the automotive producers selling new vehicles in Poland. This would allow for comparisons between satisfaction and loyalty scores between different companies as well as for comparisons of different brands’ customer profiles. 6.3.1. Questionnaire development In order to create a proper questionnaire exploring all areas of customers satisfaction with a brand, a 3 steps approach was applied. First a project group has been set at Company X in Poland. The group consisted of sales representatives from the dealer network and headquarter employees responsible for sales planning, product management, marketing, PR, customer relationship management including Customer Service employees that have frequent telephone contact with clients. The aim and preliminary structure of the research was presented in front of the project group. All the members were asked to give their input into definition of all the areas of clients satisfaction with a brand in order to build a complete measurement tool covering all aspects of the research. All in all, 3 meetings were held and finally the first official structure of the questionnaire was developed. In the second phase the research agency was contacted in order to give its input into development of the tool. The agency was presented the assumptions of the study as well as the questionnaire created during first phase of the research. It combined all its 79
experience in conducting customer satisfaction studies, analyzed the research objectives and suggested some changes in the questionnaire. Therefore the second version of the questionnaire arisen. In the third phase 10 individual interviews with Company X customers were carried out in order to verify the completeness of the questionnaire as well as to make it comprehensible and understandable. In this phase clients were firstly asked to state their definition of satisfaction with an automotive brand and then all the areas from the second version of the questionnaire were verified with respect to their clarity and completeness. Ultimately the third and final version of the research tool has been developed. It consists of questions defined by not only people working in sales and marketing, PR and CRM departments at Company X in Poland but also sales representatives who have day-to-day contact with clients. What is most important, it has been verified by customers with respect to its completeness and clarity. Below is the description of all the elements included in the final version of the questionnaire. It consists of 3 parts. First is the definition of the respondent, second is the main part of the questionnaire that consists of questions defining Brand Satisfaction Model (measured on a scale from 1 to 10 where 1 is the absolutely negative score and 10 is definitely positive score) and the third part is the demographic one. I. Definition of the respondent 1. Gender of a respondent 2. Definition of the concrete model that the respondent is driving (8 models that cover 95% of the total sales volume have been specified) 3. Definition of the type of the engine (petrol/diesel) 4. The date of the vehicle reception after purchase 5. Specification of the dealer where the vehicle was purchased II. Main part of the questionnaire 1. Expectations at the purchase of the vehicle a. Overall expectation of quality 80
b. Expectation of how well the product fits the requirements c. Expectation of reliability/How often things could go wrong 2. Overall Satisfaction a. Overall satisfaction with usage of the vehicle b. Overall satisfaction with the vehicle compared to an ideal vehicle c. Overall satisfaction with the vehicle compared to expectations at the purchase. 3. Image a. Overall satisfaction with image of a brand b. Assurance of safety when driving c. Stable position of a brand on the market d. Technological leadership of a brand e. Brand involvement in customers’ satisfaction improvement f. Brand involvement in social actions g. Brand involvement in promotional events (trades, advertising campaigns, sponsoring etc.) h. Brand involvement in environmental protection i. Brand involvement in making drivers’ lives easier 4. Sales service quality a. Overall satisfaction with sales service quality b. Professionalism of the sales representative c. Kindness and good manners of the sales representative d. Sales rep willingness to inform customer e. Contact renewal after customers visit in the dealership f. Ease of contact with the sales rep g. Atmosphere in the showroom h. Wide product offer i. Availability of additional services (financing, test drives etc.) j. Promptitude of service realization k. Abidance of timing of the service
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5. Quality of the vehicle a. Overall satisfaction with the quality of the vehicle b. Reliability of the vehicle c. Quality of exterior painting d. Quality of interior materials and finishing e. Quality of the upholstery f. Driving quality (driving and steering systems) g. Suspension quality h. Breaking quality 6. Design of the vehicle a. Overall satisfaction with the design of the vehicle b. Exterior design c. Interior design d. Modernity of design e. Uniqueness of design 7. Comfort and functionality of the vehicle a. Overall satisfaction with comfort and functionality b. Seats comfort c. Visibility from driver’s seat d. Functionality of steering elements e. Interior space f. Possibilities of interior space management (folding, removing seats etc.) g. Boot capacity h. Communication systems (radio, navigation etc.) i. Air-conditioning/ventilating systems 8. Costs of ownership a. Overall satisfaction with costs of ownership b. Fuel usage c. Insurance costs d. After-sales service costs e. Repairing costs 82
f. Spare parts exchange costs 9. After-sales service quality a. Overall satisfaction with after-sales service quality b. Professionalism of the after-sales representative c. Sales rep willingness to inform customer d. Atmosphere in the after-sales showroom e. Availability of substitute vehicle f. Availability of spare parts g. Promptitude of service realization h. Abidance of timing of the service 10. Value for money a. Evaluation of the quality with respect to the price of the vehicle b. Evaluation of the price with respect to the quality of the vehicle 11. Loyalty a. Willingness to recommend the brand b. Willingness to recommend the dealer where the vehicle was purchased c. Willingness to purchase a vehicle of the same brand If the answer is negative than the customer is asked to tick out the reasons: i. Bad quality of the vehicle ii. Bad quality of service received at the dealership iii. Design of the vehicle iv. Reliability of the vehicle v. Comfort vi. Too high price of the vehicle vii. Attractiveness of other brands viii. Too high ownership costs ix. The vehicle does not meet the expectations x. Other brands offer same quality vehicles with lower price xi. Other reasons d. Willingness to purchase a vehicle at the same dealership If the answer is negative than the customer is asked to tick out the reasons: 83
i. Poor quality of service ii. Inconvenient location iii. To high prices of after-sales service iv. Incompetent staff v. Poor quality of repairing vi. Negative experience with vehicle delivery vii. Timing/Promptitude of service viii. Poor atmosphere at the dealership ix. Poor availability of additional services such as for example substitute vehicle, financing etc. x. Other reasons III. Demographic questions 1. Age of the respondent 2. Education of the respondent 3. Number of family members living with the respondent 4. Profession/Occupation of the respondent 5. Number of habitants in the city of respondent 6. Voyevodship/Province/County of the respondent 7. Earnings of the respondent
6.3.2. Computer software for Partial Least Squares models The authors of this paper have conducted significant research on all the computer programs that could handle Partial Least Squares calculations and produce necessary output. Unfortunately not many programs support this methodology. Furthermore some programs supporting PLS calculations are not user friendly not allowing for graphical definition and representation of the model. However there are two programs with graphical interfaces helping researchers easily build the structure of relationships for particular study. These are: PLS Graph and Smart PLS. Ultimately the authors have chosen the latter one as the most complete, professional and at the same time easiest and most user friendly tool for performing PLS on BSM. The Smart PLS software has been 84
created by a group of developers sited at the University of Hamburg (Germany) and is so far available as a freeware for all academic users. 6.3.3. Working out the structure of the model The objective of the research was to build an industry specific model of customer satisfaction and loyalty which would completely cover all aspects of brand performance perception. The ACSI and ECSI models are the cornerstones of the structure for Brand Satisfaction Model. However the two models have been developed in order to serve as a universal tool for measuring satisfaction of different industries’ clients. Therefore a certain portion of generality have been applied in both American and European methodology. The Brand Satisfaction Model was designed as an automotive industry specific measurement method with strong attention to details. Thus the BSM had to cover more areas of customer satisfaction as well as some of the areas had to be divided into more detailed ones. The ACSI model consists of Perceived Quality, Perceived Value, Customer Expectations, Customer Satisfaction Index, Customer Complaints and Customer Loyalty scores. The ECSI model adds Image factor and divides Perceived Quality into “software” and “hardware” areas. According to all the research done during preparation of BSM structure and based on Company X employees experience as well as customers’ definition of satisfaction concept, the structure of the study had to be modified versus ACSI and ECSI models. If we take the ECSI methodology as a starting point than in order to create BSM structure the authors added 3 factors: Comfort and Functionality, Vehicle Design and Costs of Ownership. These 3 elements have been defined during first phase of study preparation as important elements of customer satisfaction and are rather specific for automotive industry. Furthermore Perceived quality of “software” and “hardware” has been divided into Product Quality, Sales Service Quality and After-Sales Service Quality. This distinction is justified by the fact that these 3 elements are clearly recognized by customers of passenger cars because in vast amount of cases there are 3 separate units responsible for each of the areas: Producer, After-Sales Service department of the dealership and Sales Service department of the dealer point. Furthermore The Customer complaints area has been replaced/covered by the After-Sales Service Quality factor. All
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these changes modified the ECSI model to make it more automotive industry specific as well as to make it more useful for management of Company X in Poland. Ultimately the structure of relationships between all latent variables had to be also altered and adjusted to the defined structure of Brand Satisfaction Model. This has not been an easy task due to higher number of variables included into specification. First attempt of the authors was to make the structure of relationships as much similar to ECSI as possible. Figure 6.2 presents the first structure of Brand Satisfaction Model with similar relationships as in ECSI methodology. Figure
6.2.
First
version
of
Brand
Satisfaction
Model
based
on
ECSI
methodology.
The latent variables not included in ECSI such as: Comfort and Functionality, Costs of Ownership and Vehicle Design have been connected to Value for Money and Customer Satisfaction Index variables, what was done based on theoretical knowledge and assumptions. However after validation of the model it appeared that the structure had to be significantly altered. Although Cross Loadings and AVE test confirmed proper specification of latent
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variables, the Bootstrapping algorithm (with 346 cases, 500 samples, construct level changes and mean replacement algorithm) which results are presented in Figure 6.3, confirmed that most of relationships are not significant therefore the arrows between such variables should be deleted from the model. Figure 6.3. Results of Bootstrapping algorithm for first version of Brand Satisfaction Model
After this failure the authors decided to apply different algorithm for defining structure relationships for industry specific model called Brand Satisfaction Model. The authors decided to firstly investigate the correlation matrix for all latent variables received from performing PLS on the first version of Brand Satisfaction Model (The matrix is attached in Appendix 1.). Furthermore an expert advisory had to be applied in order to build a model that could be justified by satisfaction theories and practical knowledge. Therefore some arrows were specified in order to confirm some theoretical assumptions of researchers although the correlation score did not necessarily justify the relationship. While creating new structure
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of models that have not been confirmed before by any kind of studies the researchers have to bear in mind that the model has to be proven not only by statistical tests but also by the theory lying behind the study. Therefore after many trials, the authors worked out the final structure of Brand Satisfaction Model which can be justified by model validation techniques and complies with the satisfaction theories as well as practical experience. The complete model is presented below in Figure 6.4. The detailed results of PLS algorithm application are attached in Appendix 3. Figure 6.4. Final structure of Brand Satisfaction Model for Company X in Poland
Figure 6.5 presents results of application of Bootstrapping algorithm to the final specification of BSM. Detailed Bootstrapping algorithm results are attached in Appendix 2. It confirms all relationships in a very significant manner. According to t-values received all path coefficients are significant (df = 500) with a confidence level of at least 99%. Thus this structure can represent a complete picture of how customers of Company X in Poland evaluate its brand performance. As the bootstrapping algorithm proves all the relationship in a very strong manner it would be worth verifying if the model could be also applied to other automotive brands in Poland but this topic would be touched upon in further course of this paper.
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Figure 6.5. Results of Bootstrapping algorithm for final version of Brand Satisfaction Model
6.3.4. Discussion on BSM structure To justify the structure and all the relationships of the Brand Satisfaction Model not only statistical tests or measures such as bootstrapping, AVE, Cronbach’s alpha or Cross Loadings have to prove the model. Beside statistical confirmation the theoretical and practical knowledge also has to stand behind the structure. Therefore the aim of this part of the chapter will be to explain what has already been confirmed by statistics. Some clarification regarding applied modes for latent constructs is needed. Firstly all the latent constructs are created in a reflective way due to the fact that they reflect particular feelings of customers regarding some aspect of their satisfaction i.e. Vehicle quality etc. Secondly the manifest variables in all cases do not completely define and form the latent
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construct to which they are related. Furthermore all latent constructs include one manifest variable that evaluates general satisfaction of customers with a specific latent construct thus forcing somehow the reflective mode. Finally all sets of manifest variables that form each specific construct are usually correlated to each other thus making it impossible for applying formative specification. Let’s move on to analysis of structure of inner relationships. Let’s take a closer look at Comfort and Functionality variable. It is the only latent construct related to the Vehicle Quality meaning that satisfaction of customers with comfort and functionality of driving the vehicle influences their opinion about vehicle quality. It can be reasonably explained because when the vehicle offers good comfort and is functional it creates better opinion about the product itself. When the customer has positively evaluated the vehicle in terms of comfort he/she also has a positive attitude for evaluating quality of a vehicle. The strength of the relationship should be quite strong as both latent constructs reflect practical elements of product evaluation. Moving on to Costs of ownership, this latent construct is related only to after-sales service quality variable as it partly reflects costs of service, spare-parts and repairs. However it does not prove any direct influence on value for money concept. It only has an indirect influence on the construct through the quality of after-sales service. This can be justified by the fact that the Costs of ownership construct does not include any evaluation of price of the vehicle or its quality which are the cornerstones of the Value for money factor. When analyzing Vehicle design concept the only proven relationship binds it to Image variable. This relationship can easily be proven as the exterior and interior outlook, modernity and innovativeness of a design create the image of the brand. If the design is modern and the exterior as well as interior catch the eye of customer, the evaluation of brand image performance should be higher than in the opposite case. Vehicle quality construct shows positive influence on Value for money, Overall Satisfaction and Image. The first two relationships have already been proven by for example ECSI methodology. The positive connection with Image concept confirms the
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theory that reliable, good quality vehicles such as i.e. Toyota have better perceived image than the ones from the lower part of the quality ranking. Image variable influences Value for Money and Expectations factors. The first relationship is also proven by i.e. ECSI model. The connection to expectations can be explained by the fact that the evaluation of brand Image has a positive influence on what customers will expect from the vehicle and the brand itself. If a brand is perceived as being environmental friendly, reliable, safe, involved in customers satisfaction improvement as well as strongly involved in communication campaigns than the customers will expect such attitudes when they decide to buy the vehicle of a particular brand. The expectations on the other hand are connected only to Sales service quality. Unfortunately no relationship between Expectations and Value for money, Vehicle Quality, Overall Satisfaction or Loyalty has been statistically proven. The only path approved by bootstrapping with stable parameter estimate is the path to Sales service quality. The reason for this kind of result is first of all the fact that in ACSI, ECSI and other customer satisfaction models usually the customer expectations have rather low influence on overall satisfaction and loyalty of customers. It seems that in the automotive industry in Poland in case of a premium brand like Company X the expectations have no direct influence on the 3 most important elements of the BSM: Value for Money, Overall Satisfaction and Loyalty. However they have a positive influence on Satisfaction with sales service quality. Such outcome can be explained in a way that when customers have some specific expectations about the brand and they consider buying the vehicle of this brand they first go to the showroom meaning that the first thing they evaluate is the sales service quality. Those customers in such process verify their expectations about the brand by direct contact with a dealer (representing brand) and the product itself (showroom and test drives). After buying a vehicle the expectations have no influence on customers’ evaluation of Perceived Value of the vehicle or their overall satisfaction with the car as customers begin to care more about real attributes of the product and soft elements of the service they receive than about the expectations they had before the purchase of the vehicle. The expectations have an indirect influence on loyalty through the sales service quality variable.
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Sales service quality opposite to perceived quality of “software” in ECSI model does not show any positive influence on Value for money or Overall satisfaction of clients. SSQ is only connected to Loyalty construct. This relationship can be justified as follows. Customers have direct contact with sales service quality usually when they aim to buy a vehicle. While actually using a vehicle they have no contact to sales representatives meaning that it should not influence their evaluation of their satisfaction with vehicle usage. Next contact with sales service is most often when a customer decides whether to buy a vehicle of the same brand at the same dealer or not. If the service received will be positively evaluated than it may also positively influence their decision whether to buy the vehicle of the same brand again. Therefore the above presented reasoning confirms the sole path connecting SSQ and Loyalty. After-sales service quality as the third part of Perceived quality construct in ACSI is related to Value for money factor which is the same as in ECSI and to Loyalty which can be explained similar to relationship between SSQ and Loyalty. If a client is well treated during each and every visit at the workshop than he/she will be more loyal against the dealer as well as the brand itself. The Value for money concept is related only to Overall Customer Satisfaction variable which is related only to Loyalty construct. This structure of relationships is no different to ACSI or ECSI and needs no explanation. 6.3.5. Quality criteria evaluation As discussed earlier the bootstrapping algorithm proved the structure of inner relations between all latent constructs used in the model. The three tables included in Appendix 2: Outer Model T-statistics, Path coefficients T-statistics, Total Effects T-statistics present the results of bootstrapping algorithm application to Brand Satisfaction Model. The results generally confirm inner and outer relations used in the structure applying the rule of tstatistic greater than 2. The are some inner relations (path coefficients and total effects) with t-statistic values between 1 and 2 meaning that the parameter estimate are not quite stable however the relations are proved by underlying theory of customer satisfaction therefore the authors decided to maintain the original structure of BSM. The problem of low t-statistic values exists mainly in bootstrapping algorithm of total effects and applies 92
mainly to indirect relations with usually low parameter estimates. Thus such relationships are rather harmless to the whole structure of the model as they have low influence on the interpretation of the results but on the other hand explain all the theoretical correlations of particular latent constructs. In order to evaluate the appropriateness of specification some other quality criteria described in PLS theory part of the thesis have to be analyzed. All the information on quality criteria is included in Appendix 3. The overview of quality criteria presents values for AVE, communality, composite reliability, Cronbachs Alpha and R square. In general AVE and communality values should be greater than 0,5 as well as greater than the square of correlations between all Latent Variables used in the model (Tenenhaus et al. 2005). Such condition is met with two exceptions of Comfort and Functionality and Image variables where the AVE values are equal to 0,48 and 0,49 respectively. This kind of deviation can be easily omitted as the value is very close to the minimum. In case of composite reliability and Cronbachs Alpha both statistics should be higher than 0,7 (Tenenhaus et al. 2005). All the values for latent constructs used in the Brand Satisfaction Model are greater than 0,84 further confirming the reliability of the outer structure. Analyzing the R-square values the only important variables in terms of predictive power of the model are Overall Satisfaction, Loyalty and Value for money. Other variables for which R-square was calculated serve as the connectors of indirect relations for other latent constructs and are not main elements in terms of predictive properties of the model. Therefore considering the three main variables in question all R-square values are high enough in order to give significant predictive power for the model. In general the minimum value is 0,5 (Rossiter 2002) therefore the Loyalty 0,6 value, the Overall Satisfaction 0,72 value and Value for money 0,69 value offer strong base for further analysis.
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The analysis of cross-loadings confirms the validity of the latent constructs and their respective indicators meaning that the appropriate indicators build up the latent constructs. The general rule is that the indicators should load higher on its respective latent construct and that the values of cross loadings for particular latent construct should be higher than 0,7. This conditions are met in most cases with some minor exceptions when crossloadings values are between 0,55 and 0,7. However this is a small scale problem which can be definitely omitted especially when the number of variables is so high and the number of cross-loadings parameters is equal to 528. Therefore in general the values of cross-loadings prove the outer structure of the model.
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7. RESULTS OF BRAND SATISFACTION MODEL FOR COMPANY X 7.1. Sample description Before any analysis, the detailed check of gathered data was applied. The database was checked for possible outliers as well as with regard to its consistency and possible logical mistakes. After data import to the software programs, the consistency of data with the original base was also investigated in order to assure the highest possible data validity and quality. Sample for the Brand Satisfaction Model study has been carefully selected in order to reflect the structure of Company X customers in Poland. The whole database of all the clients as well as the sales volume segmentation have been analyzed. Based on the analysis the sample of all the customers that purchased a vehicle one to four years before the research was extracted. The number of customers of particular vehicle models reflected the structure of sales volume as well as regionalization of sales with respect to dealerships shares in sales. The factors that have also been taken into account while creating sample database are gender, age group, education, occupation and earnings. From the total number of over 10 000 customers the database including 2 030 clients that meet the assumptions of the research was created. Firstly the mailing with the information about possible individual interview was sent out to all 2 030 customers. Finally the requested number of 346 responses was gathered which gives a reasonable response rate of 17%. The responses were collected through the individual interviews with the clients the method that assures customers about importance of the research by rising its prestige. It also offers lower possibility of collecting not proper responses through eye to eye contact what gives confidence that the appropriate person is responding to the questionnaire. Below are the figures describing the sample data set in detail presenting the main characteristics of the respondent group. The figures prove and are in line with the profile of Company X consumers. Respondents are mainly male according to profile of Company X customers.
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Figure 7.1. Gender of respondents 77% 80% 70% 60% 50% 23%
40% 30% 20% 10% 0% Man
Woman
The model range has been split into three categories: Compact, Mid-Size, Full-size and Large. Under compact category there are customers of two models: Compact vehicle and Compact MPV. Mid-size category is also represented by two vehicles which fall into a Mid-size sedans and Mid-size Specialty Coupes segments of passenger vehicles segmentation. Full-size and Large category is built up of 4 models: Full-size sedan, Largesize sedan, Full-size Off-road and Luxury Specialty Coupes. Figure 7.2. Model range 41% 45% 40% 35%
29%
29%
30% 25% 20% 15% 10% 5% 0% Compact
Mid-size
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Large
Figure 7.3. Engine type
100% 80%
52%
48%
60% 40% 20% 0% diesel
petrol
The shares of fuel types also are in line with actual state of vehicles sold to customers although the trend is strongly changing to diesel engines. Furthermore, the split would be different for different models as for example all sport-type vehicles as coupes or roadsters are sold mainly with petrol engines while at the same time all off-road vehicles are equipped mainly with diesel engines. Compact and limousine type vehicles sedan as well as estate wagons so far have a split of 60% diesel to 40% petrol engines with a moderate trend towards diesel. The figure presenting age of Company X customers in Poland confirms the fact that the majority of clients falls into 40 to 60 years old category. The group of 30 to 39 years old customers is already significant category with high potential for growth due to development of Polish economy which forces the growth of earnings especially for young people. Analyzing education of the customers there are two groups that cover over 90% of the total number. The biggest category consists of clients with higher/university type education. The other significant group is the one with only secondary education (38%). The group consists mainly of company owners that started their businesses and at the same time decided not to continue education. We have to bear in mind that those people
97
attended schools 15-30 years ago when the number of schools offering higher education was significantly lower. This proportion changes at a high pace towards higher education category. Figure 7.4. Age groups
35%
40%
33%
35% 30% 25%
19%
20% 10%
15% 10% 5%
3%
0% 18 to 29
30 to 39
40 to 49
50 to 60
over 60
Figure 7.5. Education
60%
53%
50%
38%
40% 30% 20% 10%
1%
4%
5%
0% preliminary secondary technical
secondary general
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bachelors
masters
Occupation of Company X customers in Poland is dominated by two categories: owners of the companies and upper-level managers what is in line with clients’ profile. There are also 3 interesting categories with equal 5% share in the total sample: Pensioners, Highly qualified specialists and people with free occupation such as for example Artists and Farmers. While the first and the latter groups have rather stable share in the total number of customers the group consisting of highly qualified specialists is the one with extremely high potential for growth which is also connected with economy development and Poland accession to EU which in long term will significantly increase salaries. Figure 7.6. Occupation/Position
70%
64%
60%
50%
40%
30%
20%
14% 5%
5%
Free occupation/Artist/Agriculture
Owner of the company
Manager position
Highly qualified specialist
2% Qualified technical worker
1%
0%
Qualified physical worker
0%
Not qualified physical worker
2%
Buerau clerk
5%
Public clerk
0%
Unemployed
2%
Pensioner
10%
The total income of households doesn’t need any comment as this is clear that biggest group of Company X customers is of course the one that has the highest earnings and the trend will maintain as it is now. Figures 7.8 and 7.9 present the regional split of customers divided into the size of cities and name of voyevodship. Naturally the strongest demand for vehicles from Premium segment is visible in biggest cities. Analysts predict that in a long term there will be negative migration to the largest agglomerations which means that more and more
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wealthy people will move to smaller cities. Thus a higher share of customers living in cities with 50 to 200 thousands inhabitants shall be observed in future. Figure 7.7. Total household income (in PLN) 78% 80% 70% 60% 50% 40% 30% 20%
7%
4%
4%
10%
7%
0% below 4000
4000 - 6000
6000 - 8000 8000 - 10 000 over 10 000
Figure 7.8. Size of the city (in thousands of inhabitants)
49% 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0%
23%
9%
village
8%
10%
city up to 10city 10 to 50 city 50 to city over 200 200
100
There are 5 strongest sales regions in Poland when it comes to analysis of customers divided into voyevodships. The biggest voyevodship regarding sales of new vehicles is Mazowieckie with its capital – Warsaw. The second biggest region is Slaskie (Katowice) and Dolnoslaskie (Wroclaw) on the south of Poland which, when summed together, have the same share as Mazowieckie (23%). Moving to northern part of Poland there are three significant
regions
with
high
demand
potential:
Wielkopolskie
(Poznan),
Zachodnipomorskie (Szczecin) and Pomorskie (Gdansk) with 8%, 8% and 6% share respectively. Figure 7.9. Region/Voyevodships
25%
23%
20% 15%
15%
6%
Zachodniopomorskie
1% Wielkopolskie
Slaskie
2%
Warminskie
3%
Pomorskie
Podkarpackie
Opolskie
1% Mazowieckie
Malopolskie
3%
Podlaskie
4%
Swietokrzyskie
6%
Lodzkie
Lubelskie
Dolnoslaskie
3% 2%
5%
Lubuskie
5% 0%
8% 8%
8%
Kujawskie
10%
7.2. Estimation results for Brand Satisfaction Model – Total Brand The parameter estimates for inner model as well as R square values for all dependent variables are presented in Figure 7.10. To actually analyze the strength of impact of particular constructs on Satisfaction and Loyalty measures the total effects were calculated and are presented in Figure 7.11.
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Figure 7.10. Results of PLS algorithm application on final version of BSM.
Looking at differences of importance of particular latent constructs regarding satisfaction and loyalty it is obvious that satisfaction does not always mean loyalty. Even if the customer is satisfied he/she does not have to purchase or recommend a vehicle of the same brand until certain conditions are met. There are 2 elements Vehicle Quality and Comfort and Functionality that generate 75% of customers satisfaction while at the same time creating only 31% of customers loyalty. This example shows how different are both concepts and that company sole orientation on satisfying its customers is not enough to be successful. In order to make customers loyal an automotive company has to take care of many areas that altogether have strong influence on loyalty. Beside Vehicle Quality and Comfort and Functionality it is Overall Satisfaction, Sales Service Quality and After Sales Service quality that all together generate 79% of customers loyalty. The moderate influence on Loyalty (6% each) have cost/price variables: Costs of ownership and Value for money. Expectations, Image of a brand as well as Vehicle Design present rather low influence on both customers satisfaction and loyalty. The comparison of importance scores for each latent construct with regard to its influence on satisfaction and loyalty clears out the direction into which the strategy of Company X in Poland should be heading. To have satisfied and loyal customers, the headquarter of Company X has to produce good quality products that offer proper driving comfort and are functional, while 102
at the same time the sales company in Poland needs to take care mainly of the quality of sales service and after sales service. The sales company can not forget and disregard price positioning of the vehicles with respect to the value they represent in comparison to competition. The level of costs of vehicle ownership is also quite important and needs to be monitored and eventually adjusted to those offered by competitors. This general implications for the total brand might be different if applied to the 3 model groups Compact vehicles, Mid-size sedans and coupes
and Full-size and Large premium
vehicles. The possible differences will be investigated in further analysis. Figure 7.11. Comparison of relative Total Effects on Overall Satisfaction and Loyalty.
50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0%
43% 32% 21%
6%
ua l it y
n V
eh ic le Q
es ig
ey
eh ic le D
alu e V
V
ua l it y ce Q
Se rv i
Sa ti s f
ac ti o
Im ag ve ra ll
Overall satisfaction
18% 1% 1%
0% fo rm on
0% n
e
3% 3%
O
s ec ta tio n
p rsh i ow ne of
Ex p
fo rt Co m Co s ts
ua lit y
5% 0%
Sa le s
6% 1%
3%
al es q fte r-s A
16%
14%
13%
13%
Loyalty
In order to discover the areas where improvement is absolutely necessary, the importance versus satisfaction analysis has to be conducted. Table 1. presents the latent variable scores received from Brand Satisfaction model estimation by PLS procedure. In general for the total brand the score of 78% in overall satisfaction and 83% in loyalty was received. It is difficult to set the minimum value for both indices as there is no direct comparison to previous studies. However comparing BSM to CSI scores and in order to force some improvement of satisfaction and loyalty the authors decided that the minimum
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score for all investigated areas is 85%. Therefore all variables that rank below 85% should be deeply investigated for improvement plan. Table 1. Latent constructs’ scores (rescaled to 0-100).
Latent Variable Expectations Vehicle Design Sales Service Quality Comfort Vehicle quality Loyalty Image Overall satisfaction After-sales quality Value for money Costs of ownership
Score 93% 91% 89% 87% 86% 83% 82% 78% 75% 75% 68%
The highest two scores were noted for the two area, which have very low influence on customers’ satisfaction and loyalty: expectations at the time of purchase and design of the vehicle, which scored 93% and 91% respectively. Two highest scores are followed by 3 very important areas for company’s overall performance which are: Sales Service Quality (89%), Comfort and Functionality (87%) and Vehicle Quality (86%). These 3 constructs have the strongest influence on customer satisfaction and as they received scores above 86%, there is no negative signal for improvement within those 3 areas. Below the minimum score there are 4 quite important areas: Image 82%, After-Sales service quality 75%, Value for Money 75%, Costs of ownership 68%. The company definitely needs to concentrate on these areas in order to improve the overall satisfaction and loyalty of customers. In order to discover what needs to be done to improve evaluation of Company X, the analysis needs to be divided into two approaches. One would be headquarters’ while the other one would be local sales companies’ responsibilities. Such distinction is necessary as headquarter and sales companies are responsible for a bit different areas included in the study. The headquarter is designing and inventing vehicles meaning that it is solely responsible for the vehicle quality, design and the comfort and functionality they provide. At the same time sales companies have very limited influence on the product characteristics - what vehicles are being produced and what quality they provide. On the 104
other hand it is sales company in every country that is responsible for sales and after-sales service quality, costs of ownership. Furthermore, local sales companies in a large part create image of a brand, as well as they offer certain value for money to the consumer by applying certain pricing strategy. As the BSM is conducted on sales company level, the authors decided to split the analysis into: 1. presentation of all results for satisfaction and importance on one Figure 7.12 as an overall picture of Company X performance and importance of particular areas 2. the presentation of only those areas that are under strict or indirect supervision of sales companies as an analysis of local performance – Figure 7.13. Figure 7.12. Satisfaction scores vs. satisfaction importance analysis – overall
95% Satisfaction Score
90%
Vehicle design
85%
Comfort/Functionality
Image
Vehicle quality
80% After-Sales Quality
75%
Value for money
70%
Costs of ownership
65% 60% 0%
10%
20%
30%
40%
50%
Satisfaction Importance
Referring to the figure 7.12, the red line draws the minimum value score for all the areas. Therefore all the areas below this line should be pushed up in order to improve the overall satisfaction score. Looking at the figure it is obvious that among all constructs below the red line the highest influence on satisfaction is given by Value for money (16%) variable and than by After-Sales quality (3%) and Image (3%). Moving on to local sales company performance the spectrum of areas in question is smaller. There are 5 areas, on which performance sales company has some kind of influence. Among them only Sales Service quality is above the red line with unfortunately
105
no influence on customers overall satisfaction. Therefore there are 4 remaining areas which need improvement: Value for money, After Sales service quality, Image and Costs of ownership. They all have different priorities: 69%, 13%, 12% and 6% respectively. However as the responsibility of local sales company, they should all be taken care of. Figure 7.13. Satisfaction scores vs. satisfaction importance analysis – sales company
95%
Satisfaction Score
90%
Sales service quality
85% Image
80% 75%
After-Sales Quality Value for money
70%
Costs of ownership
65% 60% 0%
10%
20%
30%
40%
50%
60%
70%
80%
Satisfaction Importance
In order to discover detailed areas for improvement the importance versus satisfaction analysis have to be performed for each construct on a manifest variables level. Before this detailed approach is implemented, Loyalty concept and the areas that have the highest influence on Loyalty shall be explored. Here the two steps approach have also been applied – overall and sales company specific. As can be seen in Figure 7.14 there are repeating areas such as After-Sales Service Quality, Costs of Ownership, Value for Money and Image that lower the overall loyalty of Company X clients and therefore need improvement. Furthermore the Overall Satisfaction score is also not satisfying enough and has to be improved. If the above mentioned factors are improved, the overall satisfaction score will increase as well, as there are links between the satisfaction and the mentioned areas.
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Figure 7.14. Satisfaction scores vs. loyalty importance analysis - overall
95%
Expectations Sales service quality
Satisfaction Score
90%
Vehicle design
Comfort and functionality
Vehicle quality
85% 80%
Image Value for money
75%
Overall Satisfaction After-Sales Quality
70% Costs of ownership
65% 60% 0%
5%
10%
15%
20%
25%
Loyalty Importance
Figure 7.15. Satisfaction scores vs. loyalty importance analysis – sales company
95% Sales service quality
Satisfaction Score
90% 85% Image
80%
After-Sales Quality
75%
Value for money
70% Costs of ownership
65% 60% 0%
5%
10%
15%
20%
25%
Loyalty Importance
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30%
35%
40%
Moving on to Figure 7.15, local sales company performance on factors that have influence on Company X customers’ loyalty can be analyzed. Again it is After Sales service Quality, Value for Money, Costs of Ownership and Image Variables that negatively influence the level of clients’ loyalty. The only positive sign here is the performance of sales service at dealerships. It definitely pushes the loyalty score above average. After the general analysis of different areas performance and their influence on overall satisfaction and loyalty of Company X customers in Poland, detailed satisfaction vs. importance analysis of areas that need improvement shall be conducted. However there is a strong argument to stop here and make the summary of general analysis. The Brand Satisfaction Model has been designed as a tool for measuring and improving Company X customers’ satisfaction and loyalty in order to create better image of the brand, increase brand sales and its general position on Polish automotive market. Therefore BSM includes areas that are under strict supervision of company’s headquarter, on which sales companies have very poor influence such as vehicle quality, comfort and functionality of the vehicle as well as its design. BSM includes also areas which are either sole responsibility of sales companies or which performance can be improved by local sales companies. Within those areas there is Sales service quality, After-Sales service quality, Value for Money of the vehicle in terms of its pricing strategy, Costs of vehicle ownership and Image of a Brand. Although all the areas have very different weight in terms of generating higher overall satisfaction or loyalty of Company X customers, they should all be taken care of if their score is not satisfactory enough (below 85%). The priorities should be definitely accepted and respected but unless it doesn’t require too much effort from the sales company, all the negatively scoring areas should be analyzed, monitored and improved. Such methodology is not fully consistent with satisfaction vs. importance analysis however due to responsibility split between headquarter and sales company, it is much easier and effective to take care of more areas than the satisfaction vs. importance analysis would suggest. 7.3. Estimation results – Total brand - detailed analysis of performance Having in hand all the areas that need a reparation program, which were discovered in the general analysis of latent constructs performance and importance, the detailed analysis of 108
those areas can be implemented. The performance of headquarter in terms of providing good quality products which offer good design, are comfortable and functional in use is generally well enough. This means that these areas do not need any reparation program but definitely have to be monitored in order to assure at least the same level of customers satisfaction with those areas. What definitely has to be implemented is the program for Company X Polish customers in terms of their satisfaction with work of sales company as well as dealerships representing the brand in Poland. Four areas have been recognized as those that need improvement and the vast amount of responsibility for customers satisfaction with these areas lies in hands of sales company employees as well as the dealer network. The analysis of performance of manifest variables that create After Sales Service Quality, Value for Money, Costs of Ownership and Image will be now presented. The loyalty of customers creates higher value for the company than satisfaction, therefore the analysis will be conducted according to the strength of areas influence on customers’ loyalty (After Sales service quality 30%, Value for Money 15%, Costs of ownership 15%, Image 7% – relative local influence). Taking into consideration the after sales service quality, Company X customers evaluated all factors creating the overall perception of after sales service below 79% - as presented in the Figure 7.16. This creates a significant room for improvement in this area meaning that satisfaction with all elements creating perception of service during customers visits in the workshop is not satisfactory and significantly decreases customers satisfaction and loyalty. All manifest variables generating after sales service latent construct have an importance level of between 9 and 14%. The least significant element according to the research is the availability of substitute car when customer’s vehicle is being serviced. At the same time it has very negative evaluation. The recommendation is that Company X does not have to necessarily take care of this part of post purchase service as its influence on overall satisfaction with after sales service is at the bottom of the list. Than in the middle of importance scale we have availability of spare parts with a bit higher evaluation than in case of substitute car. The logistics issue in terms of proper stock
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management in the logistics center as well as faster delivery of required spare parts should be monitored but not considered as one of the most important factors. The most important elements of service that should definitely be improved as they have the highest influence on customers satisfaction and loyalty and at the same time do not meet customers requirements and expectations are: willingness to properly inform customer about required service, professionalism of after-sales representative, promptitude and timing abidance of service, overall service quality and after-sales service reception atmosphere. It seems that soft skills training for after sales representatives having direct contact with customers is needed. The reps should be trained in order to know what kind of attitude they shall represent in front of the customer meaning that they should serve as a credible source of information. When having contact with customer the rep should concentrate on providing as much information as necessary to make sure that the client knows what needs to be done with his vehicle, how long it will last and how much it shall cost. Furthermore the after sales representatives should be trained with respect to their professional knowledge about technical issues in order to behave professionally when serving a customer. The next important factor strongly affecting customers satisfaction and loyalty is the promptitude of service in terms of quickness of service. This negative evaluation can be connected to shorts of staff in particular after sales service workshops which cause longer waiting lines or to the availability of spare parts which has been negatively evaluated by customers. The whole service logistics process needs to be investigated and parts of the process which extend the service time have to be either eliminated or accelerated. Timing abidance is also a significant element in terms of its influence on satisfaction with after sales service. This can be partly connected to the promptitude of service but in a large part it is the pressure of customers who during the time when vehicle is in the service, do not want to wait too long time and force the after sales rep to declare the earlier vehicle pick up time. In some cases shorts of service staff can also cause the negative evaluation of this area. To summarize, improvement of promptitude of service factor requires that employee count is evaluated and discussed with the staff, but also soft
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skills training could also be valuable in order to train after sales reps to be assertive and to communicate rather longer than shorter service deadlines. The atmosphere in the workshop reception room needs improvement too as it is one of the most important elements of customers service. The client has to feel as someone special and needs to be treated well. Furthermore if customers like the atmosphere of the workshop reception it improves their evaluation of the image of the brand meaning that they feel as someone unique while using the vehicle of the brand. The overall service quality was evaluated negatively meaning that the quality of service provided needs to be improved as customers are definitely not satisfied with what is being done with their vehicles and how well they are served. Figure 7.16. Satisfaction scores vs. loyalty importance – after sales service quality 79 Atmosphere
78
Satisfaction score
77
Timing abidance Willingness to inform Professionalism of rep
76 75
Availability of spare parts
74
Promptitude of service
73
Overall service quality
72 71 70
Availability of substitute car
69 68 9%
10%
11%
12%
13%
14%
Loyalty importance
The value for money construct (figure 7.17) is built out of two elements: price and quality received. As vehicle quality is a separated from value for money latent construct in the analysis therefore value for money factor can be simplified to the pricing strategy of Company X in Poland with respect to the quality of vehicle and service provided. The area was evaluated close to 75% which is definitely too low score and it needs to be improved. It is difficult to judge whether the prices of vehicles should be drastically decreased. However the pricing list modification is required in order to make the price
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positioning against main competitors more acceptable for Company X customers. Probably customers do not see such a big difference between Company X and other brands in terms of vehicle quality, sales and after sales service, comfort and functionality of the vehicles etc. but they see the difference in price positioning. Improvement of this element could definitely increase customers satisfaction and loyalty against the brand. However the sales company has to be careful at the same time as price is also the antecedent of value of the vehicle provided that it offers proper quality and comfort of usage. Therefore too low pricing can deteriorate value of a brand in eyes of its clients.
Figure 7.17. Satisfaction scores vs. loyalty importance – Value for money
76 75
Vehicle quality with respect to its price
Satisfaction Score
75 74
Price of the vehicle with respect to its quality
74 73 73 72 72 71 49,0%
50,0%
51,0%
Loyalty Importance
Analyzing evaluation of costs of ownership (figure 7.18) it seems that the lowest score is given in the areas of after-sales service responsibility and costs of vehicle insurance. Insurance is the least important factor among the others however the difference in the importance levels is not that big to definitely ignore this element. Insurance can serve as first of all attractive sales incentive for customers as well as advertising keyword to attract customers to the showrooms.
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Coming back to satisfaction with costs of after sales service it seems like Company X in Poland has quite a problem with general perception of workshop service. It is not only expensive but at the same time not satisfactory enough. Again the pricing strategy needs to be revised in order to make brands of Company X more competitive and maybe some promotional events decreasing costs of Company X vehicle usage such as free service for winter and summer holidays could also be introduced. Figure 7.18. Satisfaction scores vs. loyalty importance – Costs of ownership
80 78
Costs of fuel
Satisfaction Score
76
Overall costs of vehicle usage
74 72 70 68
Costs of regular service
66 64
Costs of repairs
Costs of insurance
Costs of spare parts
62 60 13%
14%
15%
16%
17%
18%
19%
Loyalty Importance
Costs of fuel are not that important comparing to the costs of after sales service however some inexpensive improvement in this area could also be implemented. Fuel card with a limit of e.g. 3% of a price of the vehicle given with each car sold may be a good mean for improving customers satisfaction with costs of ownership. Next idea is to offer a fully tanked vehicle after each visit to a workshop which costs exceeds e.g. 100 PLN. Image of a brand (figure 7.19) is also in large portion a responsibility of sales company locally in particular country. In this case Company X in Poland should definitely increase its involvement in customers’ satisfaction improvement by e.g. allowing customers to
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express their opinion about the quality that they receive. The researches such as Brand Satisfaction Model give the possibility for each customer to speak up and evaluate the brand in terms of soft service and vehicle quality and comfort that they receive. It gives the strong feeling to the customers that the brand takes care about them and wants to listen to their opinions in order to improve its performance and at the same time its clients satisfaction. Figure 7.19. Satisfaction scores vs. loyalty importance – Image
93 Safety assurance
Satisfaction Score
88
Stable market position of a brand
83
Technological leadership Environmental care
Overall image
78 73
Making drivers' lives easier Brand involvement in improvement of customers satisfaction
Promotional Visibility (motorshows, sponsoring, advertising) Involvement in social actions
68 8,5%
9,5%
10,5%
11,5%
12,5%
13,5%
Loyalty Importance
Technological leadership is on the edge of 85% bottom line. Such position can be a result of the fact that either the competition is quite close to Company X in terms of technological advancements or Company X customers are not aware of its brand advantage over competitors. The best solution here is surely better communication of all most important advantages of Company X vehicles in terms of modern technology used in them. The area called “making drivers’ lives easier” also has to be improved and it may be definitely connected with the above mentioned factor which is technological advantage over its main competitors.
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Factors that increase customers evaluation of a brand with regard to its image are: safety assurance and its stable market position. This areas improve overall score meaning that Company X vehicles are definitely safe in the eyes of clients, the position of a brand is very stable on the market and is not deteriorating. The elements that are of lower importance are environmental care, company’s involvement in social actions and promotional visibility of a brand in terms of its presence on motor shows, in advertising campaigns and sponsoring. As the difference in importance levels is not that significant these above mentioned areas could also be improved in order to increase the score of overall image perception especially having in mind that they are some basic factors of company’s presence on particular market.
7.4. Estimation results for Brand Satisfaction Model – 3 segments of customers The analysis presented in previous chapter is applied to total brand, meaning Company X customers in general. However there are different groups of customers with different profiles depending on what vehicle they buy. Different customers have various demographic characteristics and needs which impact their requirements towards vehicles they drive.
Therefore the authors decided to perform 3 separate analysis based on
different customer groups: Compact vehicles owners, Mid-size vehicles owners and FullSize and Large vehicles owners. The aim of the study is to discover main differences between customer groups which have different requirements for the vehicle they drive as well as different demographic characteristics and the amount of income they want to spend on vehicle. 7.4.1. General estimation results for 3 customer segments The parameter estimates for inner model as well as R square values for all dependent variables are presented in Figure 7.20, 7.21 and 7.22 for three model groups respectively. We can see quite different parameter estimates for three vehicles groups. In order to analyze differences between the customer segments we should firstly take a look at the comparison of satisfaction scores presented in Table 1. 115
Table 1. Latent constructs’ scores for 3 model groups (rescaled to 0-100). Expectations
92%
92%
Full-size and Large 95%
Vehicle Design
89%
90%
92%
Sales quality
88%
89%
88%
Comfort
86%
86%
88%
Vehicle quality
85%
88%
85%
Loyalty
83%
86%
81%
Image
82%
83%
82%
Overall satisfaction
77%
81%
77%
After-sales quality
75%
78%
74%
Value for money
74%
77%
73%
Costs of ownership
67%
67%
70%
Variable
Compact
Mid-size
Generally, with minor exceptions, the overall evaluation of particular latent areas is similar concerning the hierarchy of scores meaning that the highest scores for all customer groups are given to expectations and vehicle design and than to sales service quality, comfort and functionality, vehicle quality followed by loyalty, image, overall satisfaction, after sales service quality, value for money and costs of ownership. Figure 7.20. Results of PLS algorithm application on BSM – Compact vehicles.
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Figure 7.21. Results of PLS algorithm application on BSM – Mid-size vehicles.
Figure 7.22. Results of PLS algorithm application on BSM – Full-size and Large vehicles.
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However looking at the Table 1 in more detail, significant differences between evaluation of particular latent constructs are discovered. First of all some trends are visible if we compare scores of one variable for all model groups. Rising expectations moving towards Full-size and Large vehicles customer group are observed what is understandable having in mind the fact that these clients are wealthiest segment and spend more money on their vehicles at the same time expecting more from quality and service they will receive. Secondly, the evaluation of vehicle design is also rising moving from Compact to Large vehicles group. This also does not require very deep investigation as simply the vehicle design of more expensive, more luxurious vehicles catches the eyes of most customers. Finally, similar relationship can be found for all model groups regarding comfort and functionality of the cars. Larger vehicles are usually more comfortable, better equipped and because they are usually more expensive they use modern technology what increases their functionality. In case of costs of ownership the wealthier the customer segment, the higher the satisfaction with costs of vehicle usage what is natural and does not require any comment. Two variables have almost constant satisfaction scores for all groups of customers. Image scores between 82 and 83 while sales service quality is evaluated at the level of 88 to 89% which positions this area at the top of the list. Regarding the sales service quality it can be argued as natural state however in real life its sometimes difficult to train the sales staff in order to maintain the same and high level of service provided for all customer groups. In case of Company X this is really a success that the sales staff does not prioritize the customers who are wealthier and able to spend more money which in the end reach pockets of sales representatives. The more expensive the vehicle the more money goes to the person that sold it to the customer. Naturally sales staff would like to earn more money thus providing better service for those customers who are wiling to buy more expensive vehicle. Therefore it is a big value of Company X dealer network responsible for sales service quality which offers high and at the same time similar level of service no matter how wealthy the customer is. Analyzing other variables we can also see a strong trend although it does not depend on the size and price of the vehicle. For vehicle quality, after-sales service quality, value for money and overall satisfaction as well as loyalty, one group stands out of the crowd. It is a group of mid-size vehicles customers that on average in all the above mentioned areas 118
scores better than other model groups. This means that these vehicles offer higher quality in terms of dependability, driving quality etc. therefore creating higher value for money for mid-size vehicles owners. Surprising is the fact that the after sales service quality received by this group of customers is also higher than for compact cars and large vehicles owners. Maybe the number of visits to the workshop was lower for the group which could go in line with higher vehicle quality evaluation meaning that mid-size vehicles customers were not able to receive so much not satisfactory service from after-sales service department. Because the score on vehicle quality, value for money and after sales service quality is higher than in other groups the overall satisfaction as well as loyalty of mid-size vehicles owners scores also above other model groups. 7.4.2. Total effects analysis – 3 customer segments Let’s compare the strength of influence of all latent constructs on satisfaction and loyalty between all customer groups included in the study. Figure 7.23 presents the influence of every latent variable on overall satisfaction scores divided into customer segments. It can be observed that in terms of overall satisfaction generation the customers are quite unanimous. There are 3 exceptions from the rule. First of all image of a brand is much more important for compact vehicles users than for midsize or full-size cars owners, what is in line with customer profile research results. It seems that customers that buy the least expensive vehicle in Company X portfolio very much appreciate the image that the brand acquired during its presence on the market. On the other hand brand image is of little importance for premium customers who buy expensive vehicles. For these customers the other factors count when it comes to creation of their overall satisfaction. They are satisfied not due to brand image, but because the vehicle offers high quality and comfort that also generates higher perceived value. If value for money factor is analyzed, it can be observed that it is of highest importance for compact vehicles users and the lowest important for mid-size cars users. Generally customers who buy compact vehicles of Company X brand expect decent value for money that they have to pay. This is understandable as, referring to the results of customer profile study, clients with lowest income are more price sensitive and they require more for what they pay. On the other hand, value for money factor is of lowest importance for 119
satisfaction of owners of mid-size cars, while it is more important for full size and large cars owners. Mid-size vehicles clients break out of the pattern probably because their evaluation of vehicle quality is better than in case of other clients. That is why the value for money factor is not as important for mid size cars owners as for other customer segments, because they perceive quality as more important driver of their satisfaction than other customer segments do. Figure 7.23. Influence of latent constructs on overall satisfaction – comparison between different customers’ groups
60% 50% 40% 30% 20% 10%
sa tis fa ct io n Sa le sq ua V lit alu y ef or m on Ve ey hi cl eD es ig V n eh ic le qu ali ty
Lo ya lty
Im ag e
ati on s
ip
pe ct
ra ll
Ex
ne rs h
t ow
of
Co m fo r
O
ve
Co sts
Af te r-s
ale sq
ua lit
y
0%
Compact
Mid-size
Full-size and Large
Moving to vehicle quality, comfort and functionality it seems that customers that pay more for their vehicles require higher dependability and quality as well as comfort of the car they drive. The importance of this latent constructs is almost equal for mid-size, fullsize and large vehicles clients (46-49% - vehicle quality, 35% comfort and functionality) while compact cars users pay less attention to both factors (36% and 30% respectively). This may be easily explained by the fact that wealthier customers expect higher values in their products
what means that they have to be of good quality and offer decent
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functionality as well as comfort of driving. On the other hand compact vehicles users pay more attention to the value for money that is offered by their products as well as image of the brand. Due to premium character of a brand the “compact” customers pay more for the Company X vehicles comparing to direct competition thus expecting higher perceived value and proper image of the brand they represent. . Let’s now move on to analysis of different satisfaction areas influence on customers loyalty. Taking a closer look at Figure 7.24 it seems that loyalty construct is definitely much more complicated than satisfaction and requires deeper insight. Among all factors, only vehicle design and overall satisfaction are the areas which have similar importance level for all customer groups. Analyzing the importance of after sales service quality we discover that the more customers pay for their vehicles the less they require from after sales service in order to become loyal to the brand and dealer. For ”mid-size”, “full-size” and “large” clients there are 2 other factors that they pay special attention too – vehicle quality and comfort and functionality. Costs of vehicle ownership and usage are of course more important for “compact” customers than for “mid-size” clients and the least important for those clients who pay the most for their cars. This can be easily explained by different income levels for the 3 analyzed clients’ groups, what was also observed in customer profile research. Moving to expectations it seems obvious that higher segments clients demand more from the vehicle and the brand what was confirmed by the Brand Satisfaction Model study. The importance of Image against Loyalty goes in line with Image importance against Overall Satisfaction and can be explained in the same manner. There is a big gap between strength of influence of sales service quality on customers loyalty between customers of compact vehicles and the rest. “Mid-size”, “full-size” and “large” customers demand much more from sales service quality and position this factor as the second important for their loyalty towards a brand. At the same time compact cars users diminish the importance of this factor placing it behind vehicle quality, comfort and functionality, after-sales service quality and value for money. This discrepancy gives the marketers quite important message that the “mid-size” and “full-size and large” customers
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need to receive extraordinary sales service in order to make them loyal to the Company X brand. Figure 7.24. Influence of latent constructs on loyalty – comparison between different customers’ groups
25%
20%
15%
10%
5%
y
eh i
cl e
qu ali t
D es ig n V
ey
ic le
m on V eh
ity
O
V al
ue fo r
qu al
tio n
Sa le s
lty
at isf ac
ve ra ll s
Lo ya
Im ag e
ec t
at io ns
hi p Ex p
ne rs ow
of
Co m fo rt Co s ts
A f te r-s
al es q
ua l
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0%
Compact
Mid-size
Full-size and Large
Finishing the loyalty importance analysis it is discovered that value for money is definitely of highest importance for “compact” clients but at the same time it is the least important for “mid-size” customers. Clients of higher segments place the importance of this element somewhere in between the scores for two other groups. Again the lowest importance of this area for mid-size vehicle users can be explained by the highest quality level of vehicles they drive comparing to the rest of model groups. To sum up we discovered definitely different profiles of the three analyzed groups of clients. They differ not so much in terms of their definition of overall satisfaction however differences with regard to loyalty generation are significant in many aspects of customers satisfaction. We can in some part merge the mid-size, full-size and large vehicles’ clients but the “compact” customers differ a lot from the others. While “compact” clients are
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more price sensitive and pay a lot of attention to value for money of their vehicle as well as to the after-sales service quality they receive in the workshop, the remaining two customer segments require more from vehicle quality and especially from sales service quality. These findings are in line with customer profile research which revealed, than compact car customers are more price sensitive and more often than other customer segments search for vehicles, which are functional and economical. 7.4.3. Satisfaction vs. importance analysis - 3 clients segments - inner model Let’s analyze differences between the 3 model groups on a satisfaction vs. importance analysis figures. As discussed earlier we discovered 4 areas that definitely need improvement with regard to total brand. It will be good to know whether the same rule applies to all customers or there are some differences in approach to increase satisfaction and loyalty of customers. There might be either one strategy which could be applied to all customers segments or more strategies may arise in order to better serve needs of customers who, depending on the segment, may have different requirements against the brand performance. This part of analysis will help understand the differences between customers of Company X in Poland not only through comparison of the scores of satisfaction for specified areas but also by discovering different priorities lists for all the elements included in the study. The graphical representation of satisfaction versus importance analysis will not include the division of matrix into important and not important areas due to the fact that not all of the areas are under direct supervision of neither the headquarter nor sales company. Therefore further analysis will have to be adjusted to either sales company or headquarter perspective. The authors concentrate on performance of sales company thus such analysis should include only those factors that are directly controlled by Company X in Poland. Figures 7.25 to 7.30 present satisfaction scores for all latent variables versus their influence on either satisfaction or loyalty and are divided into 3 customers segments: Compact , Mid-size and Full-size and large vehicles owners. The analysis will allow for distinguishing important areas creating satisfaction and loyalty of customers in 3 segments.
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Figure 7.25. Satisfaction scores vs. satisfaction importance analysis – Compact vehicles
100% 95% Expectations
Satisfaction Score
90%
Vehicle design
Comfort and functionality
Sales service quality
85%
Vehicle quality
Image
80% 75%
After sales service quality
Value for money
70% Costs of ownership
65% 60% 0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Satisfaction Importance
Figure 7.26. Satisfaction scores vs. loyalty importance analysis – Compact vehicles
100% 95% Expectations
90%
Vehicle design
Sales service quality
Satisfaction Score
Comfort and functionality
85%
Vehicle quality
Image
80%
Overall satisfaction
75%
Value for money
70%
After sales service quality
Costs of ownership
65% 60% 0%
5%
10%
15%
Loyalty Importance
124
20%
25%
Figure 7.27. Satisfaction scores vs. satisfaction importance analysis – Mid-size vehicles
100% 95%
Expectations Vehicle design
Satisfaction Score
90%
Sales service quality
85%
Vehicle quality
Comfort and functionality
Image
80%
After sales service quality Value for money
75% 70% Costs of ownership
65% 60% 0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Satisfaction Importance
Figure 7.28. Satisfaction scores vs. loyalty importance analysis – Mid-size vehicles
100% 95%
Expectations
Satisfaction Score
90%
Vehicle design Comfort and functionality
85%
Vehicle quality Sales service quality
Image
80% After sales service quality
Value for money
Overall satisfaction
75% 70% Costs of ownership
65% 60% 0%
5%
10%
15%
Loyalty Importance
125
20%
25%
Figure 7.29. Satisfaction scores vs. satisfaction importance analysis – Full-size and large vehicles
100%
Satisfaction Score
95%
Expectations Vehicle design
90%
Sales service quality
Comfort and functionality
85%
Vehicle quality
Image
80%
After sales service quality
75%
Value for money
70%
Costs of ownership
65% 60% 0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Satisfaction Importance
Figure 7.30. Satisfaction scores vs. loyalty importance analysis – Full-size and large vehicles
100%
Satisfaction Score
95%
Expectations Vehicle design
90%
Comfort and functionality
Sales service quality Vehicle quality
85% Image
80%
Overall satisfaction
75%
Value for money
After sales service quality
Costs of ownership
70% 65% 60% 0%
5%
10%
15%
20%
25%
Loyalty Importance
Division of the analysis into different customer segments does not significantly change the overall picture. Again the most important is loyalty but the loyalty is in a large part created by overall satisfaction. Fortunately outcome from satisfaction importance and loyalty importance analysis is the same. There are definitely four areas that score much 126
below the minimum level of 85%. After sales service quality, value for money, costs of ownership and image need to be taken care of in order to improve overall satisfaction and loyalty of Company X customers in Poland. The strength of influence on satisfaction and loyalty generation is not that significant compared to e.g. vehicle quality or comfort and functionality however as discussed earlier this is the scope of responsibility for sales company in Poland. The other factors beside sales service quality (where score is high enough and positively influences satisfaction and loyalty) are beside the direct responsibility of sales company representing brand in Poland. Furthermore the score on those factors lies above the red line of 85% thus the improvement of brand performance in this respect is definitely more difficult to achieve. The segmentation of customers does not produce different results in terms of which areas score the lowest and have quite strong influence on satisfaction and loyalty creation. The only difference is prioritization of the four areas. For all groups of customers analyzed in the study between the four analyzed areas for improvement action the most important is the quality of after-sales service. Value for money is the second important element with exception of mid-size vehicles customers that place this element at the end of the list. Very close to value for money factor with regard to its strength of influence lies the costs of ownership variable. The least important element is the image of a brand. 7.4.4. Satisfaction vs. importance analysis - 3 customer segments –outer model In order to roll out some action plan the detailed analysis needs to be performed analogically to the one carried out for the total brand. Analyzing after sales service quality, for all customer groups professionalism of sales representatives, willingness to properly inform customers, overall service quality, promptitude of service and timing abidance are the most important elements generating the largest part of overall after-sales service satisfaction. For mid-size vehicles customers the atmosphere of showroom is placed at the 6th position of importance list while for the two other model groups it is one of the most important elements. Availability of spare parts is in the middle range of strength of influence for all customers. At the bottom of 127
the list for after sales service quality is the availability of substitute vehicle. It is the least important area and at the same time it scores the lowest for mid-size and full-size vehicles clients which is understandable as the more customers spend on their vehicle the more service they require if their car visits the workshop. If it comes to evaluation of customers satisfaction with particular elements of after-sales service it occurs that all of them score much below the minimum level of 85% which means that they all need to be taken care of however with different prioritization list for different model ranges. The most satisfied customers with after-sales service are the ones who drive the mid-size vehicles. However the score is not satisfactory enough to resign from reparation program. Therefore the action plan needs to be invented in order to improve customers’ satisfaction with service offered by after-sales department at the dealerships with accordance to the presented priorities list. It seems that a small “revolution” is needed in order fix all the problems as there is no positive sign of service which is satisfactory for the clients.
Figure 7.31. Satisfaction score vs. loyalty importance – After sales service– Compact vehicles
83,0% Satisfaction Score
81,0% 79,0%
Timing abidance
Atmosphere
77,0% 75,0%
Availability of spare parts
Willingness to inform Professionalism of rep
Availability of substitute car
73,0%
Promptitude of service
71,0%
Overall service quality
69,0% 8,0%
9,0%
10,0%
11,0%
12,0%
Loyalty Importance
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13,0%
14,0%
Figure 7.32. Satisfaction score vs. loyalty importance – After sales service – Mid-size
Satisfaction Score
vehicles
83% 81% 79% 77% 75% 73% 71% 69% 67% 65% 63%
Timing abidance Availability of spare parts
Professionalism of rep
Promptitude of service Atmosphere
Willingness to inform Overall service quality
Availability of substitute car
8,0%
9,0%
10,0%
11,0%
12,0%
13,0%
14,0%
15,0%
Loyalty Importance
Figure 7.33. Satisfaction score vs. loyalty importance – After sales service – Full-size and large vehicles
83,0% Satisfaction Score
81,0% Atmosphere
79,0% 77,0%
Willingness to inform
75,0%
Professionalism of rep
Availability of spare parts
73,0%
Timing abidance
71,0%
Availability of substitute car
Overall service quality
Promptitude of service
69,0% 8,0%
9,0%
10,0%
11,0%
12,0%
Loyalty Importance
129
13,0%
14,0%
Moving on to value for money evaluation there are two elements that create it. It is generally perceived product quality with regard to its price. As the perception of product quality itself and its comfort and functionality is good enough the only element that needs improvement is the level of price. Generally customers perceive Company X vehicles as being too expensive with regard to the overall quality they offer. Therefore some repricing program might be useful in order to improve the perceived value of cars. This element might be also dangerous as too much intervention into pricing policy may diminish the value of particular brand vehicles. Price is also the factor that creates value of the car thus it needs to be carefully tailored to each model against competition. The value for money score is the lowest for full-size and large vehicles owners than for compact cars and the highest for mid-size range. Therefore it seems that pricing policy has to be definitely adjusted for the least and the most expensive vehicles and only slightly for the middle sized cars. Figure 7.34. Satisfaction score vs. loyalty importance – Value for money– Compact, Midsize, Full-size and large vehicles
78% Satisfaction Score
77%
Vehicle quality with respect to its price - Mid-size Price of the vehicle with respect to its quality - Mid-size
76% 75% 74% 73% 72% 48,0%
Vehicle quality with respect to its price - Compact Price of the vehicle with respect to its quality - Compact Vehicle quality with respect to its price - Full-size and large Price of the vehicle with respect to its quality - Full-size and large
49,0%
50,0%
51,0%
52,0%
Loyalty Importance
Moving to detailed analysis of costs of ownership, it is apparent that comparing to results for the total brand there are not many differences. For all model groups the highest importance and at the same time the lowest scores are given for costs of regular service,
130
costs of spare parts and repairs. After sales service pricing list needs to be adjusted in order to improve customers perception of this area and at the end their loyalty. Figure 7.35. Satisfaction score vs. loyalty importance – Costs of ownership – Compact vehicles
Overall costs of vehicle usage
Satisfaction Score
78,0% 76,0%
Costs of fuel
74,0% 72,0% 70,0% 68,0%
Costs of regular service
66,0% 64,0%
Costs of insurance Costs of spare parts
62,0% 60,0%
Costs of repairs
12,0% 13,0% 14,0% 15,0% 16,0% 17,0% 18,0% 19,0% 20,0% Loyalty Importance
Figure 7.36. Satisfaction score vs. loyalty importance – Costs of ownership – Mid-size vehicles
76%
Costs of fuel
Overall costs of vehicle usage
Satisfaction Score
74% 72% 70%
Costs of regular service
68% 66% 64% 62%
Costs of repairs
Costs of insurance
Costs of spare parts
60% 12,0%
14,0%
16,0% Loyalty Importance
131
18,0%
20,0%
Furthermore costs of fuel are the least important for clients of full-size and large vehicles which is understandable. The strength of their importance rises while moving towards less expensive segments of cars. Costs of insurance are the least important for compact and mid-size vehicles customers and move one position up in the list for full-size and large vehicles owners. To sum up general evaluation of costs of ownership it seems that first thing that should be improved is the pricing policy of after sales service department. This result proves negative evaluation of this area in total. Next elements that could improve customers satisfaction and loyalty lie in the area of responsibility of sales department. Costs of fuel or insurance may be decreased by incentive campaigns where i.e. fuel card with particular limit or free insurance could be given to customers at the purchase of the vehicle. Figure 7.37. Satisfaction score vs. loyalty importance – Costs of ownership – Full-size and large vehicles
85% Satisfaction Score
Costs of fuel
80%
Overall costs of vehicle usage
75% 70% 65%
Costs of regular service
Costs of insurance
Costs of repairs Costs of spare parts
60% 12,0% 13,0% 14,0% 15,0% 16,0%
17,0% 18,0% 19,0% 20,0%
Loyalty Importance
In terms of image, the company involvement in improvement of customers satisfaction definitely needs to be increased. Such researches as brand satisfaction model give clients the possibility to speak up and express their opinion about the brand and the offered products. This area is not evaluated as satisfactory enough and for all model groups lies at the top of the importance list. Customers evaluation of sales company involvement in 132
actions that make the driver’s lives easier scores also below 85% and is one of the most important elements creating brand image. As the area is not precise it needs to be investigated in more details by maybe a small, one time conversation with the group of customers. Stable market position and safety and technological leadership are also important elements for all model groups however their score lies above minimum level of 85% thus they need no improvement. Figure 7.38. Satisfaction score vs. loyalty importance – Image – Compact vehicles
95,0% Safety assurance
Satisfaction Score
90,0%
Technological leadership
85,0% Environmental care
80,0%
Promotional Visibility (motorshows, sponsoring, advertising)
75,0% 70,0%
Making drivers' lives easier
Involvement in social actions
Stable market position of a brand
Overall image Brand involvement in improvement of customers satisfaction
65,0% 8,0%
9,0%
10,0%
11,0%
12,0%
13,0%
Loyalty Importance
Safety assurance gives very interesting field for analysis. The score for each model range is one of the highest and also does not need any reparation action. However for compact vehicles owners it is one of the most important factors, while for mid-size vehicles clients is the least important one and for full-size and large vehicles customers is placed in the middle of importance scale. These findings are in-line with customer profile research, which pointed out that safety is much more important factor for compact cars owners, than for remaining customer segments. Environmental care is not that much important for “compact” clients while it moves to the middle importance for the two other model groups. As it scores below 85% in each case it requires some action to be taken. One of
133
the actions suggested would be more news about ecological properties of Company X vehicles given to press and media in order to improve brand image in this respect. Figure 7.39. Satisfaction score vs. loyalty importance – Image – Mid-size vehicles
95%
Safety assurance
Stable market position of a brand
Satisfaction Score
90% Overall image
85%
Making drivers' lives easier
80% 75%
Environmental care
Involvement in social actions
Technological leadership
Brand involvement in improvement of customers satisfaction
Promotional Visibility (motorshows, sponsoring, advertising)
70% 65% 8,0%
9,0%
10,0%
11,0%
12,0%
13,0%
14,0%
Loyalty Importance
Figure 7.40. Satisfaction score vs. loyalty importance – Image – Full-size and large vehicles
95%
Safety assurance
Satisfaction Score
90% Stable market position of a brand
85%
Technological leadership
Environmental care
80%
Overall image
Promotional Visibility 75% (motorshows, sponsoring, advertising)
70%
Involvement in social actions
Making drivers' lives easier Brand involvement in improvement of customers satisfaction
65% 8,0%
9,0%
10,0%
11,0%
12,0%
Loyalty Importance
134
13,0%
14,0%
Involvement in social actions is evaluated as the worst element of brand image however its importance is the lowest for all models. The company may think about some action plan in this area provided that all other elements that have higher priority are taken care of. Generally promotional visibility of a brand is of middle importance for lower segments customers and is the least important for full-size and large vehicles owners. As its score is below 85% in each case the company may introduce some program that will improve brand visibility in media, press and outdoor visuals especially in the two lowest segments. To sum up the analysis of image it seems that beside safety assurance, customers evaluation of brand stability and technological leadership, the company needs to take care of all the other elements that create brand image. The priority list is a bit different for different model ranges however it can be merged in order to save resources and achieve a goal of image improvement. 7.4.5. Summary of analysis for 3 customer segments The three analyzed groups of customers present a bit different approach to purchasing and using a vehicle. While their satisfaction is generated in quite similar manner, the loyalty generation is much more complicated. The owners of compact vehicles place more importance in Value for Money and Costs of Ownership meaning that they are simply more price/costs sensitive. Such result is definitely understandable as limited amount of resources forces the more cost saving approach while deciding on vehicle purchase. Furthermore After-sales service is the most important element for compact cars users. The other two groups of customers place less importance in this area. Mid-size, Full-size and Large vehicles owners are more similar to each other compared to the compact cars customers. Instead of placing more importance to after-sales service quality, costs of ownership and Value for money, their loyalty is in a larger part generated by better sales service quality, vehicle quality as well as comfort and functionality. In order to implement some action plan the detailed analysis of the four areas that need improvement presented above in the chapter should be deeply investigated. Some detailed 135
areas score better or lower for different customer groups. Furthermore the importance of the areas is different for the three analyzed customer segments. All in all, the action plan for the total brand has to be adjusted according to differences in results achieved in the analysis. The acquired intelligence about levels of importance should be made wellknown across the whole company in order to prioritize or disregard taken operations.
136
CONCLUSIONS AND RECOMMENDATIONS After detailed analysis of Brand Satisfaction Model results the following conclusions and recommendations arisen: -
The structure of BSM evolving mainly from ECSI and JD Power methodology for automotive industry is comprehensive, statistically well grounded and offers a great portion of knowledge for Company X in Poland. It covers all important aspects of customer satisfaction as total experience with a brand. The BSM not only covers evaluation of company’s performance in different areas but, what is most important, distinguishes the importance of specified areas to overall satisfaction and loyalty generation.
-
The BSM model discovered that there are significant differences in how satisfaction and loyalty of customers are created. Satisfaction concept in the automotive industry is less complicated and is based mainly on vehicle quality, comfort and functionality which generate over 75% of customers satisfaction. On the other hand client’s loyalty is much more complex. Importance of vehicle quality, comfort and functionality decreases while at the same time the importance of sales and after sales service quality as well as costs of ownership drastically increases. Therefore there are not 2 but 5 factors that should be taken into account when implementing loyalty improvement programs.
-
There are different perceptions of satisfaction and loyalty concepts between the 3 specified segments of customers. Compact vehicles users are much more price and costs sensitive. They also pay stronger attention to the image of a brand and post-purchase service they receive. Mid-size vehicles users are definitely closer in terms of their profile to the third group of customers however they are more vehicle comfort and quality oriented while at the same time do not expect so high value for money as other clients. The full-size and large vehicles owners are definitely the least price and costs sensitive. Vehicle quality, comfort and functionality and sales service quality are the most important elements strongly affecting the level of their loyalty.
-
Company X should definitely conduct the Brand Satisfaction Model study at least on a yearly basis. The knowledge should be regularly spread across the entire organization and management should make sure that all employees understand their customers according to BSM findings. Marketing, sales and PR actions should always take into consideration the recommendations of BSM in order to create more satisfied and loyal customers. The 137
operations should be adjusted according to different customer profiles analyzed in the study as clients from different segments have different priorities lists. Therefore all measures such as incentive actions, communication, improvement of customer service processes should be targeted at specific wants and needs of particular segment. -
After the Brand Satisfaction Model was conducted, analyzed and the acquired knowledge was spread out across the whole company, the reparation program for after-sales service quality has started. First improvements are already visible in higher scores (+2 pp) for CSI in after-sales service quality. According to BSM findings the prioritization of actions has been set which helped to concentrate on those areas that have the strongest influence on quality of after-sales service. This is a short term success which hopefully will turn into long term trend.
-
The next valuable step would be to propose the BSM as a unified tool for measuring satisfaction and loyalty of customers in the whole automotive sector in Poland. The model could be proposed to the Board of Directors of Polish Official Association of Automotive Importers in order to create a comprehensive platform for comparison of different brands performance in a field of customer satisfaction. Such platform would be not only valuable for automotive companies present on Polish markets but also for customers which would benefit from higher level of service provided. This step could ignite the positive improvement of competitiveness between automotive producers operating in Poland.
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REFERENCES ANDERSON, E.W., FORNELL, C., LEHMANN, D.R. (1994): “Customer satisfaction, market share and profitability: Findings from Sweden”. Journal of Marketing, vol. 58 (3), pp. 53-66 ANDERSON, E.W., FORNELL, C., RUST, R.T. (1994): “Customer satisfaction, productivity and profitability: differences between goods and services”. Marketing Science, vol. 16 (2), pp. 129 – 45 ANDERSON, E. W., BRYANT, B. E., CHA, J., FORNELL, C., JOHNSON, M.D. (1996): “The American Customer Satisfaction Index: Nature, Purpose and Findings”. Journal of Marketing, vol. 60, pp. 7 – 18 ANDREASSEN, T.W., CHA, J., GUSTAFSSON, A., JOHNSON, M.D., LERVIK, L. (2001): “The evolution and future of national customer satisfaction index models”. Journal of Economic Psychology, vol. 22, pp. 217 – 245 BAYOL M.P. DE LA FOYE A., TELLIER C., TENENHAUS M. (2000): “Use of PLS Path Modeling to Estimate the European Consumer Satisfaction Index (ECSI) Model”, Statistica Applicata – Italian Journal of Applied Statistics, vol. 12, no 3, pp. 361-375. CHIN W.W. (1998): “The partial least squares approach for structural equation modeling”, in G.A. Marcoulides , Modern Methods for Business Research, Lawrence Erlbaum Associates, pp. 295-336. CHIN W.W. & NEWSTED P.R. (1999): “Structural Equation Modeling Analysis with Small Samples using Partial Least Squares”, in:Hoyle R., Statistical STartegies for Small Sample Research, Sage Publications, pp. 307-341. CHIN W.W. (2001): “PLS-Graph User’s Guide”, C.T. Bauer College of Business, University of Houston, USA.
139
www.efqm.org FORNELL C., & LARCKER D. (1981): “Evaluating structural equation models with unobservable variables and measurement error”, Journal of Marketing Research, 18, pp.39-50. FORNELL C. (1992): “A National Customer Satisfaction Barometer: The Swedish Experience”, Journal of Marketing, Vol. 56, 6-21. FORNELL C. & CHA J. (1994): “Partial Least Squares”, in Advanced Methods of Marketing Research, R.P. Bagozzi, Basil Blackwell, Cambridge, MA., pp. 52-78. GRONHOLDT, L., KRISTENSEN, K., MARTENSEN, A. (2000): “The relationship between customer satisfaction and loyalty: cross-industry differences”. Total Quality Management, vol. 11, pp. 509 – 514 GRONHOLDT, L., KRISTENSEN, K., MARTENSEN, A. (2002): “Customer satisfaction and business performance” in “Business performance measurement: Theory and Practice”, Cambridge University Press, pp. 280 – 283 GUSTAFSSON, A., HERRMANN, A., HUBER, F., JOHNSON, M.D. (1997): “Customer retention in the automotive industry. Quality, satisfaction and loyalty”, Gabler, pp. 119 – 223 HOPTON, CH., MARKEY, R.G., REICHHELD, F.F. (2000): “The loyalty effect – the relationship between loyalty and profits”. European Business Journal, vol.12 no.3, pp. 134- 139 www.jdpower.com JOHNSON, M.D. (1996): “Customer orientation and market action”. Prentice Hall, pp. 42 – 108 KLINE, R. B. (1998). “Structural equation modeling”, London: The Guilford Press
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LOHMÖLLER J.-B. (1984): LVPLS Program Manual, Version 1.6, Zentralarchiv für Empirische Sozialforschung, Universität zu Köln, Köln. LOHMÖLLER J.-B. (1989): “Latent Variables Path Modeling with Partial Least Squares, Physica-Verlag, Heildelberg. MUELLER, R. O. (1999). “Basic principles of structural equation modeling. An introduction to LISREL and EQS.”, Springer-Verlag: New York MYERS J.H., MULLET G.M. “Structural Equation Models”, chapter 15 of “Managerial Application of Multivariate Analysis in Marketing”, Thomson, 2003. TENENHAUS, M; VINZI, V. E.; CHATELINC, Y.-M. and LAUROB, C. (2005): “PLS path modeling.”, Computational Statistics and Data Analyses, no. 48, pp. 159-205 The EFQM Excellence Model 1999 manual. Aarhus School of Business, Business Performance Management Program WOLD, H. (1982). “Soft modelling: the basic design and some extensions.”, In Jöreskog, K.G. and Wold, H. “Systems under indirect observations, Part II”, Amsterdam: North Holland Press WOLD H. (1985): “Partial Least Squares”, in Encyclopedia of Statistical Sciences, vol. 6, Kotz, S&Johnson, N.L., John Wiley & Sons, New York, pp. 581-591.
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APPENDICES Appendix 1. Latent Variables Correlation matrix (First Version of BSM) Aftersales qualit y
Comf ort
Costs of owner ship
Expect ations
Image
Loyal ty
Overall satisfa ction
Sales qualit y
Value Vehic Vehic for le le mone Desig qualit y n y
Aftersales quality
1,000 000
Comfort
0,462 303
1,000 000
Costs of ownersh ip
0,472 885
0,540 268
1,0000 00
Expectat ions
0,195 676
0,419 443
0,2336 57
1,00000 0
Image
0,467 905
0,723 528
0,4962 45
0,36794 3
1,0000 00
Loyalty
0,577 201
0,544 896
0,4430 39
0,19953 7
0,6073 74
1,000 000
Overall satisfact ion
0,473 978
0,594 959
0,4804 12
0,27064 4
0,6840 18
0,665 158
1,0000 00
Sales quality
0,436 633
0,541 961
0,3750 76
0,32045 7
0,4818 02
0,551 462
0,3487 33
1,0000 00
Value for money
0,561 808
0,643 671
0,5313 82
0,29853 7
0,6873 65
0,655 578
0,7730 88
0,4052 19
1,000 000
Vehicle Design
0,271 908
0,668 756
0,3893 03
0,39787 0
0,5674 09
0,400 030
0,4127 73
0,4628 21
0,431 422
1,000 000
Vehicle quality
0,507 657
0,744 820
0,5183 36
0,28770 4
0,7358 78
0,671 108
0,8412 18
0,4224 55
0,807 373
0,568 071
142
1,000 000
Appendix 2. Results of Bootstrapping algorithm application on the final structure of the Brand Satisfaction Model (sample size 346, number of iterations 500) Outer Model T-Statistic Costs AfterCom of sales fort owne quality rship comfor t
23,3 479 65
comfor t%a
30,1 337 15
comfor t%b
19,4 628 46
comfor t%c
16,7 891 08
comfor t%d
9,56 163 8
comfor t%e
16,0 563 96
comfor t%f
13,3 499 30
comfor t%g
10,3 806 44
comfor t%h
8,81 846 2
costs
18,04 5577
costs %a
12,35 5443
costs %b
13,25 4982
costs %c
43,04 7303
costs %d
41,80 3177
costs
40,78
Expec tation s
Imag e
Loyalt y
143
Overa Sales ll qualit satisf y action
Value for money
Vehicle Design
Vehicle quality
%e
8004
design
58,4998 48
design %a
41,3434 76
design %b
40,3026 58
design %c
58,7475 64
design %d
47,2310 27
image
17,03 3243
image %a
14,58 1061
image %b
17,07 4691
image %c
27,02 9983
image %d
24,12 7112
image %e
9,084 976
image %f
9,776 476
image %g
11,19 7843
image %h
20,87 3509
loyalty 1
35,31 6365
loyalty 2
32,05 0081
loyalty 3
28,20 4140
loyalty 4
15,11 8128
oczek %d
23,31 8976
oczek %f
23,67 6596
oczek %g
33,34 7890
sales
30,00 9971
sales
26,46
144
%a
1719
sales %b
29,92 6009
sales %c
26,38 0701
sales %d
33,18 0027
sales %e
34,55 3519
sales %f
16,71 1855
sales %g
15,77 3017
sales %h
16,19 3364
sales %i
15,71 6443
sales %j
12,89 3444
sat1
126,7 03100
sat1a
124,8 51939
sat1b
148,7 10726
service
69,8193 07
service 69,8322 %a 65 service 87,3355 %b 71 service 36,9407 %c 96 service 14,4349 %d 00 service 25,7976 %e 21 service 58,0036 %f 85 service 35,6557 %g 48 value1
472,423 591
value2
489,753 636
vehqua
47,9541
145
l
61
vehqua l%a
31,6665 12
vehqua l%b
11,9413 13
vehqua l%c
10,9076 35
vehqua l%d
14,5858 02
vehqua l%e
19,9560 50
vehqua l%f
20,4257 33
vehqua l%g
12,2437 94
Path Coefficients (Mean, STDEV, T-Values)
Original Sample (O)
Sample Mean (M)
Standard Deviation (STDEV)
Standard Error (STERR)
T Statistics (|O/STERR|)
After-sales quality > Loyalty
0,238271
0,239061
0,072230
0,072230
3,298767
After-sales quality > Value for money
0,187820
0,187318
0,044108
0,044108
4,258204
Comfort -> Vehicle quality
0,747348
0,747459
0,033822
0,033822
22,096331
Costs of ownership > After-sales quality
0,483602
0,485781
0,044575
0,044575
10,849238
Expectations -> Sales quality
0,325988
0,332319
0,055971
0,055971
5,824281
Image -> Expectations
0,369774
0,374751
0,059031
0,059031
6,264093
Image -> Value for money
0,167117
0,171554
0,054613
0,054613
3,059988
Overall satisfaction > Loyalty
0,447200
0,444217
0,076290
0,076290
5,861885
Sales quality -> Loyalty
0,294576
0,299933
0,067905
0,067905
4,338093
Value for money -> Overall satisfaction
0,297836
0,298635
0,069204
0,069204
4,303737
Vehicle Design -> Image
0,224727
0,222102
0,061789
0,061789
3,637015
Vehicle quality -> Image
0,603007
0,602738
0,051742
0,051742
11,654194
146
Vehicle quality -> Overall satisfaction
0,591712
0,589664
0,062870
0,062870
9,411712
Vehicle quality -> Value for money
0,585819
0,579589
0,060972
0,060972
9,607931
Total Effects (Mean, STDEV, T-Values)
Original Sample (O)
Sample Mean (M)
Standard Deviation (STDEV)
Standard Error (STERR)
T Statistics (|O/STERR|)
After-sales quality > Loyalty
0,263287
0,263663
0,068598
0,068598
3,838100
After-sales quality > Overall satisfaction
0,055940
0,055355
0,016876
0,016876
3,314835
After-sales quality > Value for money
0,187820
0,187318
0,044108
0,044108
4,258204
Comfort -> Expectations
0,166641
0,168877
0,031725
0,031725
5,252745
Comfort -> Image
0,450656
0,450739
0,045892
0,045892
9,819875
Comfort -> Loyalty
0,282105
0,281160
0,050080
0,050080
5,633063
Comfort -> Overall satisfaction
0,595041
0,593675
0,032774
0,032774
18,155782
Comfort -> Sales quality
0,054323
0,056662
0,016462
0,016462
3,299916
Comfort -> Value for money
0,513122
0,510928
0,037349
0,037349
13,738612
Comfort -> Vehicle quality
0,747348
0,747459
0,033822
0,033822
22,096331
Costs of ownership > After-sales quality
0,483602
0,485781
0,044575
0,044575
10,849238
Costs of ownership > Loyalty
0,127326
0,128075
0,035859
0,035859
3,550800
Costs of ownership > Overall satisfaction
0,027052
0,026942
0,008732
0,008732
3,098027
Costs of ownership > Value for money
0,090830
0,091187
0,023729
0,023729
3,827742
Expectations -> Loyalty
0,096028
0,099249
0,026947
0,026947
3,563543
Expectations -> Sales quality
0,325988
0,332319
0,055971
0,055971
5,824281
Image -> Expectations
0,369774
0,374751
0,059031
0,059031
6,264093
Image -> Loyalty
0,057767
0,060417
0,015713
0,015713
3,676356
147
Image -> Overall satisfaction
0,049773
0,051291
0,020562
0,020562
2,420635
Image -> Sales quality
0,120542
0,125779
0,033990
0,033990
3,546394
Image -> Value for money
0,167117
0,171554
0,054613
0,054613
3,059988
Overall satisfaction > Loyalty
0,447200
0,444217
0,076290
0,076290
5,861885
Sales quality -> Loyalty
0,294576
0,299933
0,067905
0,067905
4,338093
Value for money -> Loyalty
0,133192
0,133208
0,040312
0,040312
3,304033
Value for money -> Overall satisfaction
0,297836
0,298635
0,069204
0,069204
4,303737
Vehicle Design -> Expectations
0,083098
0,082224
0,023415
0,023415
3,548991
Vehicle Design -> Image
0,224727
0,222102
0,061789
0,061789
3,637015
Vehicle Design -> Loyalty
0,012982
0,013184
0,004496
0,004496
2,887577
Vehicle Design -> Overall satisfaction
0,011185
0,011109
0,004972
0,004972
2,249745
Vehicle Design -> Sales quality
0,027089
0,027531
0,009785
0,009785
2,768330
Vehicle Design -> Value for money
0,037556
0,037089
0,013870
0,013870
2,707606
Vehicle quality -> Expectations
0,222977
0,225960
0,041241
0,041241
5,406681
Vehicle quality -> Image
0,603007
0,602738
0,051742
0,051742
11,654194
Vehicle quality -> Loyalty
0,377475
0,376180
0,064792
0,064792
5,825977
Vehicle quality -> Overall satisfaction
0,796203
0,794373
0,028609
0,028609
27,830996
Vehicle quality -> Sales quality
0,072688
0,075799
0,021703
0,021703
3,349242
Vehicle quality -> Value for money
0,686592
0,683642
0,040862
0,040862
16,802540
148
Appendix 3. Results of PLS algorithm application on the final structure of the Brand Satisfaction Model – Total Brand (Path Weighting Scheme, Mean replacement algorithm for missing values, Mean 0 and Var 1 data metric, Abort Criterion 1.0E-5, Initial Weights 1.0) Quality Criteria
Overview AVE
Composite Reliability
R Square
Cronbachs Alpha
After-sales quality
0,743979
0,958390
0,233871
0,949202
0,743979
Comfort
0,482429
0,892422
0,864926
0,482429
Costs of ownership
0,610747
0,902457
0,870282
0,610747
Expectations
0,690098
0,869728
0,136733
0,776171
0,690098
0,094039
Image
0,495642
0,897251
0,570014
0,872570
0,495642
0,102415
Loyalty
0,677321
0,893289
0,595556
0,840668
0,677320
0,148198
Overall satisfaction
0,921945
0,972553
0,721920
0,957658
0,921945
0,342770
Sales quality
0,596738
0,941729
0,106268
0,931259
0,596738
0,064057
Value for money
0,975887
0,987796
0,690302
0,975291
0,975887
0,171579
Vehicle Design
0,808352
0,954709
0,940627
0,808352
Vehicle quality
0,544042
0,904136
0,878112
0,544042
0,558528
Communality Redundancy 0,172559
0,306066
Cross Loadings Afte rsale Com s fort qual ity
Costs Expec of tation owne s rship
Imag e
comfort
0,41 0,77 518 0665 3
0,404 223
0,328 513
comfort %a
0,35 0,79 404 3244 7
0,430 350
comfort %b
0,33 0,71 293 4081 6
comfort 0,27 0,73 %c 680 4312
Loyal ty
Overa ll Sales satisf qualit actio y n
Value Vehicle for Design money
0,657 844
0,598 381
0,626 970
0,377 897
0,6422 43
0,5221 35
0,728104
0,322 557
0,622 905
0,434 095
0,518 745
0,415 753
0,5663 67
0,5214 15
0,631213
0,333 370
0,376 840
0,507 730
0,306 953
0,356 747
0,473 658
0,4280 11
0,4923 00
0,496822
0,295 233
0,345 748
0,476 674
0,347 658
0,374 541
0,467 008
0,4009 78
0,5675 81
0,507877
149
Vehicle quality
9 comfort %d
0,30 0,62 058 7962 0
0,279 222
0,257 976
0,314 571
0,277 699
0,330 457
0,351 621
0,3536 77
0,4554 56
0,454317
comfort %e
0,31 0,72 130 5196 7
0,414 829
0,245 186
0,499 085
0,330 134
0,350 544
0,311 385
0,4063 73
0,4392 08
0,475461
comfort %f
0,25 0,68 119 7559 5
0,398 984
0,227 010
0,454 725
0,327 627
0,343 565
0,303 355
0,3609 40
0,4386 60
0,460855
comfort %g
0,27 0,58 927 2573 4
0,357 147
0,228 855
0,431 754
0,288 484
0,322 177
0,325 045
0,3306 19
0,3146 90
0,371115
comfort %h
0,32 0,58 927 0688 9
0,295 748
0,251 586
0,451 390
0,335 876
0,333 032
0,343 880
0,3767 34
0,3947 46
0,411571
costs
0,34 0,52 056 4954 6
0,737 651
0,207 349
0,478 685
0,374 383
0,437 970
0,345 899
0,4629 75
0,4168 96
0,492386
costs% a
0,26 0,45 469 2463 9
0,656 791
0,231 846
0,411 347
0,318 954
0,393 485
0,335 405
0,3946 96
0,3919 63
0,433479
costs% b
0,27 0,37 572 6959 4
0,636 457
0,176 097
0,343 324
0,248 807
0,279 896
0,240 078
0,3923 83
0,2325 66
0,340275
costs% c
0,49 0,45 157 6671 4
0,867 725
0,188 785
0,428 528
0,397 181
0,424 120
0,284 023
0,4744 82
0,3047 13
0,450861
costs% d
0,43 0,34 300 8362 0
0,877 533
0,160 271
0,324 645
0,370 097
0,377 997
0,271 003
0,3926 83
0,2275 27
0,373318
costs% e
0,39 0,31 462 4541 2
0,872 290
0,131 860
0,282 688
0,331 793
0,290 175
0,242 410
0,3367 33
0,2060 15
0,288161
design
0,22 0,60 923 0900 9
0,331 491
0,363 685
0,528 830
0,343 476
0,406 151
0,455 968
0,4107 13
0,9195 60
0,546477
design %a
0,19 0,57 872 1377 2
0,292 561
0,405 965
0,457 387
0,296 767
0,299 219
0,411 820
0,3468 32
0,8991 03
0,456093
design %b
0,29 0,61 149 3764 1
0,306 746
0,340 915
0,517 063
0,390 298
0,414 257
0,443 990
0,4245 85
0,8817 53
0,569434
design %c
0,23 0,62 451 0817 6
0,335 826
0,371 381
0,535 218
0,379 453
0,354 769
0,399 881
0,3900 44
0,9215 50
0,519393
design %d
0,26 0,60 288 1991 2
0,369 807
0,335 811
0,523 198
0,371 789
0,362 871
0,363 611
0,3539 26
0,8723 76
0,486892
150
image
0,39 0,48 755 7995 0
0,386 380
0,218 654
0,701 045
0,562 129
0,780 180
0,291 337
0,6336 81
0,2930 73
0,683729
image %a
0,28 0,59 387 2018 2
0,326 940
0,301 642
0,704 244
0,393 883
0,441 665
0,328 708
0,4871 33
0,4828 71
0,557372
image %b
0,35 0,55 377 6210 6
0,305 367
0,303 942
0,731 372
0,424 540
0,491 362
0,333 849
0,5158 19
0,4419 12
0,556405
image %c
0,33 0,60 725 0184 1
0,338 403
0,302 684
0,798 033
0,418 049
0,474 734
0,349 939
0,5257 82
0,4996 44
0,557637
image %d
0,42 0,56 835 7990 0
0,392 895
0,298 147
0,801 905
0,540 814
0,523 949
0,347 597
0,5455 08
0,4577 48
0,591331
image %e
0,21 0,35 328 3444 6
0,288 737
0,162 197
0,571 081
0,310 326
0,300 137
0,287 903
0,3013 89
0,2847 67
0,313185
image %f
0,26 0,36 468 3756 7
0,323 750
0,226 507
0,589 476
0,251 352
0,256 501
0,335 371
0,2966 40
0,3147 30
0,273876
image %g
0,27 0,44 957 8949 3
0,272 204
0,230 241
0,641 581
0,264 844
0,355 340
0,350 556
0,3483 69
0,3657 22
0,363895
image %h
0,33 0,51 343 8644 3
0,358 198
0,269 058
0,757 166
0,488 783
0,484 440
0,426 619
0,5247 12
0,4420 51
0,553281
loyalty1
0,48 0,54 340 2229 5
0,422 210
0,165 258
0,654 117
0,858 884
0,730 237
0,350 103
0,7088 25
0,4195 05
0,717310
loyalty2
0,49 0,39 124 3705 8
0,360 559
0,150 659
0,388 519
0,849 768
0,409 149
0,601 351
0,4471 47
0,2846 13
0,443346
loyalty3
0,46 0,48 243 9677 3
0,399 238
0,162 518
0,597 794
0,832 810
0,668 537
0,302 142
0,6436 57
0,3532 62
0,640383
loyalty4
0,46 0,32 802 3256 3
0,241 284
0,160 352
0,284 187
0,745 602
0,320 568
0,599 213
0,2996 79
0,2330 10
0,339920
oczek% d
0,20 0,38 893 7432 9
0,169 969
0,819 162
0,317 313
0,223 781
0,281 840
0,273 308
0,2789 32
0,3446 53
0,275686
oczek% f
0,12 0,29 499 2288 0
0,175 901
0,812 377
0,288 441
0,112 014
0,170 220
0,214 761
0,2456 70
0,2482 57
0,207826
oczek% g
0,13 0,35 856 3935 3
0,213 511
0,859 832
0,314 003
0,142 032
0,203 527
0,314 813
0,2090 67
0,3973 06
0,229824
0,36
0,252
0,246
0,397
0,528
0,316
0,822
0,3822
0,3493
0,350412
sales
0,45
151
526 4
5753
875
057
370
009
121
780
28
66
sales% a
0,32 0,42 784 3849 2
0,298 947
0,287 025
0,336 650
0,419 545
0,248 279
0,811 570
0,2955 02
0,3626 91
0,291633
sales% b
0,32 0,38 839 1770 3
0,208 227
0,296 067
0,315 855
0,357 203
0,225 193
0,821 681
0,2884 70
0,3517 13
0,277101
sales% c
0,30 0,39 504 9836 6
0,286 708
0,263 665
0,321 495
0,392 029
0,252 964
0,815 307
0,2904 97
0,3850 53
0,292211
sales% d
0,27 0,38 027 9058 3
0,294 132
0,261 081
0,319 880
0,411 527
0,206 702
0,816 170
0,2367 89
0,4508 88
0,277261
sales% e
0,27 0,40 622 6462 9
0,271 066
0,308 866
0,329 426
0,383 189
0,199 607
0,829 765
0,2654 71
0,3792 45
0,281593
sales%f
0,30 0,40 826 3858 0
0,212 616
0,270 649
0,346 995
0,417 746
0,205 749
0,808 609
0,2730 74
0,3770 13
0,296421
sales% g
0,40 0,47 436 2152 1
0,332 306
0,249 525
0,450 652
0,427 141
0,283 768
0,695 434
0,3528 68
0,3441 20
0,397562
sales% h
0,37 0,39 720 4668 0
0,312 984
0,201 336
0,420 483
0,450 126
0,303 961
0,694 660
0,3146 24
0,3088 30
0,325406
sales%i
0,36 0,45 587 4564 1
0,324 306
0,197 376
0,421 795
0,395 518
0,316 973
0,702 338
0,3562 75
0,3495 71
0,400534
sales%j
0,33 0,37 059 9938 9
0,238 499
0,180 078
0,376 948
0,460 754
0,339 650
0,648 593
0,3238 25
0,2576 65
0,371654
sat1
0,41 0,55 786 6977 7
0,430 503
0,227 884
0,654 572
0,635 319
0,958 058
0,337 111
0,7367 71
0,3978 83
0,801064
sat1a
0,49 0,57 157 0757 2
0,468 881
0,264 398
0,639 015
0,634 799
0,955 991
0,315 372
0,7371 37
0,4015 69
0,777754
sat1b
0,45 0,57 739 1887 2
0,445 007
0,271 523
0,654 514
0,634 422
0,966 457
0,334 284
0,7528 72
0,3834 40
0,814336
service
0,91 0,39 085 7577 0
0,432 903
0,159 438
0,418 893
0,534 221
0,448 605
0,361 303
0,5428 32
0,2263 92
0,459934
service %a
0,91 0,37 114 6071 5
0,430 566
0,126 537
0,421 646
0,540 981
0,429 138
0,376 452
0,5349 53
0,1971 69
0,449369
service %b
0,93 0,39 124 9419
0,415 085
0,163 067
0,425 608
0,551 151
0,446 226
0,371 266
0,5297 04
0,2359 09
0,457422
152
0 service %c
0,88 0,35 438 9159 2
0,362 684
0,226 747
0,373 055
0,499 078
0,336 338
0,391 197
0,4275 78
0,2081 34
0,362109
service %d
0,66 0,33 484 8446 9
0,371 706
0,140 057
0,347 030
0,413 316
0,276 660
0,337 838
0,3394 94
0,2177 35
0,309927
service %e
0,79 0,44 644 1042 9
0,433 435
0,180 463
0,423 007
0,448 083
0,447 569
0,372 279
0,4928 49
0,3119 35
0,485847
service %f
0,90 0,46 405 7676 2
0,495 106
0,161 749
0,432 259
0,494 987
0,452 318
0,394 942
0,5190 78
0,2643 89
0,498021
service %g
0,86 0,39 544 4507 5
0,384 298
0,166 703
0,363 543
0,489 400
0,405 165
0,380 300
0,4549 30
0,2165 42
0,439719
value1
0,56 0,64 326 0399 5
0,515 694
0,284 279
0,675 551
0,650 288
0,757 064
0,400 800
0,9878 03
0,4263 08
0,793564
value2
0,54 0,62 702 2089 7
0,506 996
0,294 617
0,675 118
0,637 679
0,770 308
0,389 200
0,9879 37
0,4223 85
0,793294
vehqual
0,46 0,59 276 2375 7
0,409 694
0,212 044
0,677 228
0,644 525
0,899 455
0,351 119
0,7592 66
0,4018 98
0,863618
vehqual %a
0,50 0,51 293 5642 9
0,459 355
0,201 739
0,581 245
0,589 465
0,813 009
0,255 949
0,7037 83
0,3258 62
0,812594
vehqual %b
0,26 0,45 150 1192 6
0,314 975
0,106 089
0,445 967
0,287 377
0,401 476
0,218 691
0,4305 03
0,3602 62
0,600098
vehqual %c
0,35 0,54 409 9219 9
0,327 104
0,225 812
0,470 070
0,393 356
0,466 195
0,378 855
0,4817 96
0,4524 00
0,659822
vehqual %d
0,38 0,60 404 6278 5
0,351 052
0,239 984
0,525 130
0,409 600
0,486 742
0,306 893
0,5038 18
0,5124 30
0,710773
vehqual %e
0,32 0,54 360 2878 8
0,314 562
0,191 736
0,536 490
0,497 961
0,622 123
0,289 875
0,6127 21
0,4180 84
0,769276
vehqual %f
0,37 0,60 220 5111 8
0,371 688
0,247 211
0,519 143
0,537 681
0,588 587
0,359 426
0,6430 92
0,4497 20
0,767180
vehqual %g
0,27 0,56 306 8867 4
0,382 380
0,274 130
0,533 741
0,464 865
0,473 031
0,329 764
0,5216 26
0,5364 10
0,682027
153
Total Effects After sales quali ty
Comf ort
Costs Expe of ctatio Image owne ns rship
Aftersales quality 0,166 641
Comfort Costs of ownersh ip
0,4506 56
0,483 602
Expectat ions
Loyalt y
Over all Sales Value satisf qualit for actio y money n
0,2632 87
0,055 940
0,18782 0
0,2821 05
0,595 041
0,054 0,51312 323 2
0,1273 26
0,027 052
0,09083 0
0,0960 28 0,369 774
Image
0,0577 67
Vehicle Design
Vehicle quality
0,74734 8
0,325 988 0,049 773
0,120 0,16711 542 7
Loyalty Overall satisfact ion
0,4472 00
Sales quality
0,2945 76
Value for money
0,1331 92
0,297 836
Vehicle Design
0,083 098
0,2247 27
0,0129 82
0,011 185
0,027 0,03755 089 6
Vehicle quality
0,222 977
0,6030 07
0,3774 75
0,796 203
0,072 0,68659 688 2
Calculation Results Outer Loadings After sales quali ty
Comfor t
comfort
0,77066 5
comfort %a
0,79324 4
comfort %b
0,71408 1
comfort %c
0,73431 2
Costs of owne rship
Expec tation s
Imag e
Loyalt y
154
Overa Sales ll qualit satisf y action
Value for mone y
Vehicle Design
Vehicle quality
comfort %d
0,62796 2
comfort %e
0,72519 6
comfort %f
0,68755 9
comfort %g
0,58257 3
comfort %h
0,58068 8
costs
0,737 651
costs% a
0,656 791
costs% b
0,636 457
costs% c
0,867 725
costs% d
0,877 533
costs% e
0,872 290
design
0,91956 0
design %a
0,89910 3
design %b
0,88175 3
design %c
0,92155 0
design %d
0,87237 6
image
0,701 045
image %a
0,704 244
image %b
0,731 372
image %c
0,798 033
image %d
0,801 905
image %e
0,571 081
image %f
0,589 476
155
image %g
0,641 581
image %h
0,757 166
loyalty1
0,858 884
loyalty2
0,849 768
loyalty3
0,832 810
loyalty4
0,745 602
oczek% d
0,819 162
oczek% f
0,812 377
oczek% g
0,859 832
sales
0,822 780
sales% a
0,811 570
sales% b
0,821 681
sales% c
0,815 307
sales% d
0,816 170
sales% e
0,829 765
sales% f
0,808 609
sales% g
0,695 434
sales% h
0,694 660
sales%i
0,702 338
sales% j
0,648 593
sat1
0,958 058
sat1a
0,955 991
sat1b
0,966 457
156
service
0,910 850
service 0,911 %a 145 service 0,931 %b 240 service 0,884 382 %c service 0,664 849 %d service 0,796 %e 449 service 0,904 %f 052 service 0,865 %g 445 value1
0,987 803
value2
0,987 937
vehqual
0,86361 8
vehqual %a
0,81259 4
vehqual %b
0,60009 8
vehqual %c
0,65982 2
vehqual %d
0,71077 3
vehqual %e
0,76927 6
vehqual %f
0,76718 0
vehqual %g
0,68202 7
157
Outer Weights
After Costs Comfo of Expectat sales rt owners ions quali hip ty comfort
0,2281 24
comfort %a
0,1977 67
comfort %b
0,1556 61
comfort %c
0,1591 24
comfort %d
0,1423 43
comfort %e
0,1489 68
comfort %f
0,1443 92
comfort %g
0,1162 75
comfort %h
0,1289 50
costs
0,1944 64
costs% a
0,1511 44
costs% b
0,1574 39
costs% c
0,2806 90
costs% d
0,2472 44
costs% e
0,2253 30
Imag e
Loyal ty
Value Vehic Vehic Overall Sales for le le satisfac qualit mone Desig qualit tion y y n y
design
0,229 616
design %a
0,198 596
design %b
0,224 507
design %c
0,232 390
design
0,227
158
%d
170
image
0,192 667
image %a
0,172 659
image %b
0,174 731
image %c
0,178 627
image %d
0,183 037
image %e
0,100 752
image %f
0,101 445
image %g
0,121 345
image %h
0,173 047
loyalty1
0,338 436
loyalty2
0,296 380
loyalty3
0,309 419
loyalty4
0,267 946
oczek% d
0,412285
oczek% f
0,352844
oczek% g
0,436863
sales
0,139 212
sales% a
0,121 809
sales% b
0,110 031
sales% c
0,113 265
sales% d
0,116 978
sales% e
0,116 967
sales%
0,119
159
f
434
sales% g
0,118 792
sales% h
0,117 647
sales%i
0,105 878
sales%j
0,117 243
sat1
0,34735 2
sat1a
0,34297 6
sat1b
0,35111 2
service
0,15 6899
service %a
0,15 6584
service %b
0,15 5714
service %c
0,13 4208
service %d
0,11 6158
service %e
0,14 2107
service %f
0,15 5768
service %g
0,13 8065
value1
0,504 755
value2
0,507 524
vehqual
0,217 690
vehqual %a
0,194 552
vehqual %b
0,127 356
vehqual %c
0,144 981
vehqual %d
0,156 144
vehqual
0,171
160
%e
400
vehqual %f
0,174 276
vehqual %g
0,154 366
Path coefficients
Aftersales Comf qualit ort y
Costs of owner ship
Expecta tions
Image
Aftersales quality
Loyal ty
Value Overall Sales for satisfac qualit mone tion y y
0,238 271
0,187 820 0,747 348
Comfort Costs of ownersh ip
0,483 602
Expectat ions Image
Vehi Vehicl cle e Desi qualit gn y
0,325 988 0,36977 4
0,167 117
Loyalty Overall satisfact ion
0,447 200
Sales quality
0,294 576
Value for money
0,29783 6
Vehicle Design
0,2247 27
Vehicle quality
0,6030 07
161
0,59171 2
0,585 819
Index values Index Values for Latent Variables LV Index Values After-sales quality
7,761776
Comfort
8,816234
Costs of ownership
7,148388
Expectations
9,386072
Image
8,388493
Loyalty
8,490361
Overall satisfaction
8,025636
Sales quality
8,973071
Value for money
7,715634
Vehicle Design
9,150832
Vehicle quality
8,710951
162
Appendix 4. Results of PLS algorithm application on the final structure of the Brand Satisfaction Model – Compact Vehicles (Path Weighting Scheme, Mean replacement algorithm for missing values, Mean 0 and Var 1 data metric, Abort Criterion 1.0E-5, Initial Weights 1.0) Quality Criteria Overview AVE
Composite Reliability R Square Cronbachs Alpha
After-sales quality
0,772868
0,964042
0,321751
0,955294
Comfort
0,615318
0,933864
0,918409
Costs of ownership 0,594624
0,896510
0,860870
Expectations
0,669758
0,858374
0,112756
0,752665
Image
0,530648
0,909568
0,710467
0,888146
Loyalty
0,710878
0,907125
0,526028
0,866536
Overall satisfaction 0,914288
0,969696
0,679328
0,953114
Sales quality
0,603427
0,943242
0,219643
0,933588
Value for money
0,975473
0,987584
0,655323
0,974863
Vehicle Design
0,838080
0,962769
Vehicle quality
0,610209
0,925904
0,951549 0,661250
0,908580
Communality Redundancy After-sales quality
0,772868
0,246238
Comfort
0,615318
Costs of ownership
0,594624
Expectations
0,669758
0,076245
Image
0,530648
0,106508
Loyalty
0,710877
0,177967
Overall satisfaction
0,914288
0,420520
Sales quality
0,603427
0,127688
Value for money
0,975473
0,169007
Vehicle Design
0,838080
Vehicle quality
0,610209
0,408075
Cross Loadings After-sales quality Comfort Costs of ownership Expectations comfort
0,368551
0,908322
0,499223
0,311158
comfort%a
0,327109
0,893459
0,499673
0,257111
comfort%b
0,361751
0,803184
0,460079
0,372541
163
comfort%c
0,302326
0,840362
0,394585
0,317704
comfort%d
0,361084
0,763051
0,354829
0,227643
comfort%e
0,199894
0,749876
0,390077
0,111858
comfort%f
0,186670
0,736981
0,451857
0,160103
comfort%g
0,363920
0,780359
0,514510
0,320726
comfort%h
0,489744
0,516300
0,317839
0,296705
costs
0,323558
0,604837
0,676427
0,161764
costs%a
0,405242
0,577586
0,702207
0,242610
costs%b
0,314904
0,393787
0,633019
0,161419
costs%c
0,578369
0,534594
0,866037
0,216390
costs%d
0,497287
0,255268
0,856442
0,156119
costs%e
0,425561
0,264512
0,856077
0,145133
design
0,287264
0,664686
0,428636
0,250960
design%a
0,300855
0,669477
0,434323
0,337540
design%b
0,411170
0,729221
0,456849
0,335446
design%c
0,305569
0,703783
0,440488
0,314366
design%d
0,285438
0,599688
0,410695
0,229690
image
0,398424
0,526238
0,205550
0,283699
image%a
0,359292
0,743258
0,435439
0,250016
image%b
0,460009
0,537668
0,341913
0,258252
image%c
0,280902
0,666360
0,312323
0,248947
image%d
0,414474
0,582726
0,439095
0,234541
image%e
0,219540
0,380064
0,393251
0,178537
image%f
0,388467
0,459375
0,465197
0,253475
image%g
0,223394
0,425230
0,294965
0,147012
image%h
0,358957
0,540787
0,333553
0,310490
loyalty1
0,458454
0,479358
0,345089
0,128059
loyalty2
0,506714
0,301610
0,311258
0,233225
loyalty3
0,536437
0,508535
0,389942
0,238747
loyalty4
0,519625
0,249811
0,284650
0,237279
oczek%d
0,275680
0,299216
0,202976
0,750044
oczek%f
0,127218
0,287645
0,121946
0,827469
oczek%g
0,257396
0,252971
0,243957
0,872927
sales
0,404769
0,442999
0,237130
0,350181
sales%a
0,381844
0,436183
0,346435
0,352979
sales%b
0,293988
0,366277
0,270342
0,351298
sales%c
0,188020
0,345695
0,203641
0,293284
sales%d
0,301803
0,314968
0,261372
0,329294
164
sales%e
0,299072
0,380650
0,269954
0,425858
sales%f
0,374332
0,489102
0,354409
0,375734
sales%g
0,444635
0,504594
0,404195
0,473086
sales%h
0,417590
0,383684
0,399467
0,375602
sales%i
0,398822
0,492094
0,310554
0,298625
sales%j
0,336892
0,336203
0,233454
0,306225
sat1
0,504947
0,564225
0,374221
0,292436
sat1a
0,535152
0,555470
0,471571
0,271302
sat1b
0,538631
0,603846
0,417269
0,262348
service
0,924823
0,369664
0,545683
0,237857
service%a
0,939795
0,322607
0,544257
0,171778
service%b
0,955505
0,380540
0,537828
0,240033
service%c
0,942639
0,345214
0,522347
0,272474
service%d
0,614823
0,323734
0,437543
0,276801
service%e
0,804694
0,411014
0,400930
0,209357
service%f
0,931314
0,435218
0,576036
0,203998
service%g
0,866021
0,315132
0,391975
0,290829
value1
0,526192
0,693837
0,444741
0,393231
value2
0,556832
0,662393
0,439332
0,412993
vehqual
0,491381
0,605398
0,433815
0,244930
vehqual%a
0,516622
0,528989
0,436933
0,261298
vehqual%b
0,290631
0,593782
0,451570
0,220136
vehqual%c
0,420471
0,661912
0,439413
0,203009
vehqual%d
0,364674
0,755923
0,457825
0,264613
vehqual%e
0,263166
0,630274
0,336632
0,184753
vehqual%f
0,417013
0,685958
0,330493
0,323697
vehqual%g
0,341722
0,654619
0,376165
0,339362
Image comfort
Loyalty
Overall satisfaction Sales quality
0,754672 0,549088
0,647363
0,438249
comfort%a 0,730202 0,493370
0,622558
0,406887
comfort%b 0,583248 0,328100
0,450903
0,467230
comfort%c 0,594069 0,392949
0,478213
0,561639
comfort%d 0,455845 0,391088
0,409851
0,487933
comfort%e 0,507905 0,290753
0,349771
0,378407
comfort%f 0,549891 0,249086
0,358570
0,245879
comfort%g 0,575915 0,286322
0,401313
0,444689
comfort%h 0,469960 0,290676
0,436499
0,337467
165
costs
0,480153 0,320673
0,490458
0,308860
costs%a
0,561985 0,384154
0,576437
0,390137
costs%b
0,279476 0,085663
0,217221
0,267759
costs%c
0,495916 0,451528
0,395165
0,373683
costs%d
0,233201 0,297785
0,234874
0,278985
costs%e
0,197189 0,233616
0,164818
0,211063
design
0,636785 0,331077
0,458280
0,471075
design%a
0,631628 0,342133
0,428524
0,403599
design%b
0,695114 0,516884
0,560308
0,480789
design%c
0,644403 0,373852
0,415969
0,372850
design%d
0,555452 0,388670
0,377373
0,332598
image
0,775949 0,568405
0,828879
0,296067
image%a
0,775879 0,485195
0,559352
0,387512
image%b
0,799332 0,460316
0,718094
0,269166
image%c
0,777067 0,275709
0,548401
0,182650
image%d
0,804154 0,503103
0,629020
0,201691
image%e
0,611620 0,337185
0,434025
0,229895
image%f
0,636556 0,228182
0,418841
0,272683
image%g
0,604099 0,120880
0,390861
0,238497
image%h
0,733552 0,467777
0,591210
0,450810
loyalty1
0,639892 0,880996
0,753689
0,249019
loyalty2
0,233753 0,825759
0,304632
0,529759
loyalty3
0,643355 0,920330
0,744416
0,348400
loyalty4
0,183991 0,733808
0,247049
0,518657
oczek%d
0,321902 0,270106
0,326801
0,276801
oczek%f
0,250976 0,151076
0,197608
0,384053
oczek%g
0,262132 0,182082
0,200995
0,469960
sales
0,347974 0,427017
0,304894
0,753118
sales%a
0,312176 0,326912
0,255750
0,796759
sales%b
0,186679 0,239523
0,213803
0,803543
sales%c
0,088585 0,156231
0,123442
0,761355
sales%d
0,174630 0,336700
0,152535
0,781378
sales%e
0,206593 0,203987
0,167502
0,848090
sales%f
0,279980 0,381372
0,260731
0,899755
sales%g
0,392661 0,442698
0,381117
0,772912
sales%h
0,391562 0,340626
0,370779
0,643172
sales%i
0,445318 0,364946
0,440641
0,760951
sales%j
0,349042 0,504882
0,430442
0,693442
166
sat1
0,797655 0,615742
0,954712
0,383589
sat1a
0,745893 0,613281
0,949013
0,336583
sat1b
0,754752 0,650965
0,964760
0,370669
service
0,486682 0,547504
0,579499
0,404216
service%a
0,402038 0,523575
0,462961
0,415584
service%b
0,453194 0,562715
0,484813
0,438358
service%c
0,382281 0,560829
0,463280
0,416586
service%d 0,308607 0,455986
0,295031
0,341641
service%e
0,493007 0,540754
0,553773
0,417783
service%f
0,486378 0,498535
0,532701
0,403423
service%g
0,350801 0,448881
0,456908
0,423829
value1
0,742745 0,549651
0,737279
0,503510
value2
0,735974 0,525044
0,778980
0,476037
vehqual
0,794575 0,607016
0,880075
0,361486
vehqual%a 0,694599 0,580618
0,795334
0,370588
vehqual%b 0,647227 0,409009
0,591498
0,328690
vehqual%c 0,552084 0,422845
0,402185
0,417867
vehqual%d 0,656758 0,462371
0,489199
0,388314
vehqual%e 0,616650 0,401348
0,602246
0,319883
vehqual%f 0,557686 0,502996
0,444612
0,488590
vehqual%g 0,657414 0,438577
0,572402
0,463896
Value for money Vehicle Design Vehicle quality comfort
0,712730
0,687441
0,794166
comfort%a
0,698607
0,645204
0,805647
comfort%b
0,601338
0,588098
0,637560
comfort%c
0,558592
0,666439
0,666711
comfort%d
0,528462
0,573384
0,592607
comfort%e
0,380165
0,554615
0,553722
comfort%f
0,402825
0,503301
0,538826
comfort%g
0,464557
0,565825
0,587421
comfort%h
0,374374
0,366866
0,465039
costs
0,454806
0,495524
0,582239
costs%a
0,504564
0,548883
0,647319
costs%b
0,330916
0,303975
0,304578
costs%c
0,415018
0,453915
0,503085
costs%d
0,234755
0,231700
0,254675
costs%e
0,187220
0,214586
0,181882
167
design
0,571507
0,900610
0,681746
design%a
0,578582
0,941631
0,649038
design%b
0,638644
0,904622
0,778274
design%c
0,519481
0,947728
0,672265
design%d
0,418929
0,880969
0,598435
image
0,700385
0,471843
0,726129
image%a
0,582580
0,717619
0,694918
image%b
0,627994
0,522354
0,717465
image%c
0,522483
0,545757
0,595983
image%d
0,548802
0,501566
0,638817
image%e
0,389807
0,374189
0,423211
image%f
0,452090
0,383334
0,485405
image%g
0,395712
0,417817
0,432659
image%h
0,586856
0,558723
0,646043
loyalty1
0,612411
0,462091
0,691900
loyalty2
0,306701
0,258431
0,348208
loyalty3
0,605995
0,453942
0,648796
loyalty4
0,185048
0,198109
0,280320
oczek%d
0,350518
0,244451
0,258087
oczek%f
0,337788
0,271976
0,283668
oczek%g
0,322329
0,276661
0,263122
sales
0,502144
0,364339
0,384655
sales%a
0,428005
0,424800
0,360741
sales%b
0,371157
0,342401
0,294043
sales%c
0,284391
0,265476
0,214434
sales%d
0,200163
0,349407
0,292422
sales%e
0,271003
0,404204
0,318533
sales%f
0,353524
0,413347
0,389772
sales%g
0,476481
0,379817
0,454920
sales%h
0,398824
0,257749
0,412825
sales%i
0,477194
0,356862
0,539603
sales%j
0,362766
0,271507
0,463181
sat1
0,764842
0,507511
0,780181
sat1a
0,718662
0,443496
0,713547
sat1b
0,718588
0,463178
0,747491
service
0,559483
0,291251
0,471896
service%a
0,478728
0,244507
0,396507
service%b
0,490427
0,291477
0,433071
168
service%c
0,454239
0,235901
0,399983
service%d
0,348076
0,288809
0,322507
service%e
0,538369
0,483845
0,565999
service%f
0,494196
0,357989
0,496701
service%g
0,467562
0,270357
0,418240
value1
0,987265
0,603624
0,755166
value2
0,988056
0,583587
0,763376
vehqual
0,731346
0,522453
0,829399
vehqual%a
0,683846
0,413127
0,774443
vehqual%b
0,556052
0,508740
0,755625
vehqual%c
0,503735
0,646114
0,730919
vehqual%d
0,536518
0,685336
0,806023
vehqual%e
0,574611
0,643254
0,816924
vehqual%f
0,585655
0,631184
0,726910
vehqual%g
0,590505
0,640185
0,802099
Total Effects After-sales quality Comfort Costs of ownership Expectations After-sales quality Comfort Costs of ownership
0,194786 0,567231
Expectations Image
0,335792
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design
0,055312
Vehicle quality
0,239539
Image After-sales quality
Loyalty
Overall satisfaction Sales quality
0,306112
0,078102
0,580080 0,277585
0,591317
Costs of ownership
0,173636
0,044302
Expectations
0,076069
Image
0,081926
Comfort
0,468661 0,126879
Loyalty Overall satisfaction
0,091289
0,444377
169
0,157373
Sales quality
0,162313
Value for money
0,181322
0,408035
Vehicle Design
0,164722 0,013495
0,020900
0,025923
Vehicle quality
0,713354 0,341360
0,727172
0,112262
Value for money Vehicle Design Vehicle quality After-sales quality
0,191411
Comfort
0,516269
Costs of ownership
0,108574
0,813173
Expectations Image
0,310951
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design
0,051221
Vehicle quality
0,634882
Outer Loadings After-sales quality Comfort Costs of ownership Expectations comfort
0,908322
comfort%a
0,893459
comfort%b
0,803184
comfort%c
0,840362
comfort%d
0,763051
comfort%e
0,749876
comfort%f
0,736981
comfort%g
0,780359
comfort%h
0,516300
costs
0,676427
costs%a
0,702207
costs%b
0,633019
costs%c
0,866037
costs%d
0,856442
costs%e
0,856077
design design%a
170
design%b design%c design%d image image%a image%b image%c image%d image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d
0,750044
oczek%f
0,827469
oczek%g
0,872927
sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service
0,924823
service%a
0,939795
service%b
0,955505
service%c
0,942639
service%d
0,614823
171
service%e
0,804694
service%f
0,931314
service%g
0,866021
value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Image
Loyalty
Overall satisfaction Sales quality
comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design design%a design%b design%c design%d image
0,775949
image%a
0,775879
image%b
0,799332
172
image%c
0,777067
image%d
0,804154
image%e
0,611620
image%f
0,636556
image%g
0,604099
image%h
0,733552
loyalty1
0,880996
loyalty2
0,825759
loyalty3
0,920330
loyalty4
0,733808
oczek%d oczek%f oczek%g sales
0,753118
sales%a
0,796759
sales%b
0,803543
sales%c
0,761355
sales%d
0,781378
sales%e
0,848090
sales%f
0,899755
sales%g
0,772912
sales%h
0,643172
sales%i
0,760951
sales%j
0,693442
sat1
0,954712
sat1a
0,949013
sat1b
0,964760
service service%a service%b service%c service%d service%e service%f service%g value1 value2 vehqual
173
vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Value for money Vehicle Design Vehicle quality comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design
0,900610
design%a
0,941631
design%b
0,904622
design%c
0,947728
design%d
0,880969
image image%a image%b image%c image%d image%e image%f image%g image%h
174
loyalty1 loyalty2 loyalty3 loyalty4 oczek%d oczek%f oczek%g sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service service%a service%b service%c service%d service%e service%f service%g value1
0,987265
value2
0,988056
vehqual
0,829399
vehqual%a
0,774443
vehqual%b
0,755625
vehqual%c
0,730919
vehqual%d
0,806023
vehqual%e
0,816924
vehqual%f
0,726910
175
vehqual%g
0,802099
Outer Weights After-sales quality Comfort Costs of ownership Expectations comfort
0,177406
comfort%a
0,179971
comfort%b
0,142422
comfort%c
0,148934
comfort%d
0,132380
comfort%e
0,123694
comfort%f
0,120367
comfort%g
0,131222
comfort%h
0,103884
costs
0,162277
costs%a
0,203244
costs%b
0,157936
costs%c
0,290074
costs%d
0,249408
costs%e
0,213435
design design%a design%b design%c design%d image image%a image%b image%c image%d image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d
0,357005
176
oczek%f
0,396709
oczek%g
0,462771
sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service
0,157215
service%a
0,147306
service%b
0,151640
service%c
0,146665
service%d
0,118517
service%e
0,140880
service%f
0,149264
service%g
0,124452
value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Image
Loyalty
Overall satisfaction Sales quality
comfort comfort%a
177
comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design design%a design%b design%c design%d image
0,185528
image%a
0,173121
image%b
0,176278
image%c
0,151102
image%d
0,156924
image%e
0,109200
image%f
0,127162
image%g
0,110384
image%h
0,167391
loyalty1
0,339297
loyalty2
0,243649
loyalty3
0,361820
loyalty4
0,227432
oczek%d oczek%f oczek%g sales
0,131173
sales%a
0,114939
sales%b
0,100061
sales%c
0,076234
178
sales%d
0,112523
sales%e
0,106877
sales%f
0,127922
sales%g
0,154808
sales%h
0,121097
sales%i
0,111994
sales%j
0,136657
sat1
0,355462
sat1a
0,338477
sat1b
0,351815
service service%a service%b service%c service%d service%e service%f service%g value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Value for money Vehicle Design Vehicle quality comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g
179
comfort%h costs costs%a costs%b costs%c costs%d costs%e design
0,219799
design%a
0,218019
design%b
0,239932
design%c
0,222428
design%d
0,191725
image image%a image%b image%c image%d image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d oczek%f oczek%g sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i
180
sales%j sat1 sat1a sat1b service service%a service%b service%c service%d service%e service%f service%g value1
0,498178
value2
0,514309
vehqual
0,193525
vehqual%a
0,173547
vehqual%b
0,153884
vehqual%c
0,136810
vehqual%d
0,157488
vehqual%e
0,156039
vehqual%f
0,146490
vehqual%g
0,159477
Index Values Results Index Values for Latent Variables LV Index Values After-sales quality
7,707890
Comfort
8,739694
Costs of ownership
7,066291
Expectations
9,291980
Image
8,389854
Loyalty
8,469529
Overall satisfaction
7,889300
Sales quality
8,960235
Value for money
7,690175
Vehicle Design
9,006335
Vehicle quality
8,632728
181
Appendix 5. Results of PLS algorithm application on the final structure of the Brand Satisfaction Model – Mid-size vehicles (Path Weighting Scheme, Mean replacement algorithm for missing values, Mean 0 and Var 1 data metric, Abort Criterion 1.0E-5, Initial Weights 1.0) PLS Quality Criteria Overview AVE
Composite Reliability R Square Cronbachs Alpha
After-sales quality
0,705925
0,949731
0,207406
0,937509
Comfort
0,477433
0,889969
0,859571
Costs of ownership 0,605441
0,899726
0,867366
Expectations
0,721923
0,886158
0,315686
0,808046
Image
0,435126
0,871934
0,434305
0,838482
Loyalty
0,597603
0,855461
0,629035
0,780341
Overall satisfaction 0,881843
0,957246
0,681052
0,932998
Sales quality
0,539511
0,927087
0,116399
0,912917
Value for money
0,963072
0,981189
0,639334
0,961658
Vehicle Design
0,748316
0,936884
Vehicle quality
0,433883
0,856771
0,915850 0,497074
Communality Redundancy After-sales quality
0,705925
0,143231
Comfort
0,477433
Costs of ownership
0,605441
Expectations
0,721923
0,227853
Image
0,435126
0,097289
Loyalty
0,597602
0,109489
Overall satisfaction
0,881843
0,157824
Sales quality
0,539511
0,062490
Value for money
0,963072
0,204720
Vehicle Design
0,748316
Vehicle quality
0,433883
0,213887
182
0,807901
Cross Loadings After-sales quality Comfort Costs of ownership Expectations comfort
0,308752
0,783414
0,412866
0,429905
comfort%a
0,392647
0,673697
0,492601
0,305820
comfort%b
0,325933
0,576920
0,253288
0,376092
comfort%c
0,324076
0,634751
0,258848
0,373511
comfort%d
0,368962
0,751996
0,428558
0,319650
comfort%e
0,365378
0,821899
0,544734
0,305516
comfort%f
0,217808
0,745449
0,403458
0,226113
comfort%g
0,201183
0,565853
0,306022
0,252304
comfort%h
0,135515
0,613711
0,254531
0,201124
costs
0,327053
0,508553
0,774391
0,226708
costs%a
0,288790
0,471841
0,660889
0,264715
costs%b
0,139414
0,340539
0,556635
0,140856
costs%c
0,429941
0,464214
0,827629
0,200236
costs%d
0,404361
0,443280
0,911505
0,195620
costs%e
0,421943
0,385126
0,877803
0,144413
design
0,258299
0,523393
0,363193
0,411304
design%a
0,126542
0,523524
0,289120
0,383848
design%b
0,323992
0,522699
0,407946
0,284960
design%c
0,235131
0,563868
0,267012
0,408389
design%d
0,265372
0,572632
0,348402
0,330201
image
0,394457
0,436110
0,370251
0,295115
image%a
0,045427
0,400365
0,290620
0,352588
image%b
0,182039
0,498763
0,359325
0,442809
image%c
0,197907
0,520551
0,322750
0,489439
image%d
0,457271
0,503274
0,375328
0,506104
image%e
0,118870
0,259327
0,161160
0,232050
image%f
0,128174
0,313669
0,189707
0,317089
image%g
0,212006
0,373238
0,247957
0,297562
image%h
0,143441
0,360514
0,406030
0,290159
loyalty1
0,449200
0,603369
0,480556
0,221409
loyalty2
0,476286
0,419578
0,295457
0,200192
loyalty3
0,318066
0,399337
0,475625
0,103996
loyalty4
0,364914
0,328934
0,209691
0,114329
oczek%d
0,136680
0,462026
0,196352
0,874321
oczek%f
0,069130
0,268173
0,224955
0,825496
oczek%g
0,031583
0,399661
0,206882
0,848461
183
sales
0,290037
0,456063
0,276385
0,238430
sales%a
0,206820
0,436130
0,329059
0,298692
sales%b
0,158164
0,325877
0,115696
0,267963
sales%c
0,288450
0,479698
0,407889
0,315613
sales%d
0,218621
0,554479
0,372548
0,333404
sales%e
0,162124
0,443950
0,286325
0,305336
sales%f
0,140842
0,287470
0,156298
0,204494
sales%g
0,275020
0,530494
0,280986
0,262864
sales%h
0,363254
0,401764
0,260901
0,140518
sales%i
0,310068
0,466105
0,345423
0,158220
sales%j
0,148726
0,390157
0,213028
0,179351
sat1
0,429349
0,502421
0,446556
0,201576
sat1a
0,415239
0,613185
0,475102
0,294473
sat1b
0,329843
0,546482
0,436096
0,378687
service
0,934754
0,388721
0,393166
0,091033
service%a
0,901923
0,366785
0,449997
0,099025
service%b
0,938874
0,386548
0,403345
0,089459
service%c
0,769283
0,278074
0,204724
0,114576
service%d
0,610486
0,300189
0,356267
0,021815
service%e
0,751032
0,388057
0,428134
0,071878
service%f
0,894927
0,425357
0,406080
0,095758
service%g
0,865595
0,336381
0,383524
0,026495
value1
0,555860
0,604494
0,565361
0,333318
value2
0,534136
0,570017
0,583718
0,346989
vehqual
0,411798
0,537057
0,361586
0,224805
vehqual%a
0,448304
0,461375
0,481538
0,191582
vehqual%b
0,144237
0,265801
0,206763
0,029286
vehqual%c
0,241615
0,333578
0,111133
0,245830
vehqual%d
0,379203
0,438931
0,361180
0,197741
vehqual%e
0,164634
0,586594
0,318908
0,324709
vehqual%f
0,326688
0,467251
0,527871
0,254507
vehqual%g
0,326000
0,566660
0,637906
0,308630
Image comfort
Loyalty
Overall satisfaction Sales quality
0,499146 0,450938
0,493559
0,408250
comfort%a 0,469256 0,383535
0,425850
0,416263
comfort%b 0,442506 0,305192
0,317228
0,444659
comfort%c 0,334085 0,275475
0,424768
0,357509
184
comfort%d 0,426097 0,524615
0,420760
0,488123
comfort%e 0,553928 0,447311
0,382615
0,385671
comfort%f 0,426195 0,479140
0,466926
0,439320
comfort%g 0,411985 0,354294
0,376957
0,338288
comfort%h 0,418178 0,367472
0,340569
0,426516
costs
0,465327 0,457412
0,447024
0,375072
costs%a
0,396150 0,476783
0,445455
0,332420
costs%b
0,251541 0,273421
0,299824
0,164197
costs%c
0,436205 0,372556
0,372110
0,325408
costs%d
0,354102 0,396203
0,397737
0,315469
costs%e
0,332908 0,358656
0,335459
0,284766
design
0,501816 0,369159
0,488219
0,472939
design%a
0,362796 0,348715
0,283510
0,463244
design%b
0,455043 0,405743
0,530696
0,422975
design%c
0,482972 0,437275
0,336702
0,505521
design%d
0,514930 0,405844
0,455662
0,386809
image
0,612705 0,580233
0,738605
0,311307
image%a
0,558133 0,243627
0,224097
0,343926
image%b
0,699180 0,454425
0,431886
0,456570
image%c
0,764794 0,344335
0,378394
0,456332
image%d
0,806129 0,450317
0,396707
0,513104
image%e
0,509472 0,125331
0,137816
0,067978
image%f
0,654318 0,169139
0,211457
0,320316
image%g
0,655640 0,272753
0,342951
0,413105
image%h
0,622939 0,251595
0,217031
0,294143
loyalty1
0,603379 0,830309
0,757562
0,487273
loyalty2
0,334404 0,770412
0,268209
0,601662
loyalty3
0,424506 0,785952
0,671154
0,370646
loyalty4
0,200314 0,699817
0,218398
0,486825
oczek%d
0,460332 0,186505
0,258695
0,350156
oczek%f
0,477104 0,173191
0,302937
0,159021
oczek%g
0,495491 0,181525
0,238027
0,339963
sales
0,471630 0,554155
0,370551
0,818970
sales%a
0,401170 0,537192
0,307661
0,782944
sales%b
0,355684 0,321913
0,223589
0,780680
sales%c
0,470640 0,598582
0,435024
0,821675
sales%d
0,504127 0,472071
0,283816
0,816178
sales%e
0,426730 0,429376
0,207567
0,792365
185
sales%f
0,229444 0,379938
0,119058
0,672968
sales%g
0,491701 0,355670
0,297747
0,638617
sales%h
0,405922 0,507686
0,376317
0,606046
sales%i
0,445724 0,428493
0,316544
0,701865
sales%j
0,274575 0,271176
0,258624
0,593031
sat1
0,506581 0,627164
0,936009
0,378612
sat1a
0,542748 0,619161
0,944008
0,373638
sat1b
0,557773 0,625754
0,937158
0,389331
service
0,337991 0,501633
0,390205
0,288323
service%a
0,340608 0,460621
0,401281
0,278644
service%b 0,362982 0,525353
0,408137
0,315646
service%c
0,237963 0,408676
0,163748
0,278043
service%d 0,296633 0,346311
0,213807
0,236343
service%e
0,250121 0,356742
0,389503
0,220560
service%f
0,290049 0,470631
0,424604
0,277936
service%g 0,199636 0,389397
0,330235
0,266995
value1
0,637283 0,644650
0,635171
0,370359
value2
0,629540 0,658703
0,674506
0,403114
vehqual
0,524711 0,563923
0,792004
0,432705
vehqual%a 0,443824 0,543471
0,668893
0,160704
vehqual%b 0,245626 0,220350
0,335432
0,094903
vehqual%c 0,369118 0,330209
0,448417
0,356268
vehqual%d 0,379023 0,414369
0,534652
0,275173
vehqual%e 0,347887 0,377637
0,408615
0,349617
vehqual%f 0,339184 0,425700
0,467986
0,289904
vehqual%g 0,518538 0,556644
0,532064
0,355763
Value for money Vehicle Design Vehicle quality comfort
0,475532
0,472732
0,560491
comfort%a
0,519348
0,382030
0,518859
comfort%b
0,336533
0,371001
0,400768
comfort%c
0,286365
0,431626
0,458778
comfort%d
0,444658
0,615776
0,553677
comfort%e
0,519851
0,485424
0,537796
comfort%f
0,411389
0,447878
0,508234
comfort%g
0,299135
0,255572
0,384356
comfort%h
0,373593
0,369247
0,417634
costs
0,449348
0,422911
0,499244
186
costs%a
0,457795
0,221919
0,458798
costs%b
0,414334
0,086670
0,298991
costs%c
0,536476
0,379086
0,512281
costs%d
0,488924
0,341875
0,506274
costs%e
0,429455
0,267497
0,457530
design
0,356722
0,908290
0,548997
design%a
0,260709
0,813503
0,385783
design%b
0,369991
0,889411
0,597482
design%c
0,291826
0,867795
0,424100
design%d
0,334324
0,843018
0,471438
image
0,668747
0,339963
0,693426
image%a
0,311555
0,318575
0,417938
image%b
0,519289
0,316762
0,480622
image%c
0,449668
0,493586
0,409509
image%d
0,484416
0,519980
0,432793
image%e
0,221357
0,201947
0,166161
image%f
0,242265
0,327241
0,188118
image%g
0,292835
0,321140
0,278872
image%h
0,369763
0,258330
0,286404
loyalty1
0,735828
0,521314
0,731981
loyalty2
0,352228
0,276390
0,327543
loyalty3
0,572570
0,359737
0,631823
loyalty4
0,283854
0,171784
0,279171
oczek%d
0,313367
0,356669
0,312039
oczek%f
0,375863
0,166838
0,297116
oczek%g
0,210968
0,512143
0,270074
sales
0,367428
0,305614
0,393529
sales%a
0,267069
0,350798
0,336866
sales%b
0,166184
0,324944
0,225457
sales%c
0,343287
0,549620
0,473235
sales%d
0,304071
0,647422
0,382309
sales%e
0,283773
0,355637
0,256205
sales%f
0,161354
0,262864
0,185119
sales%g
0,274446
0,311356
0,377426
sales%h
0,364066
0,351201
0,334936
sales%i
0,361275
0,356044
0,331316
sales%j
0,238279
0,258994
0,219035
sat1
0,605676
0,449900
0,769066
187
sat1a
0,652056
0,479701
0,761919
sat1b
0,622555
0,454056
0,775451
service
0,560380
0,248188
0,458067
service%a
0,564136
0,239262
0,467364
service%b
0,539122
0,262069
0,454964
service%c
0,356811
0,106547
0,238792
service%d
0,303684
0,201607
0,264684
service%e
0,437300
0,307401
0,389073
service%f
0,521502
0,262279
0,484615
service%g
0,360624
0,267513
0,406240
value1
0,981114
0,349506
0,720335
value2
0,981610
0,387951
0,709617
vehqual
0,568566
0,415946
0,784338
vehqual%a
0,591599
0,327433
0,759266
vehqual%b
0,299595
0,203319
0,471343
vehqual%c
0,371766
0,310619
0,541233
vehqual%d
0,491295
0,546857
0,708736
vehqual%e
0,378512
0,362391
0,596198
vehqual%f
0,503552
0,258179
0,629480
vehqual%g
0,552686
0,501805
0,714346
Total Effects After-sales quality Comfort Costs of ownership Expectations After-sales quality Comfort Costs of ownership
0,179940 0,455418
Expectations Image
0,561859
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design
0,160371
Vehicle quality
0,255221
Image After-sales quality
Loyalty 0,239531
Overall satisfaction Sales quality 0,037155
188
Comfort
0,320258 0,256940
0,559518
Costs of ownership
0,109087
0,016921
Expectations
0,129261
Image
0,091344
0,061391
0,341173 0,044817
0,191691
Loyalty Overall satisfaction
0,417647
Sales quality
0,378873
Value for money
0,063140
0,151180
Vehicle Design
0,285429 0,026072
0,012792
0,054714
Vehicle quality
0,454244 0,364436
0,793604
0,087075
Value for money Vehicle Design Vehicle quality After-sales quality
0,245768
Comfort
0,396431
Costs of ownership
0,111927
0,705034
Expectations Image
0,296450
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design
0,084615
Vehicle quality
0,562286
Outer Loadings After-sales quality Comfort Costs of ownership Expectations comfort
0,783414
comfort%a
0,673697
comfort%b
0,576920
comfort%c
0,634751
comfort%d
0,751996
comfort%e
0,821899
comfort%f
0,745449
comfort%g
0,565853
comfort%h
0,613711
costs
0,774391
costs%a
0,660889
costs%b
0,556635
189
costs%c
0,827629
costs%d
0,911505
costs%e
0,877803
design design%a design%b design%c design%d image image%a image%b image%c image%d image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d
0,874321
oczek%f
0,825496
oczek%g
0,848461
sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b
190
service
0,934754
service%a
0,901923
service%b
0,938874
service%c
0,769283
service%d
0,610486
service%e
0,751032
service%f
0,894927
service%g
0,865595
value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Image
Loyalty
Overall satisfaction Sales quality
comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design design%a design%b
191
design%c design%d image
0,612705
image%a
0,558133
image%b
0,699180
image%c
0,764794
image%d
0,806129
image%e
0,509472
image%f
0,654318
image%g
0,655640
image%h
0,622939
loyalty1
0,830309
loyalty2
0,770412
loyalty3
0,785952
loyalty4
0,699817
oczek%d oczek%f oczek%g sales
0,818970
sales%a
0,782944
sales%b
0,780680
sales%c
0,821675
sales%d
0,816178
sales%e
0,792365
sales%f
0,672968
sales%g
0,638617
sales%h
0,606046
sales%i
0,701865
sales%j
0,593031
sat1
0,936009
sat1a
0,944008
sat1b
0,937158
service service%a service%b service%c service%d service%e
192
service%f service%g value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Value for money Vehicle Design Vehicle quality comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design
0,908290
design%a
0,813503
design%b
0,889411
design%c
0,867795
design%d
0,843018
image image%a image%b image%c
193
image%d image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d oczek%f oczek%g sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service service%a service%b service%c service%d service%e service%f service%g value1
0,981114
value2
0,981610
vehqual
0,784338
vehqual%a
0,759266
194
vehqual%b
0,471343
vehqual%c
0,541233
vehqual%d
0,708736
vehqual%e
0,596198
vehqual%f
0,629480
vehqual%g
0,714346
Path Coefficients After-sales quality Comfort Costs of ownership Expectations After-sales quality Comfort Costs of ownership
0,455418
Expectations Image
0,561859
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design Vehicle quality
Image After-sales quality
Loyalty
Overall satisfaction Sales quality
0,224013
Comfort Costs of ownership Expectations
0,341173
Image Loyalty Overall satisfaction
0,417647
Sales quality
0,378873
Value for money
0,151180
Vehicle Design
0,285429
Vehicle quality
0,454244
0,708597
Value for money Vehicle Design Vehicle quality After-sales quality
0,245768
195
Comfort
0,705034
Costs of ownership Expectations Image
0,296450
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design Vehicle quality
0,427625
Outer Weights After-sales quality Comfort Costs of ownership Expectations comfort
0,185464
comfort%a
0,171688
comfort%b
0,132612
comfort%c
0,151808
comfort%d
0,183209
comfort%e
0,177954
comfort%f
0,168172
comfort%g
0,127182
comfort%h
0,138193
costs
0,202320
costs%a
0,178649
costs%b
0,086243
costs%c
0,265967
costs%d
0,250143
costs%e
0,261020
design design%a design%b design%c design%d image image%a image%b image%c image%d
196
image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d
0,406008
oczek%f
0,346104
oczek%g
0,423485
sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service
0,170441
service%a
0,171948
service%b
0,171614
service%c
0,114346
service%d
0,115953
service%e
0,141448
service%f
0,163219
service%g
0,131030
value1 value2 vehqual vehqual%a vehqual%b
197
vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Image
Loyalty
Overall satisfaction Sales quality
comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design design%a design%b design%c design%d image
0,231491
image%a
0,155932
image%b
0,204714
image%c
0,204584
image%d
0,216027
image%e
0,093189
image%f
0,117729
image%g
0,131753
image%h
0,138858
loyalty1
0,406386
loyalty2
0,301708
198
loyalty3
0,332320
loyalty4
0,241415
oczek%d oczek%f oczek%g sales
0,145619
sales%a
0,149058
sales%b
0,099722
sales%c
0,164081
sales%d
0,139278
sales%e
0,126925
sales%f
0,104634
sales%g
0,106300
sales%h
0,124301
sales%i
0,109543
sales%j
0,078584
sat1
0,354658
sat1a
0,353523
sat1b
0,356725
service service%a service%b service%c service%d service%e service%f service%g value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
199
Value for money Vehicle Design Vehicle quality comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design
0,249801
design%a
0,180597
design%b
0,226517
design%c
0,240420
design%d
0,256329
image image%a image%b image%c image%d image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d oczek%f oczek%g sales
200
sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service service%a service%b service%c service%d service%e service%f service%g value1
0,506136
value2
0,512854
vehqual
0,245772
vehqual%a
0,219700
vehqual%b
0,115829
vehqual%c
0,153286
vehqual%d
0,186449
vehqual%e
0,172461
vehqual%f
0,179454
vehqual%g
0,216891
201
Index Values Results Index Values for Latent Variables LV Index Values After-sales quality
8,053256
Comfort
8,736349
Costs of ownership
7,043332
Expectations
9,275809
Image
8,467164
Loyalty
8,736364
Overall satisfaction
8,274511
Sales quality
9,021823
Value for money
7,960828
Vehicle Design
9,138596
Vehicle quality
8,890804
202
Appendix 6. Results of PLS algorithm application on the final structure of the Brand Satisfaction Model – Full-size and large vehicles (Path Weighting Scheme, Mean replacement algorithm for missing values, Mean 0 and Var 1 data metric, Abort Criterion 1.0E-5, Initial Weights 1.0) PLS Quality Criteria Overview AVE
Composite Reliability R Square Cronbachs Alpha
After-sales quality
0,756338
0,961199
0,220759
0,953577
Comfort
0,417075
0,862975
0,825457
Costs of ownership 0,631850
0,910180
0,882212
Expectations
0,688444
0,868744
0,101650
0,772819
Image
0,515331
0,903972
0,540174
0,881729
Loyalty
0,683263
0,895821
0,668624
0,844064
Overall satisfaction 0,939084
0,978835
0,772297
0,967552
Sales quality
0,631180
0,948994
0,069712
0,939794
Value for money
0,980902
0,990359
0,752208
0,980530
Vehicle Design
0,821036
0,958165
Vehicle quality
0,556229
0,906952
0,945447 0,575419
Communality Redundancy After-sales quality
0,756338
0,165511
Comfort
0,417075
Costs of ownership
0,631850
Expectations
0,688444
0,069946
Image
0,515331
0,094646
Loyalty
0,683262
0,132700
Overall satisfaction
0,939084
0,336551
Sales quality
0,631180
0,044446
Value for money
0,980902
0,159029
Vehicle Design
0,821036
Vehicle quality
0,556229
0,321525
203
0,880875
Cross Loadings After-sales quality Comfort Costs of ownership Expectations comfort
0,486584
0,701444
0,358895
0,302654
comfort%a
0,379716
0,785724
0,348787
0,353190
comfort%b
0,338939
0,714064
0,297551
0,358419
comfort%c
0,236001
0,682580
0,256100
0,385769
comfort%d
0,247213
0,451548
0,142889
0,218285
comfort%e
0,382478
0,659463
0,353861
0,333402
comfort%f
0,366883
0,606493
0,355257
0,245082
comfort%g
0,284473
0,527113
0,322851
0,206239
comfort%h
0,274856
0,619692
0,307845
0,255494
costs
0,386846
0,456552
0,776274
0,233476
costs%a
0,165649
0,309901
0,637468
0,145489
costs%b
0,332093
0,386249
0,678024
0,197377
costs%c
0,469630
0,416694
0,893648
0,193685
costs%d
0,413690
0,377911
0,869240
0,125562
costs%e
0,367094
0,313662
0,876489
0,114905
design
0,172556
0,587421
0,245510
0,438682
design%a
0,145712
0,491685
0,188848
0,531135
design%b
0,174418
0,556224
0,115859
0,410043
design%c
0,180344
0,578444
0,303586
0,389941
design%d
0,261063
0,625606
0,359490
0,428830
image
0,399395
0,535569
0,508721
0,175029
image%a
0,336038
0,550161
0,286933
0,320668
image%b
0,351798
0,621586
0,252952
0,203443
image%c
0,440366
0,603556
0,382295
0,235845
image%d
0,418318
0,641452
0,401432
0,291397
image%e
0,254347
0,425490
0,328220
0,135004
image%f
0,270540
0,356726
0,349798
0,143900
image%g
0,376664
0,533043
0,279515
0,289664
image%h
0,403120
0,599637
0,366024
0,229804
loyalty1
0,512689
0,612642
0,467497
0,195850
loyalty2
0,484392
0,495551
0,440663
0,086442
loyalty3
0,476453
0,562117
0,384430
0,174686
loyalty4
0,464469
0,405859
0,247259
0,150493
oczek%d
0,217163
0,411070
0,122880
0,790053
oczek%f
0,235346
0,323431
0,195756
0,826712
oczek%g
0,153565
0,410431
0,206856
0,870456
204
sales
0,370460
0,481707
0,265872
0,196862
sales%a
0,368645
0,430058
0,259101
0,233853
sales%b
0,429625
0,436230
0,227805
0,316616
sales%c
0,389417
0,429925
0,281320
0,242127
sales%d
0,283848
0,359523
0,277888
0,158366
sales%e
0,331734
0,418245
0,265890
0,229892
sales%f
0,358292
0,418498
0,159242
0,277565
sales%g
0,425825
0,444385
0,321235
0,136097
sales%h
0,362657
0,443438
0,309245
0,186311
sales%i
0,369058
0,451953
0,334545
0,197408
sales%j
0,403004
0,427782
0,268307
0,112262
sat1
0,356390
0,610812
0,468097
0,221811
sat1a
0,496962
0,581794
0,476182
0,255537
sat1b
0,446464
0,601986
0,487976
0,259751
service
0,891576
0,431957
0,402760
0,176200
service%a
0,894955
0,446260
0,378132
0,148404
service%b
0,912642
0,428400
0,362681
0,182187
service%c
0,900188
0,422797
0,352342
0,294909
service%d
0,784663
0,404870
0,370116
0,180126
service%e
0,812486
0,517402
0,475678
0,265185
service%f
0,885154
0,534140
0,510663
0,217410
service%g
0,867337
0,517744
0,410374
0,235519
value1
0,587218
0,660415
0,555849
0,220129
value2
0,543788
0,656576
0,530888
0,219318
vehqual
0,456868
0,667845
0,444476
0,245849
vehqual%a
0,511586
0,587148
0,484406
0,219857
vehqual%b
0,293151
0,425623
0,280357
0,067521
vehqual%c
0,365287
0,577256
0,374623
0,218713
vehqual%d
0,406049
0,577041
0,279144
0,257162
vehqual%e
0,402442
0,538878
0,339559
0,202613
vehqual%f
0,364311
0,626742
0,344546
0,217115
vehqual%g
0,210936
0,521364
0,276647
0,220795
Image comfort
Loyalty
Overall satisfaction Sales quality
0,662560 0,695889
0,655821
0,337419
comfort%a 0,665404 0,483882
0,543719
0,445745
comfort%b 0,508045 0,353709
0,346294
0,531378
comfort%c 0,470020 0,374716
0,291116
0,472384
205
comfort%d 0,198086 0,135793
0,276695
0,200980
comfort%e 0,471679 0,326035
0,362254
0,225314
comfort%f 0,425086 0,387703
0,319339
0,305911
comfort%g 0,383435 0,270345
0,281171
0,274535
comfort%h 0,462597 0,355790
0,260550
0,329058
costs
0,494821 0,430027
0,436368
0,383500
costs%a
0,329866 0,257025
0,285571
0,331358
costs%b
0,458229 0,355972
0,319883
0,264686
costs%c
0,378019 0,374106
0,461891
0,213744
costs%d
0,374292 0,401561
0,450663
0,251026
costs%e
0,315602 0,381746
0,347942
0,242843
design
0,469513 0,392449
0,357143
0,458396
design%a
0,349744 0,276832
0,220791
0,408554
design%b
0,435562 0,347048
0,272388
0,473404
design%c
0,495616 0,396902
0,344947
0,372807
design%d
0,526840 0,395221
0,338722
0,391876
image
0,703457 0,561065
0,774887
0,292171
image%a
0,707365 0,409327
0,459711
0,287959
image%b
0,713735 0,426688
0,367014
0,348544
image%c
0,824082 0,566679
0,469841
0,428460
image%d
0,800597 0,590742
0,503559
0,389015
image%e
0,583350 0,383945
0,296413
0,426618
image%f
0,553195 0,369520
0,218649
0,404790
image%g
0,696339 0,434967
0,362858
0,439194
image%h
0,825874 0,622906
0,529532
0,480704
loyalty1
0,693729 0,858880
0,708885
0,365961
loyalty2
0,525380 0,885788
0,514963
0,649274
loyalty3
0,648846 0,788246
0,631226
0,254410
loyalty4
0,417124 0,767739
0,405118
0,726514
oczek%d
0,254600 0,236988
0,285617
0,241158
oczek%f
0,264277 0,092023
0,116269
0,188079
oczek%g
0,274213 0,120435
0,221913
0,225251
sales
0,416742 0,610626
0,306903
0,876228
sales%a
0,341776 0,456658
0,227086
0,849399
sales%b
0,410572 0,463508
0,231161
0,855927
sales%c
0,414405 0,455673
0,249660
0,850556
sales%d
0,341424 0,458515
0,209312
0,845315
sales%e
0,387441 0,508878
0,228113
0,842762
206
sales%f
0,482676 0,473198
0,217528
0,823817
sales%g
0,483542 0,439269
0,219931
0,669414
sales%h
0,461684 0,503751
0,251426
0,776448
sales%i
0,408678 0,417268
0,256908
0,664272
sales%j
0,448981 0,521209
0,317422
0,633991
sat1
0,627899 0,667030
0,966102
0,308483
sat1a
0,615213 0,671882
0,964621
0,290163
sat1b
0,629980 0,642692
0,976425
0,309832
service
0,412514 0,540259
0,382202
0,378064
service%a
0,477303 0,572075
0,410383
0,402454
service%b
0,446144 0,554400
0,436812
0,365524
service%c
0,449371 0,487477
0,333232
0,443502
service%d
0,425084 0,480436
0,328529
0,418970
service%e
0,443966 0,423765
0,400220
0,408544
service%f
0,459418 0,489041
0,412027
0,445882
service%g
0,441900 0,520552
0,394840
0,403760
value1
0,659258 0,718975
0,806262
0,358275
value2
0,661473 0,704921
0,800878
0,335814
vehqual
0,661258 0,695790
0,938753
0,332606
vehqual%a 0,564415 0,614300
0,869479
0,239796
vehqual%b 0,359425 0,243625
0,299708
0,204830
vehqual%c 0,476505 0,424111
0,552200
0,373482
vehqual%d 0,509388 0,385121
0,477798
0,275832
vehqual%e 0,561994 0,591955
0,681101
0,269071
vehqual%f 0,569625 0,596753
0,711340
0,317015
vehqual%g 0,465631 0,456070
0,400253
0,246163
Value for money Vehicle Design Vehicle quality comfort
0,664926
0,444845
0,741440
comfort%a
0,551400
0,519356
0,624199
comfort%b
0,394224
0,482644
0,482133
comfort%c
0,359097
0,564153
0,424692
comfort%d
0,233716
0,260167
0,365169
comfort%e
0,390681
0,315698
0,431073
comfort%f
0,357687
0,333296
0,430835
comfort%g
0,295682
0,245100
0,289719
comfort%h
0,395963
0,433617
0,364341
costs
0,513348
0,330894
0,466261
207
costs%a
0,328155
0,342579
0,312130
costs%b
0,439696
0,263282
0,399437
costs%c
0,480751
0,162574
0,403281
costs%d
0,443364
0,167005
0,408087
costs%e
0,387377
0,169018
0,297152
design
0,340317
0,951949
0,465140
design%a
0,215935
0,901079
0,333651
design%b
0,316908
0,849767
0,411623
design%c
0,368710
0,933445
0,463358
design%d
0,345271
0,890844
0,436989
image
0,585685
0,184422
0,673724
image%a
0,510536
0,336713
0,512497
image%b
0,446873
0,428563
0,473477
image%c
0,562427
0,483582
0,585734
image%d
0,562297
0,451074
0,607668
image%e
0,292138
0,289659
0,314508
image%f
0,263021
0,296337
0,218211
image%g
0,361392
0,345050
0,374045
image%h
0,555650
0,466454
0,593347
loyalty1
0,749828
0,376810
0,730284
loyalty2
0,561475
0,346122
0,538444
loyalty3
0,690450
0,302772
0,640725
loyalty4
0,384183
0,310550
0,395111
oczek%d
0,231454
0,439052
0,301536
oczek%f
0,145876
0,337763
0,162649
oczek%g
0,171937
0,411157
0,227419
sales
0,313214
0,370407
0,315818
sales%a
0,234957
0,316560
0,241437
sales%b
0,281869
0,379559
0,278850
sales%c
0,273477
0,398764
0,277198
sales%d
0,231830
0,407975
0,236709
sales%e
0,266370
0,376516
0,288328
sales%f
0,283630
0,435985
0,292145
sales%g
0,302195
0,364573
0,361965
sales%h
0,247126
0,367063
0,284307
sales%i
0,287436
0,370262
0,355627
sales%j
0,333372
0,255317
0,372273
sat1
0,766175
0,322736
0,827692
208
sat1a
0,778694
0,353568
0,827803
sat1b
0,813528
0,327862
0,867137
service
0,523042
0,156771
0,439373
service%a
0,555610
0,142634
0,470256
service%b
0,553706
0,168962
0,474773
service%c
0,447946
0,254798
0,387653
service%d
0,388077
0,217009
0,358713
service%e
0,480422
0,173475
0,462421
service%f
0,528232
0,196900
0,498958
service%g
0,471426
0,170463
0,458337
value1
0,990470
0,360181
0,841739
value2
0,990339
0,347947
0,844406
vehqual
0,832742
0,355462
0,907941
vehqual%a
0,750984
0,304548
0,858737
vehqual%b
0,403120
0,298963
0,531512
vehqual%c
0,554009
0,330215
0,691101
vehqual%d
0,499262
0,324846
0,664484
vehqual%e
0,696997
0,344251
0,788866
vehqual%f
0,732261
0,429057
0,837131
vehqual%g
0,471919
0,494689
0,602734
Total Effects After-sales quality Comfort Costs of ownership Expectations After-sales quality Comfort Costs of ownership
0,144802 0,469850
Expectations Image
0,318826
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design
0,072960
Vehicle quality
0,190889
Image After-sales quality Comfort
Loyalty
Overall satisfaction Sales quality
0,220640
0,043816
0,454172 0,318870
0,639516
209
0,038232
Costs of ownership
0,103668
Expectations
0,097741
Image
0,041322
0,020587 0,264030 0,021322
0,084180
Loyalty Overall satisfaction
0,476481
Sales quality
0,370188
Value for money
0,125661
0,263727
Vehicle Design
0,228841 0,009456
0,004879
0,019264
Vehicle quality
0,598727 0,420360
0,843061
0,050401
Value for money Vehicle Design Vehicle quality After-sales quality
0,166142
Comfort
0,574451
Costs of ownership
0,078062
0,758564
Expectations Image
0,080849
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design
0,018501
Vehicle quality
0,757288
Outer Loadings After-sales quality Comfort Costs of ownership Expectations comfort
0,701444
comfort%a
0,785724
comfort%b
0,714064
comfort%c
0,682580
comfort%d
0,451548
comfort%e
0,659463
comfort%f
0,606493
comfort%g
0,527113
comfort%h
0,619692
costs
0,776274
costs%a
0,637468
costs%b
0,678024
costs%c
0,893648
210
costs%d
0,869240
costs%e
0,876489
design design%a design%b design%c design%d image image%a image%b image%c image%d image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d
0,790053
oczek%f
0,826712
oczek%g
0,870456
sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service
0,891576
211
service%a
0,894955
service%b
0,912642
service%c
0,900188
service%d
0,784663
service%e
0,812486
service%f
0,885154
service%g
0,867337
value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Image
Loyalty
Overall satisfaction Sales quality
comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design design%a design%b design%c
212
design%d image
0,703457
image%a
0,707365
image%b
0,713735
image%c
0,824082
image%d
0,800597
image%e
0,583350
image%f
0,553195
image%g
0,696339
image%h
0,825874
loyalty1
0,858880
loyalty2
0,885788
loyalty3
0,788246
loyalty4
0,767739
oczek%d oczek%f oczek%g sales
0,876228
sales%a
0,849399
sales%b
0,855927
sales%c
0,850556
sales%d
0,845315
sales%e
0,842762
sales%f
0,823817
sales%g
0,669414
sales%h
0,776448
sales%i
0,664272
sales%j
0,633991
sat1
0,966102
sat1a
0,964621
sat1b
0,976425
service service%a service%b service%c service%d service%e service%f
213
service%g value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Value for money Vehicle Design Vehicle quality comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design
0,951949
design%a
0,901079
design%b
0,849767
design%c
0,933445
design%d
0,890844
image image%a image%b image%c image%d
214
image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d oczek%f oczek%g sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service service%a service%b service%c service%d service%e service%f service%g value1
0,990470
value2
0,990339
vehqual
0,907941
vehqual%a
0,858737
vehqual%b
0,531512
215
vehqual%c
0,691101
vehqual%d
0,664484
vehqual%e
0,788866
vehqual%f
0,837131
vehqual%g
0,602734
Path Coefficients After-sales quality Comfort Costs of ownership Expectations After-sales quality Comfort Costs of ownership
0,469850
Expectations Image
0,318826
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design Vehicle quality
Image After-sales quality
Loyalty
Overall satisfaction Sales quality
0,199762
Comfort Costs of ownership Expectations
0,264030
Image Loyalty Overall satisfaction
0,476481
Sales quality
0,370188
Value for money
0,263727
Vehicle Design
0,228841
Vehicle quality
0,598727
0,643344
Value for money Vehicle Design Vehicle quality After-sales quality
0,166142
Comfort
0,758564
Costs of ownership
216
Expectations Image
0,080849
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design Vehicle quality
0,708882
Outer Weights After-sales quality Comfort Costs of ownership Expectations comfort
0,271227
comfort%a
0,228339
comfort%b
0,176370
comfort%c
0,155357
comfort%d
0,133583
comfort%e
0,157692
comfort%f
0,157604
comfort%g
0,105982
comfort%h
0,133280
costs
0,223340
costs%a
0,095635
costs%b
0,191729
costs%c
0,271134
costs%d
0,238838
costs%e
0,211937
design design%a design%b design%c design%d image image%a image%b image%c image%d image%e image%f
217
image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d
0,410311
oczek%f
0,379351
oczek%g
0,416126
sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service
0,149729
service%a
0,154507
service%b
0,151026
service%c
0,131583
service%d
0,126007
service%e
0,138867
service%f
0,154127
service%g
0,142760
value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d
218
vehqual%e vehqual%f vehqual%g
Image
Loyalty
Overall satisfaction Sales quality
comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design design%a design%b design%c design%d image
0,180053
image%a
0,166860
image%b
0,150272
image%c
0,184022
image%d
0,188729
image%e
0,099408
image%f
0,084730
image%g
0,128439
image%h
0,182850
loyalty1
0,315840
loyalty2
0,319585
loyalty3
0,268910
loyalty4
0,304374
219
oczek%d oczek%f oczek%g sales
0,139083
sales%a
0,111480
sales%b
0,119984
sales%c
0,111997
sales%d
0,105346
sales%e
0,121582
sales%f
0,118556
sales%g
0,099577
sales%h
0,116801
sales%i
0,100462
sales%j
0,113910
sat1
0,341292
sat1a
0,343210
sat1b
0,347400
service service%a service%b service%c service%d service%e service%f service%g value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
220
Value for money Vehicle Design Vehicle quality comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design
0,227457
design%a
0,169434
design%b
0,211009
design%c
0,240102
design%d
0,255229
image image%a image%b image%c image%d image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d oczek%f oczek%g sales
221
sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service service%a service%b service%c service%d service%e service%f service%g value1
0,506563
value2
0,503125
vehqual
0,220447
vehqual%a
0,197553
vehqual%b
0,104167
vehqual%c
0,152303
vehqual%d
0,144527
vehqual%e
0,175684
vehqual%f
0,187009
vehqual%g
0,130075
222
Index Values Results Index Values for Latent Variables LV Index Values After-sales quality
7,630681
Comfort
8,952333
Costs of ownership
7,290020
Expectations
9,542902
Image
8,345158
Loyalty
8,331630
Overall satisfaction
7,950921
Sales quality
8,957169
Value for money
7,559792
Vehicle Design
9,264105
Vehicle quality
8,656681
223
Joanna Waligóra Student ID 254 581 Robert Waligóra Student ID 254 582
MEASURING CUSTOMER SATISFACTION AND LOYALTY IN THE AUTOMOTIVE INDUSTRY A CASE OF PREMIUM BRAND OF PASSENGER CARS
Master Thesis Advisor: Jacob Kjær Eskildsen Department of Marketing and Statistics
Aarhus, 2007
2
CONTENTS EXECUTIVE SUMMARY ..................................................................................................5 INTRODUCTION – A NEED FOR THE STUDY..............................................................7 MAIN OBJECTIVES OF THE PAPER..............................................................................8 1. THE IMPORTANCE OF CUSTOMER SATISFACTION FOR BUSINESS PERFORMANCE ................................................................................................................9 1.1. Customer satisfaction in customer orientation model .................................................10 1.2. Customer satisfaction in The EFQM Excellence Model .............................................13 1.3. The evidence of positive impact of satisfaction on business results ............................15 1.3.1. Satisfaction influence on ROI, stock prices and shareholder value.......................16 1.3.2. Customer retention impact on business results.....................................................17 1.3.3. Dissatisfaction influence on business performance ..............................................18 2. THE THEORY OF CUSTOMER SATISFACTION....................................................22 2.1. The definition of customer satisfaction.......................................................................22 2.2. Antecedents of customer satisfaction .........................................................................22 2.3. Consequences of customer satisfaction. .....................................................................25 3. CUSTOMER SATISFACTION MEASUREMENT SYSTEMS ..................................29 3.1. Antecedents of satisfaction measurement system implementation – customer’s personal values research .................................................................................................................29 3.2. Rationale for development and use of industry or nation universal customer satisfaction measurement indexes........................................................................................................32 3.3. National Customer Satisfaction Indexes .....................................................................33 3.3.1. Swedish Customer Satisfaction Barometer ..........................................................33 3.3.2. American Customer Satisfaction Index ...............................................................36 3.3.3. European Customer Satisfaction Index................................................................39 3.3.4. Automotive industry specific customer satisfaction indexes ................................43 4. COMPANY X CUSTOMER’S PROFILE ....................................................................47 4.1. Company X customers – demographics .....................................................................47 4.2. Company X customers – benefits driving the car purchase.........................................53 4.3. Company X customers – attitudes to vehicle ..............................................................58 4.4. Summary of Company X customer’s profile ..............................................................59 5. STRUCTURAL EQUATION MODELING AND PARTIAL LEAST SQUARES .....61 5.1. Structural Equation Modeling – covariance-based approach.......................................61 5.2. Partial Least Squares..................................................................................................62 5.2.1. Specification of the model...................................................................................62 5.2.2. Estimation...........................................................................................................64 5.2.3. Validation of model ............................................................................................67 6. MEASURING CUSTOMER SATISFACTION AT COMPANY X IN POLAND ......71 6.1. Customer Satisfaction Index at Company X – Sales Service Quality..........................72 6.2. Customer Satisfaction Index at Company X – After - Sales Service Quality...............74 6.3. Brand Satisfaction Model at Company X in Poland – history, underpinnings and structure ...........................................................................................................................75 6.3.1. Questionnaire development .................................................................................79 6.3.2. Computer software for Partial Least Squares models...........................................84 6.3.3. Working out the structure of the model ...............................................................85 6.3.4. Discussion on BSM structure ..............................................................................89 6.3.5. Quality criteria evaluation ...................................................................................92 7. RESULTS OF BRAND SATISFACTION MODEL FOR COMPANY X ...................95 7.1. Sample description.....................................................................................................95
3
7.2. Estimation results for Brand Satisfaction Model – Total Brand ................................101 7.3. Estimation results – Total brand - detailed analysis of performance..........................108 7.4. Estimation results for Brand Satisfaction Model – 3 segments of customers.............115 7.4.1. General estimation results for 3 customer segments...........................................115 7.4.2. Total effects analysis – 3 customer segments .....................................................119 7.4.3. Satisfaction vs. importance analysis - 3 clients segments - inner model .............123 7.4.4. Satisfaction vs. importance analysis - 3 customer segments –outer model..........127 7.4.5. Summary of analysis for 3 customer segments...................................................135 CONCLUSIONS AND RECOMMENDATIONS ...........................................................137 REFERENCES .................................................................................................................139 APPENDICES ..................................................................................................................142 Appendix 1. ....................................................................................................................142 Appendix 2. ....................................................................................................................143 Appendix 3. ....................................................................................................................149 Appendix 4. ....................................................................................................................163 Appendix 5. ....................................................................................................................182 Appendix 6. ....................................................................................................................203
4
EXECUTIVE SUMMARY The new method of customer satisfaction and loyalty measurement has been developed for Company X in Poland. The method is called Brand Satisfaction Model. The Company X is operating on the automotive market representing premium brand of passenger vehicles in Poland. The model has been created based on customer satisfaction and loyalty theories and so far implemented and practically adopted models. The Brand Satisfaction Model is mainly built on the ACSI, ECSI and JD Power CSI studies with particular use of satisfaction theories presented in the paper. The BSM structure is adjusted to industry specific requirements which have been verified by customer focus groups and statistical validity tests. Therefore unique, industry specific method for measuring satisfaction of passenger vehicles clients has been developed and is presented below:
Practical research on a group of 346 customers of Company X in Poland has been conducted. After analysis of satisfaction scores and importance levels for all the areas included in the study four areas that need to be definitely improved have been revealed: After Sales service quality, Value for money, Costs of ownership and Brand Image. The results of the study have been made well-known across the entire organization. The reparation program has been developed and implemented and as a result of it the next After
5
Sales service satisfaction study presented the increase in overall score by 2 percentage points. Further actions concentrating on improvement of the other three mentioned areas have been implemented but their results were not known yet when the paper was written. Therefore the knowledge gained with Brand Satisfaction Model helped Company X prioritize its actions and concentrate on those areas that need to be taken care of in a first place. Furthermore the study analyzed three customer groups separately: Compact, Mid-size and Full-size and Large vehicles owners in order to discover differences in their definition of satisfaction and loyalty. Compact vehicles users are much more price and costs sensitive. They also pay stronger attention to the image of a brand and post-purchase service they receive. Mid-size vehicles users are definitely closer in terms of their profile to the third group of customers however they are more vehicle comfort and quality oriented while at the same time do not expect so high value for money as other clients. The full-size and large vehicles owners are definitely the least price and costs sensitive. Vehicle quality, comfort and functionality and sales service quality are the most important elements strongly affecting the level of their loyalty. The knowledge gained from the analysis of three customer segments helped the sales and marketing as well as PR departments adjust its operations and strategy to specific requirements of different customer groups in order to improve their overall satisfaction and loyalty to a brand. Developed model proved to be very explanatory with regard to the type of knowledge received after application of the structure to the dataset gathered during interviews with Company X customers. The BSM is also an effective tool that not only helps to understand customers better but also answers the question: how to improve customers’ satisfaction and loyalty. The Polish Automotive Market Research Institute presented interest in the model with the aim to make the Brand Satisfaction Model the uniform platform for measuring and comparing customer satisfaction and loyalty across whole polish automotive sector.
Successful
implementation of Brand Satisfaction Model by all brands of passenger vehicles operating in Poland would definitely supply automotive companies in Poland with knowledge comparisons of brands performance on the Polish market.
6
INTRODUCTION – A NEED FOR THE STUDY There is a need for the comprehensive study at Company X in Poland which would cover all aspects of customer satisfaction and loyalty. The need was recognized by the marketing and sales department and the board of directors due to the fact that so far the knowledge about Company X clients was limited to their demographic and social profile and customer’s evaluation of sales and after-sales service quality. All other areas such as vehicle quality, design, comfort and functionality, cost of ownership, value for money etc. have been so far neglected and not measured. Therefore the Brand Satisfaction Model has been created in order to close the gap in knowledge about Company X clients. Customer Satisfaction can be measured and monitored on many levels of advancement. First of all, customer orientation concept, means-end chain theory, expectations disconfirmation and performance models, Hirschman’s exit theory are important theories which define clients’ satisfaction and loyalty concepts and their influence on company business results. Than, the EFQM Excellence Model takes the satisfaction studies to the next level and measures customer satisfaction importance and influence on company’s profitability and success. Finally, there are those customer satisfaction measurement nation-wide studies such as SCSB, ECSI and ACSI, which define the satisfaction concept empirically and help understand the relationships between antecedents of satisfaction and its consequences such as loyalty and retention. Additionally, there are industry specific types of researches such as JD Power automotive CSI that measure clients’ satisfaction with different aspects of product usage which are usually applicable to only one industry. Taking into consideration all the above mentioned satisfaction theories, the Brand Satisfaction Model has been built up based on the above mentioned theories and researches as a complete and comprehensive measurement method of clients’ satisfaction and loyalty for Company X in Poland. Although its structure is similar to ECSI, the BSM includes some of the JD Power CSI study elements. Such combination of the theories and the two researches offers a valuable tool that combines most of theoretical and empirical knowledge so far possessed by academic and professional environment. The Brand Satisfaction Model may be useful sales and marketing tool not only for Company X but also for other automotive companies operating on Polish market. If the study was applied to other firms, than a great portion of knowledge could be added to the whole 7
automotive sector in Poland by allowing for cross industry comparisons. Provided that the BSM is well grounded in terms of its statistical properties as well as satisfaction theories, there is high probability that the same structure could be applied to other automotive brands. So far there has been no other unified measurement model of customer satisfaction and loyalty created and used in the polish automotive sector. There are different researches covering some aspects of company’s performance but the unified and complete approach allowing for comparison between different brands is not available. Therefore the study that is comprehensive and at the same time industry specific – such as Brand Satisfaction Model would be a huge contribution to the Polish automotive sector. MAIN OBJECTIVES OF THE PAPER The main objective of the study is: -
Creation of complete satisfaction measurement model for Company X selling premium passenger vehicles in Poland and assessment of Company X customers’ satisfaction and loyalty based on the new methodology. Up till now the Company X has been only using its own Customer Satisfaction Index study as the measure for sales company performance. However such approach leads to severe limitations of the study results, as the Customer Satisfaction Index concentrates only on measurement of satisfaction with sales and after-sales service quality. Therefore more comprehensive approach covering all aspects of customer experience with product, brand and dealerships is needed.
In order to support the main goal some sub objectives shall be fulfilled: -
Creation of theoretical satisfaction measurement model and statistical validation of the model. The model shall be based on customer satisfaction theories and measurement models described in this paper.
-
Application of the theoretical model into the practical research - measurement of Company X customers’ satisfaction and loyalty using the new methodology.
-
Analysis of the research results and comparison of the differences between Company X customer segments. The Company X clientele shall be segmented into three groups based on existing Customer Profile study: Compact vehicles, Mid-size vehicles, Full-size and Large vehicles owners. 8
1. THE IMPORTANCE OF CUSTOMER SATISFACTION FOR BUSINESS PERFORMANCE Satisfaction understood as emotional state shall be held by people, who are willing to develop successfully personal relations, but has also been of utmost importance in business and professional situations. The latter will be of our interest in the further course of this work. In general, satisfied customers, satisfied employees and satisfied shareholders all have one common characteristic – they are positive and enthusiastic about the company they are dealing with. Talking in more detail, they shall behave in a way desired and understood by a firm, when it comes to making decision about further cooperation with the company. Specifically, they will be making repeat purchases, delivering best quality of work and investing additional funds in the company stocks. Such behavior of satisfied customers, employees and shareholders will contribute to business growth. Therefore satisfaction, understood in such a wide context, shall definitely be on the top of board of directors’ list as it has strong positive impact on business results. Although satisfaction is applicable to organization’s customers, employees and shareholders, within the course of this work customer satisfaction will be discussed. Specifically, customer as the ultimate judge of products or service quality and his or her satisfaction with the delivered products or services will be taken into account. Customer satisfaction is crucial for business performance, as it is the driver of customer loyalty and consecutive retention. This statement, although intuitively true, could be argued with. On one side, it could be said, that there is no need to dedicate time and funds to make the customer’s satisfied, but it is less expensive and sufficient to deliver high quality offerings, which will certainly be purchased by some clients. Furthermore, one could argue that even though customers are not loyal and will not stay with the company, new clients can be easily found. On the other side it can be argued, that even though customers will buy the product, they will not repurchase unless the offering meets customers’ needs. Moreover, it may turn out, that despite product’s quality is high it does not fill client’s expectations, as it misses some of required benefits. Finally, one could say that it is much more expensive to acquire new customers than retain current ones, as the costs associated with the customer recruitment are higher than those connected with customer retention. 9
The above arguments connected with customer satisfaction concept have been widely measured and discussed in the literature. As a result there is lots of evidence supporting the initial statement: customer satisfaction is crucial for business performance, as it is the driver of customer loyalty and consecutive retention the importance of customer satisfaction for business results. Within the course of this chapter, we will focus on only few supportive theories. First of all, the importance of customer satisfaction for business performance has been justified within the customer orientation concept. Secondly, the actual importance of customer satisfaction for business performance versus importance of other factors has been quantified within the EFQM Excellence Model. Finally, also the impact of increased satisfaction on business results was researched and quantified within the literature. 1.1. Customer satisfaction in customer orientation model Customer satisfaction concept has been placed at the heart of customer orientation model. Based on this model, there are two kinds of companies;
on the one side, there are product oriented companies, who are trying to sell the products which they produce regardless of the level, to which those products satisfy their customers’ needs. To simplify it, product oriented companies are searching for customers, whose needs can be matched with the products, that the company is offering. Very often those companies end up in the business stagnation phase, as they are not be able to follow the natural development of customer needs – they continue to offer what they think is desired by the consumers instead of delivering what is actually desired.
on the opposite side, there are customer oriented companies, who are focused on meeting customer’s needs and satisfying him or her, as they know that satisfaction is a prerequisite to retention, which in turn has positive impact on the long-term health of their business.
Customer orientation is an ongoing process, during which organizations pursue three goals: 1. attain customer information, 2. disseminate and use that information when making decisions 3. implement change (Johnson, Herrmann, Huber, Gustafsson, 1997).
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First goal - “attain customer information” - means that a firm must collect information about its customers. This is done through various research techniques in order to find out, what are the needs and values of customers and how they are served by current products and services. The information attained shall also point out future customer’s needs and the direction into which they will be developing. Secondly, a customer oriented company needs to ensure, that the “disseminate and use the information” goal is met. Therefore it is necessary to make sure that the information collected is shared between all departments involved in production and delivery of products or services to customers. For that to be possible, tight cooperation between market research and other departments is necessary. Moreover, organization’s leadership must understand the necessity of and support the facts-based decision process. Finally, there is no use of information, which is collected and stored in databases. To fulfill the third goal – “implement the change” - it is necessary to translate the conclusions and recommendations from the research into actions, which will enable the company to deliver improved products and services. To summarize, a customer oriented company has one primary goal – to satisfy its customers, which is realized by getting to know customer needs and values, sharing this knowledge throughout the company and translating it into improved products and services, which are able to satisfy the customer to largest possible extent. Satisfying the customers is a never ending process. As the customer grows up, gets older and ages, his or her needs and values change. Moreover, as the economies develop, mature and decline, the wants of human beings also change. As a result, companies are forced to follow or even be ahead of customer’s needs in order ensure business growth. Customer orientation process never comes to an end – it is a sequence of repetitive stages. The theory of customer orientation distinguishes four major phases, which a customer oriented company has to go through all over again to ensure growth in customer orientation (Johnson, Herrmann, Huber, Gustafsson, 1997): 1. Customer strategy and focus 2. Customer satisfaction measurement 3. Analysis and priority setting 4. Implementation.
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Figure 1.1. The four phases of customer orientation
Phase I: Customer Strategy and Focus
Phase II: Customer Satisfaction Measuremen t
Phase III: Analysis and Priority Setting
Phase IV: Implementation
Source: Johnson, Herrmann, Huber, Gustafsson, 1997 In the first phase of the process, companies should answer the question, how important is the customer for their business performance and to what extent is the customer orientation their business priority. In other words, it shall be clearly stated, to what extent company shall and can adjust their strategy to consumers needs. Furthermore, phase 1 is the right time to specify, which customer segments shall be in the center of organizations attention – e.g. referring to automotive industry, shall the company focus on premium or mass cars’ users, shall the company target young and dynamic or adult and affluent customers? During phase two of customer orientation process, organization shall develop a measurement system, which will enable to evaluate the level of customers’ satisfaction of particular target groups with currently delivered products or services. In more detail, the measurement system shall answer the question, which needs, values and benefits are key for consumers within customer segments. Specifically, the research shall evaluate, to what extent current products and services’ attributes deliver the desired benefits and therefore fill customers’ needs. As the second phase provides the company with the assessment of benefits’ importance and the extent to which current offerings fill those benefits, during third phase organization shall analyze the information gathered and set priorities for further actions. In other words, organization shall spot for product benefits, which are very important for target customers, however not delivered by current products or services. Such benefits shall be the key priority for company and a main focus in order to make the customers more satisfied and therefore more prone to repeat purchases.
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Fourth phase of the customer orientation process requires that all the priorities set in phase three are translated into specific actions and process, which will be conducted. Those actions shall result in making the customer more satisfied through delivery of improved product or service. This customer orientation process shall never end and shall be repeated – after fourth phase, phase one shall start, which shall verify, if the improved product really satisfied customer to larger extent. To summarize the customer orientation model, it is entirely focused on customer satisfaction. Based on this model, only customer oriented company, which tries to deliver offerings tailored to customer’ needs may expect returns from their actions. Returns equal higher satisfaction levels being observed, which in turn shall increase the probability of repeat purchases and as a result, increasing returns for the organization. Customer orientation model undoubtedly has the customer focus and customer orientation in its hearth and stresses the importance of customer satisfaction for the business performance. Although customer orientation model has stressed the importance of customer satisfaction for business performance, it has not quantified the importance. This leads us to the next theory, which has taken the discussion to next level and quantified the importance of customer satisfaction to business performance – The EFQM Excellence Model. 1.2. Customer satisfaction in The EFQM Excellence Model The authors of The EFQM Excellence Model have not only acknowledged the importance of customer satisfaction for organizations, but also measured the importance for the business performance. The EFQM Excellence Model was introduced in 1992 and is a practical tool, which in midterm helps organizations to evaluate and improve their performance, and in long term enables them to strive for excellence. The organizations are evaluated based on nine criteria, which are included in The EFQM Model. Five of them are “enablers” – they cover, what an organization does, and remaining four are “results”, which include what an organization achieves. There is relation between two groups – the “results” are driven by “enablers”. The structure of the model is presented in the below figure.
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Figure 1.2. The EFQM Excellence Model
Source: www.efqm.org The EFQM Excellence Model, similarly as customer orientation model, puts customer and his satisfaction in the heart of the theory. Specifically, it discusses the concept of customer satisfaction within three of its nine criteria: 1. firstly, it is stressed within “Leadership” criterion, that company leaders need to meet, understand and respond to needs and expectations of stakeholders, which also include customers as one of most important groups. 2. secondly, also “Processes” criterion concentrates on satisfaction. Processes in the organization shall be designed in such manner that they support organizations’ policy and strategy, fully satisfy and generate value for its customers and other stakeholders (The EFQM Excellence Model 1999 manual). 3. lastly, “Customer results” criterion is completely dedicated to customers’ satisfaction. Measures within this criterion are supposed to assess customer’s perception of overall organization’s
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image,
his or
her
satisfaction with
products/services, sales and after sales support and evaluate customer loyalty to the organization. The focus on customer and his or her satisfaction in three out of nine criteria in The EFQM Excellence Model is the evidence supporting the importance of customer satisfaction for the business performance. The authors of the model have established importance weights for each criterion in the model. It is necessary to stress, that “Customer results”, called also customer satisfaction criterion, is the weightiest criterion in the model and accounts for twenty percent of the total scoring system when companies assess and measure their own excellence (Gronholdt, Kristensen, Martensen, 2002). To put it differently, customer satisfaction has not only the largest impact on evaluation of organization excellence, but most importantly understanding the customers and measuring their satisfaction is important step in quality improvement, which than results in higher satisfaction levels, improved business results and business excellence. To summarize, based on the EFQM Excellence Model, customer satisfaction is the most important factor driving the organization towards excellent performance and increasing financial results. Having in mind that customer satisfaction is important for business performance, that it is the most important factor in driving business towards excellence, it is important to quantify the influence of increased satisfaction on the company performance. 1.3. The evidence of positive impact of satisfaction on business results In literature, there have been lots of empirical studies conducted on satisfaction influence on company’s performance, as well as effect on the influence of customer dissatisfaction on the firm’s results. The satisfaction or dissatisfaction influence on organization’s performance may be discussed in three aspects: 1. positive impact of growing satisfaction on return on investments (ROI), prices of stocks and shareholder value 2. positive impact of satisfaction on customer retention and as a result lower costs or higher returns resulting from long term relationship with the customers 3. negative impact of customer dissatisfaction on business performance and business results
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There is strong evidence within those three aspects for positive correlation between growing customer satisfaction and business results. 1.3.1. Satisfaction influence on ROI, stock prices and shareholder value The empirical studies were conducted based on customer satisfaction measurement models and using the data acquired during models testing and implementation in order to evaluate if there is positive correlation between increased satisfaction and ROI, stock prices and shareholder value. Starting with Swedish Customer Satisfaction Barometer index (which will be described in detail in further course of this paper), it was analyzed, what is the effect of increased satisfaction on ROI. The results of the study conducted by Anderson, Fornell and Lehmann (1994) are the first, large sample evidence, that customer satisfaction is related with company performance. The study revealed that as the satisfaction changes by one percent, ROI changes by 0.4 percent. Further studies conducted on SCSB by Anderson, Fornell and Rust (1997) proved that average elasticity of ROI is higher for goods – 0.265 than for services – 0.14. This implies that it is much more difficult for service companies to satisfy their clients than it is for production companies. Such difference may be related to the fact, that it is much easier for a consumer to distinguish between and objectively evaluate the quality of the product rather than the service. Referring further to the Swedish example, Ittner and Larcker have taken the analysis to the next level, and examined the correlation between satisfaction and stock prices. The results of their study prove that a one percent change in the satisfaction index translate into about seven percent change in shareholder value (Gronholdt, Kristensen, Martensen, 2002). The same authors carried the analysis based on American Customer Satisfaction Index (ACSI). The study results were in line with the Swedish results and they confirmed that there is relation between satisfaction levels and stock prices; companies with highest customer satisfaction indexes earn return on stock price of 1-2 percent per month above the average return on the market (Gronholdt, Kristensen, Martensen, 2002). To summarize, there is solid evidence in the form of results of various empirical studies, that customer satisfaction is correlated with financial results in following manner: 16
1. increasing customer satisfaction positively influences return on investments (ROI) 2. the higher the customer satisfaction, the higher earnings on stocks for shareholders 3. increasing satisfaction drives positive change in shareholder value 1.3.2. Customer retention impact on business results Satisfaction is a prerequisite for customer loyalty and retention. In other words, if customers are satisfied with the product, it is probable, that they will be loyal to the company and that the loyalty will be translated into repeated purchases. Repeated purchases are in turn prerequisite to increasing financial results for the company, what implies that customer retention is profitable to the organization. Going further, the benefits from retaining the customers are larger than from acquiring new one and the costs associated with current customer are lower and declining as compared to new customer. This thesis has been supported by Reichheld (Johnson, Herrmann, Huber, Gustafsson, 1997), who has been discussing effects of customer retention on business performance and he defined areas – both cost and revenue, which are strongly impacted by customer retention: 1. Acquisition costs; all costs related with attracting customer to the company, such as incentive program, creation of customer accounts, customer training. As these costs appear in the early stage of relationship with the customer, customer retention allows for avoiding them. 2. Start-up costs; costs, they are related to the beginning of cooperation with the customer, egg. set up of customer bank account. With time, the account is maintained and some costs are associated with that, but one time set up costs do not happen again. 3. Base revenues; the revenue, which a company accounts for regularly during each following period, e.g. base revenue from monthly payment for mobile phones. When customer is retained, the base revenue is guaranteed cash flow for a firm. 4. Volume effects; the surplus revenue, which company earns as the relation with a customer is developing. Customers, if satisfied, tend to increase their spending with a company by either buying larger quantities of a product. 5. Spin-off effects; with time, customers have a tendency to purchase complementary products or services, e.g. satisfied car owner shall buy second car for his family members or will acquire a car gadgets from the company, e.g. watch from Company X collection 6. General efficiency effects; operation costs are expected to decrease with time, as the company gets to know its customers better and therefore is capable of delivering the 17
products or services in the required manner. On the other hand, customers get to know the structure of the company and the requirements from the company side, which enable for delivery of higher quality offerings. In other words, cooperation between both sides becomes smoother. 7. Referral effects; satisfied customer shall talk to two persons about his or her positive purchase experience, however dissatisfied customer will talk to and discourage ten persons from potential cooperation with the organization. Nowadays, this factor is becoming of extreme importance – as the traditional marketing tools have become well known and understood by customers, customer referrals and so called word of mouth has a great power. 8. Price- sensitivity effects; loyal customers are less price sensitive than new customers. If the relationship with the company is satisfactory for the customer, he is willing to pay more for the same products. Moreover, if the customer is acquired in his early stage of life, as he grows older and becomes more affluent, he is also willing to trade for premium products within the same supplier. If customer is satisfied, he is probable to continue the relationship with the company. If that is the case, the above described effects shall happen – they will either lead to lower costs or higher returns. In the end, as the relationship with customer is continued, profit per customer shall grow over time. 1.3.3. Dissatisfaction influence on business performance We have already explained the importance of customer satisfaction for business performance and proved that there is measurable, positive impact of increased customer satisfaction on business results. This implies that companies, which enjoy increasing satisfaction of its customers, at the same time note increasing business results. However, there are those companies, who observe declining satisfaction. The question is therefore what are the results of customer satisfaction decline? Based on Hirschman’s theory (Johnson, 1996), dissatisfied customers may react in two ways – they may either voice or exit. Customer exit is the worse consequence of customer evaluation of product offering. In such situation, the organization looses customers, what results in declining sales and revenues for 18
the company. Moreover, such customer, called “dissatisfied switcher”, will most probably express his or her dissatisfaction through word of mouth to other potential customers. In other words, dissatisfaction has not only direct effect on organization business measured as lost potential sales, but may also have indirect effect on the business in the form of negative word of mouth. Therefore it is of extreme importance for the company to handle in the right manner second possible reaction of dissatisfied customer –customer voice. If a customer is dissatisfied, before he or she exits, he or she may also complain to the company. Depending on how his or her complaint is handled – whether in satisfactory or nonsatisfactory manner, he or she will either exit or retain with a company. Therefore it is extremely crucial for the company to establish effective complaint management system which will ensure, that two actions happen: a) listening to complaints and b) reaction to the complaints. The establishment of complaint system is important due to three reasons: 1. effective complaint handling system may prevent from customer exit and therefore business loss 2. it may prevent from negative word of mouth from dissatisfied switchers 3. dissatisfied customers, who are potential “dissatisfied switchers” and whose complaints are handled in satisfactory manner, may become even more satisfied and loyal clients – so called “satisfied repeaters”. As a result, they shall not only repurchase from the company, but shall also convert the negative word of mouth into the positive one. Apart from dissatisfaction consequences described by Hirschman – exit or voice, it may also happen that a dissatisfied customer will not voice and will not exit. In such case the dissatisfied customer will not voice a complaint, as he or she believes that there will be no benefit from such action – no positive response from the company. At the same time, he or she will retain with the company, as there is no other available or no better product or service provider. Such consumers are called dissatisfied repeaters. They are most often acting in the low competition or even monopoly markets – e.g. state-owned services, where a choice is limited or none, therefore despite dissatisfaction, consumers need to repeat the purchase. However, if the economic environment changes, competition increases and more interesting offerings appear, dissatisfied repeaters are likely to switch to those new options. Therefore those customers shall also be in the loop and actions shall be taken to increase their satisfaction levels so as to prevent them from switching to other companies. 19
The below table presents four types of customers, out of which two were described above – dissatisfied switchers and dissatisfied repeaters. Figure 1.3. Four customer types
Repurchase Behaviour Repeat
Switch
High
Satisfied Repeaters
Satisfied Switchers
Low
Dissatisfied Repeaters
Dissatisfied Switchers
Customer Satisfaction
Source: Johnson 1996 The empirical studies on satisfaction and dissatisfaction influence on business performance in general confirm and support the conclusions, that;
satisfaction is of crucial importance for business performance
satisfaction has positive impact on business results
retention, as a result of satisfaction, has positive influence on lower costs and higher returns
dissatisfaction may lead to customer base decline and therefore generate lower return
In more detail, the discussed studies justify organizations’ choice of customer orientation strategy. Starting from positive influence of customer retention on lower costs and higher, increasing profits and ending with higher return on investment for companies, who are able to raise customer satisfaction levels – these are all undeniable evidences, that investment in customer satisfaction and retention shall be the key area of focus for managers. In particular in maturing economies, where market dynamics presents a one-digit quote or even zero number, where markets are saturated with competing, comparable products or services, it is important to adopt defensive strategy. Defensive marketing concentrates on customer retention by either increasing customer satisfaction or building switching barriers and is opposite to offensive marketing, which focuses on increasing market size and building market
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share. Majority of companies adopt balanced mix of both strategies - acquiring new customers and retaining the current ones. However, in maturing economies, the skewness is towards defensive strategies, as it becomes more and more difficult and costly to acquire new clients. Therefore, increasing customer satisfaction has become a key focus area for managers in today’s organizations. In the course of this chapter we have proven the undeniable importance of customer satisfaction for increasing business excellence and described the studies, which measure the impact of customer satisfaction on ROI and on stock prices. We came to the conclusion that as increasing customer satisfaction has positive effects on business growth, it shall be the top priority for the management. However, we have also discussed that in order to satisfy the customers better, it is necessary to diagnose current level of satisfaction by establishment and implementation of customer satisfaction measurement model. Thank to such model, the weaknesses of current offerings can be spotted and eliminated to deliver products capable of satisfying the customer to larger extent. However, to build the satisfaction measurement system, it is necessary to understand the concept of satisfaction, its drivers and consequences. Therefore next chapter will focus on theoretical framework of satisfaction, its antecedents and consequences.
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2. THE THEORY OF CUSTOMER SATISFACTION 2.1. The definition of customer satisfaction In the literature, there has been discussion about two major concepts of satisfaction; transaction-specific satisfaction and cumulative satisfaction (Gustafsson, Herrmann, Huber, Johnson, 1997). The first one is described as customer evaluation of single experience with a product or service – therefore how happy the customer is with the offering at given point of time, during concrete transaction. Transaction-specific concept refers to satisfaction as the evaluation of single experience. Opposite to transaction specific satisfaction is the concept of cumulative satisfaction, which understands satisfaction as customer’s up to date experience with a product or service. In such comprehension, satisfaction is the sum of evaluations of all purchase and consumption experiences with a product during whole relationship. During the course of this paper, cumulative satisfaction concept will be used, as it is more appropriate for automotive industry. In this durables business, purchases are infrequent and satisfaction is understood as a long term experience. The owners of the cars, if asked about satisfaction with the particular brand, refer to cumulative satisfaction – they talk about purchase experience, vehicle use experience, ending with after-sales service experience. 2.2. Antecedents of customer satisfaction Satisfaction has its antecedents or drivers – factors, which influence the satisfaction levels. In general, there are two major drivers of customer satisfaction – product’s performance, which includes both product’s quality and product’s value (relation of price and quality). In more detail, satisfaction drivers were initially defined in two models in the literature – disconfirmation model, which is often associated with transaction-specific satisfaction and performance model used in studies of cumulative satisfaction. Specifically, the theory of the models and the differences between them are described below: a) Disconfirmation model Referring to disconfirmation model, the difference between perceived product’s performance and expected performance is a driver of satisfaction. 22
Disconfirmation model assumes that satisfaction increases if performance exceeds expectations – in such case we talk about positive disconfirmation. In the opposite case, when product or service performs below expectations, there is negative disconfirmation effect, which leads to decline in satisfaction. The figure below graphically presents the reasoning of disconfirmation model. It assumes that expectations may have both positive and negative influence on satisfaction. If performance increases over constant expectations, there is positive disconfirmation, which positively influences satisfaction. However, if expectations grow above constant performance, there is negative disconfirmation of expectations and satisfaction decreases. Such transaction specific gaps are than aggregated into an overall customer satisfaction (Johnson, M.D., 1996). Figure 2.1 The Disconfirmation Model
Performance minus expectations
+
Customer satisfaction
Source: Johnson, M.D., 1996 b) Performance model Within the performance model, expectations of product or service performance are similar to product’s image, which is based on either personal experiences with the product or information and opinions heard and learned from other users. As opposite to disconfirmation model, expectations have only positive influence on satisfaction. Moreover, expectations shall have positive impact on perceived performance, what means that expectations are able to predict current level of performance. In addition, if expectations are strong, than they shall positively influence the perceived performance – therefore in such case the evaluation of performance may be far from real performance level.
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Figure 2.2. The Performance Model
Expectations
+
+ + Customer satisfaction
Performance
Source: Johnson, M.D., 1996 Despite the expectations importance in the performance model, it is the performance, which is main driver of customer satisfaction. Based on the model, performance has positive effect on satisfaction level. The graph below represents the performance model (Johnson, M.D., 1996). Comparing disconfirmation and performance models, it is necessary to say, that the second one has been evaluated as more appropriate model for predicting customer satisfaction. In general, empirical studies of satisfaction confirm that expectations have rather positive than negative influence on satisfaction. Moreover, disconfirmation model is adjusted to studies of transaction specific satisfaction, while majority of empirical studies understand satisfaction as cumulative, not transaction specific. As an effect of the above arguments, performance model is evaluated as superior to disconfirmation model in the studies of customer satisfaction. Such conclusion will be also valid in the practical part of this work, as the satisfaction measurement model will be assessing up to date experience and therefore satisfaction with the automobiles, rather than single transaction satisfaction.
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2.3. Consequences of customer satisfaction. Satisfaction has not only its drivers – performance and expectations, but also its results – loyalty and retention. Those two consequences are correlated with each other, but are at the same time distinct results of customer satisfaction. Loyalty is only expressed psychological predisposition toward purchasing and/or using a particular product/service once again, however it does not guarantee a success to an organization measured as customer retention. In other words, loyalty is a high perceived or expressed likelihood of repurchase or willingness to pay a higher price, but does not mean, that customer will repurchase from an organization (Johnson, M.D., 1996). It is the retention, which is ultimate consequence of satisfaction and which is the actual act of repurchase. There are various reasons, due to which loyal customer – or the one, who expresses the loyalty attitude, in the end switches to competition. The Customer Experience Model (presented in the figure below) explains why loyalty does not necessarily end up with retention. Figure 2.3. The Customer Experience Model
Customer’s internal knowledge database
Customer perceptions, judgements and choice
Consumption, customer satisfaction and loyalty
External market infomation
Source: Johnson, M.D., 1996
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The model separates the consumption experience and resulting satisfaction and loyalty from the repurchase decisions and explains, what happens, when potentially satisfied consumer does not repeat the purchase with the same company. Based on the model, there are three aspects of product or service consumption and the consecutive satisfaction and loyalty. First of all, customer relation with the company starts with the decision about the product or service purchase and the consumption. As a result of consumption experience, customer forms the evaluation, perception and expectation towards the product and at the same time, he or she becomes more or less satisfied with the product. Secondly, during the consumption process, consumer stores in mind all the information learned regarding experience with the product. He or she uses those experiences and information when making decision about the future repurchase. Supposing that he or she is satisfied with the product, this makes him or her more predisposed towards repeated purchase. Finally, the consumer comes to the decision about repurchase of the product. He or she will most probably make the decision based on the knowledge and experience gained so far. However, as the world is changing, customer is exposed to new information during the consumption – repurchase process. He or she receives information about new offerings, is exposed to word-of-mouth information. As a result, even though customer is satisfied with the current product and expresses to be loyal, external markets conditions may influence his decisions and he or she may switch. Such customers are called satisfied switchers – they may switch e.g. from Audi to BMW, because BMW will offer better priced offer – therefore customer will perceive BMW as higher value car, or BMW will offer technological advancements, that Audi is not able to deliver. On the other side, the above described scenario may not happen. Even though a customer is exposed to external information and knows other options, he may stick with the current brand and repurchase. But such case will most often happen by habitual, daily purchases. In case of durables – and such is the automotive industry, companies need to make sure, that they have the absolute competitive advantage and that no other brand is capable of attracting current customers. Both satisfaction drivers and results are linked in a theoretical framework, which helps to understand the relations between drivers and effects of satisfaction. The framework is presented in the below figure. 26
Figure 2.4. A framework for linking quality, satisfaction and retention
Internal product and service production and maintenance process
Perceived value, quality, and expectations
Customer satisfaction
Customer loyalty and complaint behavior
C O N T E X T
Customer retention
Source: Johnson, Herrmann, Huber, Gustafsson, 1997 At the beginning of the whole process is the actual production of product or service and placing an offer to the consumer. Providing that the product matches consumers needs, the consumption process starts. During that process, consumers evaluate the product with regard to its performance – understood as evaluation of quality, value (equal to quality versus price paid and price paid versus quality) and confront the performance versus expectations. Such evaluation lays ground for perception of satisfaction – the extent to which product or service met customers needs. The level of satisfaction or dissatisfaction strongly affects and predicts customer loyalty and as a result customer retention, however it guarantees nothing, as even satisfied customers may switch to competition. Therefore in order to retain customers, companies need to continuously improve current offering, present revolutionary and innovative products and constantly deliver higher customer value. In other words, satisfying a customer is a constant process, which means that new and better ways need to be found to customer needs. To summarize, customer satisfaction is important concept for business performance and has measurable impact on business results. It is due to the fact that satisfaction influences loyalty and consecutive retention. In other words, dissatisfied consumers may substantially negatively impact business results. Therefore, it is of extreme importance to measure the current satisfaction levels to be able to spot problems, eliminate them and deliver improved products and services to customers in order to lift current satisfaction levels.
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Having discussed the theory of satisfaction, its importance and impact on business performance, we will now discuss satisfaction measurement systems developed so far within the literature.
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3. CUSTOMER SATISFACTION MEASUREMENT SYSTEMS 3.1. Antecedents of satisfaction measurement system implementation – customer’s personal values research Referring to customer orientation strategy, an organization, which recognizes the need to make its customers more satisfied, shall first develop the customer satisfaction measurement system in order to evaluate current level of satisfaction and be able to translate findings of the study into the specific improvement plans. Therefore, for each organization, which is customer focused, settlement and implementation of customer satisfaction measurement system is a must and a major step towards customer satisfaction growth. However, customer satisfaction measurement systems are just part of overall customer research. Before any satisfaction measurement system is implemented, an organization shall get to know its customers better. This includes knowledge of demographic characteristics, such as age, gender, income, but most of all the set of customer’s personal values. The theory, which justifies the importance of the knowledge of customer’s values is the means-end theory. The theory explains how the choice of concrete product enables the consumer to satisfy his or her personal values. In other words, how the “means” – products lead to desired end states – called “ends”. Referring to the theory, customers consider products as bundles of attributes (Johnson, Herrmann, Huber, Gustafsson, 1997). During the decision - making process, they do not analyze the attributes of the offering separately, but they analyze all product attributes together as a set, and based on their perceived utility, customers make decision about the offering purchase. As a result, these are those attributes, which enable the customer to fill his or her wants. What drives customer perception of attributes utility and ability to satisfy his or her wants are the personal values in life, which the customer is trying to satisfy and which guide his or her decision-making process. The central hypothesis of the means-end theory is that customers consider bundles of products attributes to be the instrument (means) for fulfilling desirable goals or values (ends) (Johnson, Herrmann, Huber, Gustafsson, 1997). The means-end theory argues, that customers make their decisions about the product purchase based on the knowledge gained during up to date consumption process, which is structured into so called means-end chains. These chains link product’s attributes, utility components
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and set of personal values into a process, which explains, what drives customer decision about the purchase and how the process is being conducted. Figure 3.1. The means-end model
attributes
concrete
abstract
utility components
functional
socio-psychological
set of values
instrumental
terminal
Figure 3.1. Johnson, Herrmann, Huber, Gustafsson, 1997 Attributes, which are products characteristics, can be divided into:
Concrete attributes – which include physical, chemical or technical properties of the product
Abstract attributes – which are as opposite to concrete attributes, non-measurable ones, they are one’s subjective perceptions about the products, e.g. aggressive line of the vehicle
Based on concrete or abstract attributes of the product, consumer evaluates its utility. There are two types of utility assessment, which are connected with two kinds of attributes:
functional utility is the assessment of the concrete attributes – therefore of physical characteristics of the product.
socio-psychological utility is connected with abstract attributes – usefulness and results of non-measurable attributes, e.g. thank to aggressive line of the vehicle customer will feel much younger, when driving the car.
Finally, the set of values is understood as series of individual standards, which remain constant over period of time and serve to formulate goals in life and put them into practice in everyday behaviour (Johnson, Herrmann, Huber, Gustafsson, 1997). In other words, personal
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values are the ultimate drivers of consumers’ behaviour and decisions. The values are split into two distinct types:
instrumental goals consist of moral (tolerance, responsibility, honesty) and achievement-oriented values (logical, intellectual and imaginative)
terminal values include desirable goals in life, which can be divided into personal values (inner harmony, maturity in love) and social values (global peace, national security).
Based on the means-end theory, consumers will choose products with attributes, which will produce desirable consequences – therefore will offer desirable utility components and will respond to customer’s personal values. For example, if social acceptability value is core to customer, than he or she will choose a car with high brand image, e.g. BMW, as driving the BMW will confirm his or her membership in a high class of society and will impress family, friends and colleagues and as a result will lead to feeling of social acceptability. Such customer will under any circumstance choose e.g. a Fiat brand, as this is brand has value or mass image and will not impress the others and therefore will not lead to social acceptability feeling or state. In general, consumers hold different personal values in their lives and based on those values, they make choices between offerings. Knowledge of customers’ values helps the organization to tailor its offerings to those needs and by that respond to them better than competitors. As the end result, such action will ensure that organizations’ product, not the competitors’ is chosen and that customers’ satisfaction is brought to higher levels. In more detail, all customers of a particular company have diverse values and needs. As a result of such heterogeneity between customers, only differentiated offerings are able to satisfy customer’s diverse needs. Specifically, based on the knowledge of customers’ personal values and needs, a firm’s clientele shall be divided into groups, which will be homogenous inside and heterogeneous between the groups. Only such segmentation will enable to:
deliver products tailored to needs of each customer segment
lead to higher satisfaction of firm’s clientele.
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Therefore before satisfaction measurement system is implemented, creative and flexible research methods shall be used to discover the hidden needs and values of customers. Most often qualitative methods used for this part of research are focus groups, face to face interviews, surveys, laddering methods etc. After knowledge of customer personal values is gained, satisfaction measurement system shall be implemented, as it is the most informative tool to measure the extent, to which product attributes are able to respond to customer needs. 3.2. Rationale for development and use of industry or nation universal customer satisfaction measurement indexes Thank to knowledge of customer’s needs, company is able to evaluate, how well its current offerings serve customer needs. Such evaluation shall be done with use of customer satisfaction measurement system. Satisfaction measurement system is a crucial part of customer research helpful in diagnosing customers’ satisfaction levels. Such findings are good guidance about areas of products performance, which shall be improved in order to lift the satisfaction to the next level. Many companies have been measuring satisfaction levels on continuous basis. It has been done in more or less advanced manner and most probably many tools – mainly qualitative - were developed to measure customer satisfaction. However regardless of the advancement of methodology used by single companies, satisfaction measurement systems developed for a single organization have major limitations. First of all, measurement systems of that kind can not verify whether satisfaction index equal to 80 is a “high” or “low” result, as there is no benchmark. As companies build satisfaction measurement systems based on different methodologies and measurement indexes, which are tailored to only this organization’s competitive environment, results are not comparable between the organizations. It means that satisfaction index of 70 scored by company A’s may be in reality higher result than index of 80 reached by company B provided that both companies use different satisfaction measurement systems. Secondly, such indexes deliver results, which are not comparable within the industry. It implies that it is not possible to say, whether index of 80 is “good” or “bad” result on industry level, as there is no average for industry available. Therefore, it can not be assessed if companies in industry A satisfy their customers better than companies in industry B. 32
Finally, without unified, industry or even nation wide index, satisfaction levels can not be compared across companies from other industries, sectors or other countries. To summarize, without usage of industry universal index, an organization can only monitor progress and dynamics of its customer’s satisfaction over time. Such firm is even not able to say, whether the score is on high or low level. What is more, there is no benchmark to competition, not to mention industry or other economies. In order to respond to such limitation and enable comparisons, nation and industry wide measurement models were developed in various countries and continents. The ones that are perceived as pioneering ones and which laid ground for further development of satisfaction models were: 1. Swedish Customer Satisfaction Barometer – SCSB 2. American Customer Satisfaction Index – ACSI 3. European Customer Satisfaction Index – ECSI
3.3. National Customer Satisfaction Indexes 3.3.1. Swedish Customer Satisfaction Barometer First national customer satisfaction index was developed in Sweden in 1989. It was designed in such a manner, that it enabled for estimating satisfaction index on the level of company and total industry. As a result, it enabled to make comparisons of satisfaction measurement results between companies, but also industries. Since SCSB establishment, data was collected annually. Every year customers of about 100 companies from 30 leading industries were contacted for the interview, what resulted in ca. 25 000 respondents answering to the survey questionnaire every year. Respondents were contacted via telephone and during ca. eight minute survey they were answering to the questions using 10 point scale (Fornell, 1992). The customers evaluated their satisfaction with organizations offerings on the brand level. However, if a company was selling multiple brands, only the largest brand was chosen to represent the company.
33
After data collection results of the survey were analyzed using partial least squares methodology, which details will be described in further chapters of this paper. The structure of the original SCSB model is presented in the below figure. Figure 3.2. The SCSB (Swedish Customer Satisfaction Index)
Perceived Performance (Value)
Customer Complaints
Customer Satisfaction (SCSB)
Customer Expectations
Customer Loyalty
Source: Fornell, 1992 In each satisfaction measurement model, which will be discussed within the course of this work, satisfaction is central variable and has its antecedents and consequences. What is more, usually all or majority of variables in the model are latent variables – variables, which can not be observed separately. Each of the latent variables is described by set of observable variables. Within the SCSB model, satisfaction is a function of only two antecedents – expectations and perceived performance. This part of the model is based on the performance model described in the chapter 2.2 of this paper. Expectations are defined as what customers expect regarding the product performance – how well, they believe, the product or service will perform. In the SCSB model, expectations play an important role as determinants of satisfaction. According to the model, they shall positively influence the perceived performance, as customers learn from experience and based on the knowledge form expectations towards a product performance. Moreover, as
34
expectations forecast firm’s ability to provide future performance, it is argued that expectations shall have positive impact on satisfaction (Andreassen, Cha, Gustafsson, Johnson, Lervik, 2001). The SCSB model lays heavy importance on confirmation / disconfirmation of expectations, as driver of satisfaction. Expectations are not only included as a separate construct, which influences perceived performance and satisfaction, but discrepancy of expectations is also part of definition of satisfaction construct. In the SCBS index expectations are the observable variable, operationalised by just one question. Second driver of customer satisfaction in the SCSB model - perceived performance (value) is defined as relation of product price to product quality. This variable is described by two measures:
quality given price
price given quality.
In other words, authors of the SCSB model believe, that customers evaluate product’s performance by comparing the quality of the offering versus price paid and price paid versus quality of the offering. Perceived performance is expected to positively influence customer satisfaction – when it increases, so does the satisfaction. Satisfaction variable in the SCSB index described by three measures: 1) general satisfaction, 2) confirmation of expectations, 3) the distance from the customer’s hypothetical ideal product or service (Fornell, 1992). Such defined satisfaction is expected to have two immediate consequences – customer complaint and customer loyalty. Customer complaints are measured by two variables – complaint to personnel and complaints to management. Similarly, customer loyalty is also operationalized by two variables: (1) tolerance to price increase – how much more the customer is ready to pay provided that he or she is likely to repurchase, (2) declared repurchase intention. Such consequences of satisfaction are derived from previously discussed Hirschman’s exit – voice theory. Based on it, if a customer is dissatisfied, he or she may either stop the relationship with a company (exit) or complain (voice). Within the SCSB model, there is 35
relation between customer complaint and customer loyalty. The authors of the model suggest that, if the company develops proper complaint handling system, the complaining customers may turn into loyal ones. However, if the company does not handle complaints, customer exit is likely. The SCBS model, as the first national satisfaction measurement system, delivered few key findings, which were later often discussed in the literature. Firstly, the SCSB index turned out to be higher for industries, where: 1. offerings were differentiated and customer demand was also such, therefore match between supply and demand was possible. An example is an automobiles industry, where heterogeneous demand was satisfied by differentiated offerings and this industry in 1991 scored 78 on satisfaction index. 2. needs and supply were homogenous – basic foods (milk, sugar) scored also highest results in 1991 – 78 as in case of automobile. Secondly, lowest satisfaction levels were visible for industries, where heterogeneous demand could not be matched by supply, which was not differentiated. Good example of such industry is television broadcasting, which received one of the lowest scores of SCSB index – 48. Finally, it was apparent, that services received lower scores on satisfaction index than products (Fornell, 1992). The Swedish Customer Satisfaction Index, as the first truly national satisfaction measurement system, laid ground for development of the indexes in other countries, as well as other continents. 3.3.2. American Customer Satisfaction Index Second national satisfaction measurement index was developed in United States in 1994 and was named The American Customer Satisfaction Index. The methodology of the ACSI was based on the SCSB, however due to size of American economy, was applied to larger number of companies, industries and sectors. The largest companies from industries representative to major industry groups, which were chosen from seven major economic sectors were included in the design of the sample used in ACSI research. As a result, in 1994 ACSI research covered more than two hundred companies from over forty industries in the seven major consumer sectors of the economy (Anderson, 36
Bryant, Cha, Fornell, Johnson, 1996). Within each company approximately 250 interviews with company customers were conducted. Respondents were supposed to answer brand or model level questions using 10 point scale. As in case of SCSB, partial least squares methodology was applied to the analysis of the results from the survey. The structure of the ACSI model was based on the SCSB, however there were few differences regarding model structure, but also measurement properties of the model. Figure 3.3. The American Customer Satisfaction Index (ACSI) Model
Perceived quality
Customer Complaints
+
-
+ Customer Satisfaction (ACSI)
Perceived value
+
+
+ Customer expectations
+
Customer Loyalty
Source: Anderson, Bryant, Cha, Fornell, Johnson, 1996 The major improvements in the ACSI versus SCSB models are as follows: 1. Expectations variable is explained by three observable variables - as opposite to SCSB, where it was measured by only one construct. 2. Perceived performance (value) construct used in SCSB model was replaced with two separate constructs – perceived quality and perceived value. The first one measures the influence of the quality and the second one the influence of the price on
37
customer satisfaction. Such modification enables to evaluate, whether satisfaction in certain companies or industries is more driven by price or by quality of the offering. Perceived value variable was described by two questions – quality relative to price and price relative to quality. Perceived quality variable is measured by three questions, which enable to confront the product or service actual performance versus expectations held by customer before the purchase. 3. Customer loyalty is described by one extra variable as compared to SCSB index – the additional variable is supposed the give answer to the questions, of how much the price would need to be discounted to encourage the customers to repurchase, provided that they are unlikely to repurchase. Findings from ACSI index contributed greatly to explanation of satisfaction concept and its consecutive driver - loyalty. In general, in line with findings from SCSB index, the ACSI Model confirmed, that satisfaction is greatest in goods, lower in services and definitely lowest in public administration. However, satisfaction scores for goods and services were higher in ACSI than in SCSB. Referring to literature, satisfaction levels are expected to be higher when competition, differentiation, involvement, or experience is high or when switching cost, difficulty of standardization or ease of evaluating quality is low (Anderson, Bryant, Cha, Fornell, Johnson, 1996). Authors of ACSI model used those findings to conclude, that satisfaction is higher in U.S. compared to Sweden due to higher differentiation and competitiveness in U.S. To comment further on that conclusion, it shall be also taken into consideration, that cultural and psychological conditions may to large extent explain those differences. As Americans are much more optimistic than Europeans on average and Swedes in particular, this shall in general predispose Americans to choose higher scores on the scale, when responding to survey questionnaire. Furthermore, the ACSI model delivered important findings, which explain the complex theory of satisfaction and loyalty. Specifically, there were three major conclusions from the ACSI Model (Anderson, Bryant, Cha, Fornell, Johnson, 1996): 1. Customization of an offering (how well does the offering fit the personal needs?) is more important than reliability of the offering (how often has the things gone wrong?). Naturally, customization is more important for services than manufactured goods, however it still implies that tailoring the product or service to customer’s needs shall have larger impact on perceived quality and satisfaction than standardizing the 38
offerings in order to ensure greater reliability. 2. Expectations have stronger influence on perceived quality and perceived value for industries, where there is relatively low variance in consumption and production – and where customers make routine purchases. Once the variance in offerings is large and so is variance in consumption, than expectations shall have weaker impact on perceived quality and price. As a result, expectations impact turned out to be lowest in manufacturing durables, finance/insurance and services. The same conclusions were valid with regards to expectations influence on satisfaction – lowest impact was observed in manufacturing durables and finance/insurance. Simplifying, the latest quality experiences with an automobile or insurance play more central role to satisfaction than expectations held before purchase. If a customer is more engaged in the decision process and the purchase, product performance will influence to larger extent his or her satisfaction than the expectations held before the purchase and before the experience with the offering. 3. Based on ACSI Model, quality has larger impact on customer satisfaction than value. As long as value concept plays important role in customer attraction and during decision-making process, quality is more important in satisfying the customer and therefore predisposing him to be loyal and retain with a company. There were industry differences visible; price-driven satisfaction was highest for non-durables, while lowest for durables, services, retail and government agencies. Implication from this finding is such, that in maturing economies, where industries are saturated, where supply is heterogeneous where acquiring the customer is extremely difficult and in practice very often equals taking over competitor’s customer base, quality is crucial and is much stronger predictor of customer loyalty and therefore probable repeated purchase than price. The ACSI Index was widely commented after its creation and it was also tested and applied in many empirical studies. It also laid ground for development of European based index called the European Customer Satisfaction Index (ECSI). 3.3.3. European Customer Satisfaction Index The goal of ECSI development was to supply European companies and countries with similar diagnostic tool as American counterparts have been using since 1994. Moreover, development 39
of similar index enabled the comparisons between countries within Europe, but also between Europe and North America. The ECSI model was developed and tested for the first time in 1999, while second round of research was carried out in 2000 with minor changes implemented to the original model. Twelve European countries participated in the 1999 project. In terms of industries covered by ECSI model, telecommunication was included in the research in all markets, while retail banking and supermarkets in almost all participating countries (Juhl, Kristensen, Ostergaard, 2002). It was also possible to include sectors of special interest in single markets, as it was in case of Denmark. For majority of companies in each country, about 250 of their customers responded to the telephone survey. As a result, almost 55 000 interviews were held in 1999. The ten point scale was used in the survey however results were afterwards adjusted to ACSI 1-100 points scale to enable comparisons between ACSI and ECSI index. Figure 3.4. The European Customer Satisfaction Index (ECSI) Model
Image
Expectations
Perceived quality of „hard ware”
Perceived value
Customer satisfaction
Perceived quality of „human ware”
Source: Juhl, Kristensen, Ostergaard, 2002
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Customer loyalty
As discussed previously, ECSI methodology was based on ACSI model. As in case of SCSB and ACSI models, partial least squares methodology is used for estimation of the model. Furthermore, as in case of ACSI, all variables are latent ones operationalized by few measurement variables – specifically by two to six variables (indicators), which are translated into specific questions asked during the survey. With regard to ECSI model structure, ACSI was an exemplar for ECSI construction, however the latter one is different due to three constructs: 1. within ECSI model, image variable was included, which is expected to influence perceived value, satisfaction and customer loyalty variables 2. perceived quality was divided into separate variables;
a product quality – so called “hard ware quality” – which describes performance of the product/service attributes
a service quality – so called “human ware quality” – the quality of service delivered to the customer (Juhl, Kristensen, Ostergaard, 2002)
3. Customer complaint variable was excluded from the ECSI model as compared to ACSI index. There are also differences compared to ACSI model with regard to variables measuring loyalty construct, which is the ultimate variable explained by the model. Within ECSI model, loyalty is measured by following questions: (1) the product repurchase likelihood, (2) the probability of buying another product from the same company, (3) intention to switch to competitor – price tolerance (4) intention to recommend the offering to other consumers (Gronholdt, Kristensen, Martensen, 2000). The difference in loyalty variable compared to ACSI lies in second and fourth question. Within ACSI first question was the same as in ECSI, however the other two questions in ACSI regarded price tolerance, while in ECSI only third question is dedicated to price tolerance. The remaining ones in ECSI examine the probability of purchase extension to other offerings within the same company, probability of positive word of mouth and probability of product repurchase.
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Among results of ECSI pilot study from 1999 several key conclusions were drawn, from which there is one applicable to Polish economy and business environment in which Company X is operating. The analysis of results for Denmark revealed that the link between satisfaction and loyalty is stronger in competitive industries. In other words, the positive effect of customer satisfaction on loyalty increases with the degree of competition in the market (Gronholdt, Kristensen, Martensen, 2000). This conclusion is extremely crucial for Company X, which operates in highly competitive automotive industry. Based on this finding, it is important, that Company X tries to increase customer satisfaction as such increases shall be strongly reflected in growing customer loyalty. In general, increasing loyalty has measurable, positive effects for business performance. Specifically, there are few key results of increasing customer loyalty for company results: 1. Increasing revenues due to customer retention and repeated purchases 2. Costs decline, as there is no need to acquire new customers, because the current ones stay with the company, so the costs connected with new customers acquisition decrease 3. Employee retention increases as a result of job pride and job satisfaction. As the relationship with customers and familiarity of their needs is sustained customers are served better and therefore their satisfaction and retention increases. Increase productivity results from increasing employee tenure (Hopton, Markey, Reichheld, 2000) As the increased loyalty has such strong influence on business performance, and satisfaction influence on loyalty is stronger in competitive industries, therefore it is of utmost importance for Company X in Poland to make customer satisfaction its priority goal. The Customer Satisfaction Indexes described so far in this chapter – SCSB, ACSI and ECSI are the most important indexes developed so far and used for measuring customer satisfaction and customer loyalty. They are universal methodologies and can be applied to various industries, sectors and on various markets. As a result they allow for comparisons of results and benchmarking between companies, industries and results. However, specific industries often tailor satisfaction measurement studies to the specifics of the concrete industry or even company.
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3.3.4. Automotive industry specific customer satisfaction indexes Within automotive industry, which lies at the heart of this paper, J.D. Power and Associates is the most important and most referred to marketing information organization, which measures the customer satisfaction in the automotive industry. J.D. Power is an independent and unbiased source of customer satisfaction, product quality and buyer behaviour researches. As it is global company, it measures customer satisfaction with brands in many countries what enables companies to compare results on local and regional level. J.D. Power provides following syndicated reports, which deliver information for automotive industry and which are widely used within automotive companies: 1. Initial Quality Study (IQS) 2. Sales Satisfaction Index (SSI) 3. Customer Satisfaction Index (CSI) 4. Automotive Performance, Execution and Layout (APEAL) 5. Vehicle Dependability Index (VDI)
Initial Quality Study Initial Quality Study (IQS) is a research, which is supposed to evaluate the automotive quality after three months of usage. During the study respondents are asked to asses the quality of the car with regard to:
design – problems with design include car components or features, which may be working right, however they may be perceived as difficult to use or understand
defects / malfunctions – this kind of problems include complete breakdown of any component or car feature.
In the course of the study 217 car attributes are evaluated with regards to its functionality and reliability. As a result, the study reports number of defects and malfunctions per 100 cars at the level of whole brand, but also at the model level. IQS study is conducted annually and has been is use for the past twenty years – since 1987. It serves as benchmark for evaluating new vehicles quality. 43
In the latest, 2007 release of the study, 97 000 purchasers and lessees of new car models launched in 2007 were surveyed ninety days after the purchase. Within this study, Company X scored enormous improvement as a total brand with regard to quality of the vehicles. In the ranking of the brands with lowest rate of faults, it advanced by more than 10 positions. Moreover, such substantial increase was driven by all models and such results have been described by Neal Oddes, director of product research and analysis at J.D. Power and Associates as Company X commitment to quality (http://www.jdpower.com ). Company X as a whole brand received the highest quality ratings with regard to: body and interior quality – mechanical, overall quality – mechanical and power train quality – design. Sales Satisfaction Index Another important J.D Power study, widely used within automotive industry, is Sales Satisfaction Index (SSI). It has also been in use for the past twenty years. As opposite to IQS, which measures automotive quality itself – therefore referring to ECSI it measures “human ware quality”, SSI evaluates the customer satisfaction with dealers and vehicles, therefore so called “hard ware quality” as defined in ECSI. In more detail, it covers the area of sales moment – therefore this is an evaluation of customers’ first experience with the company. Specifically, it evaluates customer satisfaction in five dimensions: dealership facility, salesperson, paperwork/finance process, delivery process and vehicle price (http://www.jdpower.com). This implies that SSI results in evaluation of “human ware quality” to larger extent than “hard ware quality”. The 2007 results of SSI study are not available however in 2006 Company X was positioned in top ten in ranking of automotive brands, whose customers are most satisfied with the car purchase process. Company X scored much above the average for the industry, which in 2006 amounted to 847 points (http://www.jdpower.com ). APPEAL Automotive Performance, Execution and Layout Study (APEAL) is the latest study offered by J.D. Power, as it is in use only since 1996. This is also the only study, which measures the emotional side of car ownership – it examines what customers feel about their cars. The study was designed to complement the IQS study, which concentrates on the quality, while APPEAL on the owners delight with car design, content, layout and performance. 44
The respondent in the study are car owners, who have been using their car for only 90 days. During the research, respondents are supposed to evaluate their cars on more than 100 attributes,
which
engine/transmission;
cover
eight
ride,
categories
handling
and
of
vehicle
braking;
performance
and
design:
comfort/convenience;
seats;
cockpit/instrument panel; heating, ventilation and cooling; sound system; and styling/exterior. The 2007 survey was based on responses from more than 91 000 car purchases and lessees of new 2007 model-year cars and trucks, who purchased their vehicles ninety days earlier. The results of the APEAL study were extremely satisfactory to Company X brand. The brand received highest scores in four out of five measured areas. Such result can be translated into high profitability of the brand, as based on the results from the 2007 study results, manufacturers and dealers of models with higher APEAL scores can offer lower incentives to new-buyers (http://www.jdpower.com). Vehicle Dependability Index One more study offered by J.D. Power and Associates is the Vehicle Dependability Index (VDI). The study is designed to evaluate the long-term experience with a vehicle, as it measures the quality after three years of car ownership. The study covers such areas as durability of specific items, frequency of warranty work, ratings of the work performed and the amount spent on non-routine repairs during the past year (Johnson, Herrmann, Huber, Gustafsson, 1997). Therefore the index is a solid insight for the consumers of the model’s reliability and dependability within the warranty period. Customer Satisfaction Index Finally, J.D. Power could not lack customer satisfaction index in its portfolio - it is called Customer Satisfaction Index (CSI). As all indexes described in previous chapters, the J.D. Power CSI index is supposed to measure the level of customer satisfaction with the car usage during the first three years of the automotive use. The CSI index is composed of variables, while each of them is measured by few questions. Based on results released for German market in 2005, the four variables explaining customer satisfaction are:
quality and reliability of vehicle - covers problems with vehicle,
vehicle appeal – means satisfaction with the vehicle’s performance, design, 45
function and styling
service satisfaction – is understood as customer satisfaction with dealership and service
ownership costs – cover costs of car use, insurance and repairs
J.D. Power vehicle quality and satisfaction measurement studies are used widely among automotive industry organizations. They enable to evaluate satisfaction levels and benchmark them against competitors. Moreover, J.D. Power methodologies, as external ones, are objective in measuring and evaluating satisfaction levels. Therefore they are good indicator of direction, into which automotive firm is heading in terms of vehicle quality, performance, brand image and sales services, which are prerequisites for customer satisfaction, which in turn impacts organizations financial results.
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4. COMPANY X CUSTOMER’S PROFILE Nowadays, majority of companies are conducting mainly qualitative research which measures customer’s values, needs and beliefs. Such qualitative methods are also used to measure consumer demographics. Company X in Poland conducts an annual research with the external agency, which supplies the company with following information: 1. consumer demographics and interests 2. benefits driving the car purchase 3. reasons for vehicle purchase and attitudes towards the car The research is conducted on yearly basis since 2002 by the same research agency, what allows for results comparisons and trends observations. The study, which results will be cited in the next chapters, was conducted in autumn 2006. The research uses mail questionnaires as a data collection methodology. In last year wave there were 326 respondents, who returned the filled questionnaire. Within this chapter, we will present analysis of the results of 2006 wave, which will describe the demographic profile, but also personal needs and values of Company X car owners. 4.1. Company X customers – demographics In general, the analysis of demographics from the 2006 survey allows for customer segmentation into groups, which are homogenous inside, while they differ between the groups:
Compact cars – users of smallest cars and at the same time the most affordable among all Company X models belong to this group,
Mid size cars – cars within this segment are larger and more comfortable than compact cars, and at the same time more expensive as well as more luxurious.
Full size and large cars – these are definitely the most expensive cars, largest ones and most prestigious and luxurious ones.
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Each of the segments can be described by seven dimensions: gender, age, size of household, occupation, income of the owner, previous experience with Company X cars, interests and hobby. Starting with gender, among Company X car owners, 75% of clients is male. Across the segments, there is correlation visible between gender and car size – the larger the car, the larger percentage of men owners versus women. Therefore, largest percentage of women owners is in the compact cars segment, where 32% of the car owners are women versus 25% for the total brand. Contrary, in full size cars segment, 89% of car owners are men. Such results are very natural – the smaller the car, the more appealing to women. As a result compact cars are most often in the possession of women, while only few of them (11% of total population of full size cars owners) own models from full size segment. As Company X cars are premium ones, they are sold at correspondingly high prices and therefore younger consumers in majority can not afford them. This is reflected in the age structure of Company X owners – 78% of respondents are in the age of 29 to 58 years. Another conclusion applicable in the analysis of age structure of respondents is that the smaller the car and therefore more affordable, the youngest and the oldest consumers are driving it. Within the owners of compact cars, there is largest percentage of youngest (below 29 years old) and oldest respondents (above 59 years old) as compared to other segments – 7% and 16% respectively. Such observation is related not only to the fact that disposable income of youngest and oldest consumers is relatively lower than of mid age consumers, but also to the fact, that compact cars are proper size cars at youngest and oldest stage of life, as respondents at this stage of life usually don’t have the children yet or already don’t have children dependent on them. The Company X car owners most often have four members in the family (over 50% of respondents). However, within compact cars segment, 2-persons families are statistically more often. This finding is in line with the analysis of age structure – the youngest and oldest customers are most often driving compact cars, as they are of comfortable size for their twoperson household. The largest group among Company X customers are managers - entrepreneurs (private companies’ owners), managers, directors and business owners – 45% of respondents. Second 48
largest group is intellectuals (doctors, lawyers, scientists) – 22% of respondents belonged to this group. There were significant differences visible among segments; among compact cars owners, intellectuals were much more visible than in mid size and full size car owners. On the other hand, managers are largest group among owners of full size cars as compared to other segments. Such relation has its background in the income – as the managers are on average most affluent group, they are most likely to purchase full size car as opposite to less affluent intellectuals. The size of the car is reflected in its price, therefore the larger the car, the higher the price and as a result higher income of the owners. Such relation was observed in the analysis of income among Company X car owners. Respondents, who are driving compact cars, have on average lower income than mid size car owners and much lower than full size car drivers. Company X customers are split in half in terms of previous experience with the brand – 51% of respondents confirmed, that they have had a Company X car before the current one. On average more often men and persons working on managerial positions are within this group. Among customers, who had Company X car before, 30% had one car before, while remaining 70% had more than one Company X car before the current one. There were significant differences visible between customer segments with regard to previous experience with the brand. For compact cars owners, statistically more often current car is a first Company X car – this is valid for 62% of compact car respondents, who claim that compact car is their first one. This is opposite to full size cars owners, where for only 22% of respondents this is first Company X vehicle. Moreover, among full size cars owners, 77% of them have had more than two cars of this brand previously. Among those compact car owners, who had Company X before, only 51% had more than one such car before the current one. With regards to interests and hobbies, in general Company X customers are most interested with movies (56% of respondents), house and garden (56%), winter sports (40%), travelling (36%) and music (35%). It is important to note, that during the past four years (2002 – 2006), increasing interest with tennis was noted, while fewer respondents claimed, that they are interested in cooking. This observation is in line with the changes within culture and style of living in Poland and with increasing purchasing power of Polish consumers.
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With regards to differences between models owned and interests, the higher the car model, the more expensive the hobby. Compact car users statistically more often claimed that they are interested in cooking, house and garden, while they claimed lower interest in winter sports and golf. On the opposite side, full size car owners responded, that they are most interested in travelling, tennis, water sports and golf. Such differences are related to financial and social status – travelling or water sports definitely require more investments that interest in cooking, house or garden. On the other hand, sports such as tennis or golf are regarded as sports for people from upper classes of society, those with higher income and such hobbies are regarded as prestigious ones. Therefore full size car owners will more often declare interest in golf or tennis, than in cooking, house and garden. Summing up the analysis of demographic characteristics of Company X car owners, the main conclusions from analysis are:
Company X cars are more appealing to men, as every 3 out of 4 respondents is men. Female respondents are most often driving the smallest models of Company X – compact cars. This implies that if Company X wants to target women, it shall concentrate on offering smaller cars, while the larger cars shall be offered rather to male customers.
As Company X cars are premium ones, therefore they are affordable at maturity stage of life, when disposable income is relatively larger – 78% of respondents are in the age of 29 to 58 years. Therefore marketing efforts such as communication, marketing campaigns shall be focused on places, media channels, which are most often used by respondents in such age. However, if there is desire to attract younger customers, than smaller models shall be offered to them, as these are the ones that this target group can afford.
As Company X cars are premium cars, customers most often purchase compact car as their first car of this brand – 62% of compact cars owners declare, that this is their first vehicle of Company X, while only 22% of full size cars owners confirm this statement. This implies that to gain new customers, compact cars will be the best incentive. Furthermore, to overcome high price barrier, promotional tools shall be used with the offer of smallest cars, as they shall be most effective in case of new customers. On the contrary, clients who decide to purchase larger models as their first Company X car are affluent enough and as a result price incentives will rather not 50
be effective tool to attract their attention.
Company X shall target mainly managers and intellectuals with its offerings – 67% of respondents belong to those two occupation groups. It shall be noted however, that offerings which will meet intellectuals’ needs are those placed in the compact car segment, as they are the affordable ones for this group. Contrary, managers shall rather be targeted with mid-size and full size cars, as these are the ones affordable by this group, but also the ones, which are more prestigious to drive.
As owners of Company X cars are mainly in their mature life stage, most often four persons live in their household – two adults and two children. This implies, that Company X shall offer solutions friendly to families – comfortable sizes of trunks, foldable back seats to fit more luggage if necessary.
With regard to income of respondents, compact car owners are on average less affluent than respondents, who drive mid size and full size cars. Therefore offerings for compact cars customers shall deliver more value for money, as these customers will be more price sensitive than owners of mid size of full size models.
The analysis of Company X customers’ demographics showed also, that there is justification for segmentation of respondents into three groups – compact cars, mid size cars and full size cars, as respondents within these groups are homogenous. The differences between respondents within each group and the average for total Company X are as below:
The average Company X client is male (75% of respondents) in the middle age – from 28 to 58 years old. Every second respondent lives in a four persons households (50% of customers). Almost half of Company X clients are managers, while almost 20% of them represent intellectuals’ group. Company X customers most often agree that their hobbies are movies, house and garden, winter sports, travelling and music.
Compact cars owners – in general, this group differs a lot from mid and full size car owners. Compact car drivers are mainly youngest or oldest customers (below 29 years old or above 59 years old). Majority of this group belongs to intellectuals, pensioners and students. Within this group, two person households are much more often present than in other groups. Compact car drivers have also the lowest income compared to other groups – as they are either youngest or oldest persons, therefore least affluent. Statistically, women more often drive and own compact cars than other
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models. Respondents within this group have only started their adventure with Company X brand – within compact cars owners there is largest percentage of customers who declare, that this is their first Company X car. In terms of interest and hobbies, respondents within this group declared more often than customers within other groups that their hobbies are those least demanding in terms of financial input – cooking, house and garden.
The profile of mid size car owners is most similar to average demographic profile of Company X customer. 80% of customers within this group are men. They are in their maturity stage of life, being between 39 to 58 years old (64% of respondents). Their households are of traditional size – three of four persons. Almost half of the customers in the mid size car segment are managers (45%) followed by intellectuals. Their income is on the level of average income observed for Company X customers. For 50% of customers within this group current Company X car is not the first one – they have had a car of such brand previously. In terms of interests, customers within this group statistically more often claim interest in pop music, tennis and soccer.
The owners of full size models differ a lot compared to compact car drivers, but there are similarities to mid size cars owners. The owners of full size Company X cars are in almost 90% men. As in case of mid size car owners, they are most often in the age of 39 to 58 years old – within this group there is lowest percentage of youngest (below 29 years old) and oldest (above 59 years old) respondents. They are well settled in life – in majority they work as managers and their income is the highest among Company X customers. Customers within this group have larger families – most often four persons within the household. Furthermore, as they are the wealthiest group, they have largest experience with the Company X cars – 78% of customers from this group have had Company X car before. Customers within this group statistically more often declare, that they have either expensive or prestigious hobbies and interests – they are more often than other customers interested in travelling, tennis, water sports and golf.
The differences between three core groups of Company X customers deliver important knowledge to the management, which enables to target each customer segment with such offer, that it is adjusted to each customer profile and by doing so maximize the probability of satisfying the customer. The analysis of factors, which drive the decision of car purchase,
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shall deliver more detail knowledge of customer needs and values, which shall further enhance the knowledge of differences between customer segments.
4.2. Company X customers – benefits driving the car purchase During the annual customer research, not only customer profile is measured, but also Company X customers are questioned to point out three most important benefits, as well as factors, which are crucial in their car purchase decision making process. Respondents are asked to choose three most important benefits from the list of fourteen, which are the most important for them when deciding about the car purchase. The benefits and factors used in the survey are: 1. Safety of the vehicle 2. Comfort of the vehicle and delight from driving 3. The technological advancement of the car 4. The brand image 5. The unique design of the car 6. Previous experience with the brand 7. High expected return if car is sold after few years 8. Functionality and economy of the car 9. Prestige due to car ownership 10. Recommendation from a friend regarding the car 11. Promotion or advertising influence 12. The environment friendliness of the car 13. After sales services 14. Other reasons The results of 2006 survey revealed, that in general there are four benefits, which where chosen most often as the crucial ones for Company X customers:
safety of the car – 59% of respondents pointed this factor as one of most important, when purchasing the car
comfort of the vehicle and delight from driving – 56% of those asked pointed this benefit as very important 53
technological advancement of the vehicle – 28% of respondents believe, that this benefit is crucial factor, when purchasing the car
brand image – this benefit was chosen by 27% of Company X customers
On the other hand, the least important factors for Company X customers, which are able to influence the decision about car purchase, were:
after sales service – only 1% of respondents believes, that this is important factor, which is taken into account while making decision about car purchase
the environment friendliness of the car – was also chosen by only 1% of customers
promotion or advertising – this factor was taken into account by only 2% of Company X car owners, when making the decision about the brand they want to drive
These results have crucial implications and are important advices for Company X managers. First of all, based on the survey, safety of the car, comfort and delight from driving are the key benefits that Company X cars shall deliver to their owners. These are also the key car features, which if performed on high level, are able to attract future consumers and retain current clientele. Furthermore, these features shall be claimed in any promotional materials and advertising, as their importance is so high to Company X clients. Secondly, if Company X has any issues with quality, which leads to lower safety, less comfort or lack of technological advancements, than it can expect declining number of customers attracted or the customer exit to happen, as the most important benefits will not be delivered to the customers. Finally, as promotion and advertising factors are least important for Company X customers, those tools shall not communicate promotional activities – attractive pricing or discounts. The advertising shall rather be used for image building, as image is one of the most important factors for Company X clientele. Therefore, instead of communication of promotional incentives in media, advertising shall communicate brand benefits and in this manner enhance the brand image further as the factor taken into account by 27% of respondents during car purchase decision making process.
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The 2006 study revealed the differences between various models owners – other benefits were pointed out as the most important by different model owners. As a result, three customer segments divided based on demographic characteristics may be described by other benefits, which are on average more important for them during decision-making process. Compact car owners pointed out more often than other models owners to safety of the vehicle, brand image and functionality and economy of the car as benefits important to them during the car purchase decision process. The larger sensitivity to those factors is related to demographic profile of compact cars customer segment: 1. Functionality and economy of the car; as discussed before, compact car owners are the group with smallest disposable income. Therefore functionality and economy of the car is on average more important to them than to any other customer segment, as their funds are more limited than funds of other Company X customers. 2. Safety; Company X cars score five stars in the Euro NCAP safety ranking and are perceived as safest cars. Safety benefit does differentiate Company X from other brands and has been pointed out by 59% of Company X customers as very important. However, safety benefit was chosen more often by compact car owners, than mid size and full size car drivers. Such difference is also related to demographics. Compact car owners are the youngest and the oldest customers of Company X and very often compact car is their first Company X car. While comparing the options on the market, they are searching for safe vehicles and if a car is described as very safe, this feature may be decisive for them to choose this particular brand. Therefore Company X cars are more appealing to them than any other brand, as they are perceived as the safest. For mid size or full size cars owners’ safety is more of a granted benefit, as they most often have been driving Company X before. Furthermore, as they are more wealthy customers and they are driving more expensive cars than compact ones, they are searching for other benefits than just safety, which is important, but basic one for them. For the same reason safety is more important for compact car users – as they have the smallest income, they can afford smallest Company X cars and those delivering basic benefits, such as safety. On the other hand, those basic benefits are the ones that compact cars owners are searching for – safety, but also reliability and economy of the vehicle. 3. Image; this benefit is more important to compact size owners than other segments for 55
several reasons. First of all, compact car customers are the youngest and the oldest groups and very often they did not have previous experience with Company X. Therefore, image benefit acts as strong differentiating feature, which makes Company X car more attractive than other brands. Than, as this may be the customer first Company X car, the desire to drive a high image, admired brand car is larger than for customers, who are driving Company X for longer time. For such clients, the desire to drive high image brand has been fulfilled before and therefore is not perceived as important now. Contrary, for compact cars owners, image benefit may be very important, as this may be their first premium brand car. To summarize, customers within compact cars segment perceive safety, functionality and economy of the vehicle, as well as image of the brand as more important factors than mid size and full size cars segments. The skewness towards such benefits is partly related to demographics of the compact car owners; 1) lower income of compact car owners, therefore more focus on basic benefits such as safety, reliability and economy, 2) as the compact cars owners are the youngest or oldest customers, it is very often their first Company X car. As a result safety and image of the car, which strongly differentiates Company X from other brands, push this group towards purchase of Company X, 3) as this may be their first Company X car, the desire to drive high image car may be stronger than for mid and full size car owners, for which this is next Company X model and they are used to such high image cars. Based on the benefits, which are on average more important for compact car owners, this customer segment can be described as functional segment. Mid size cars owners on average pointed more often to comfort and pleasure of driving than other customer segments. At the same time, functionality and economy of the vehicle was chosen very seldom by this customer segment. Such discrepancies are also related to demographic characteristics of this customer segment. Customers within this group have higher income than compact car users and are better settled in life. They are also more often managers, therefore handling high positions within the company, which are associated with higher standard of life. As a result, mid size car owners can choose vehicles, which offer comfort, delight of drive and some portion of image to the users. Those customers take functionality of the vehicle for granted and do not put so much 56
attention into economy of the vehicle, as they can afford higher expenses. They are searching for pleasure, comfort and delight when driving. As a result, mid size car segment can be called pleasure segment, as customers within this group value the delight higher than the functionality. The benefits which were on average more often chosen as the most important ones by full size cars owners were pleasure and comfort of driving, previous experience with the brand and prestige of car ownership. The full size car owners are most affluent customers of Company X. Therefore pleasure and excitement of driving is very important for them and this is why they choose the largest, most expensive and most luxurious models. Furthermore, prestige is important for this group, as these customers are mainly managers, well settled and affluent, therefore they need to be surrounded by prestigious products - with cars between them. Lastly, the current model is not their first Company X car. Those customers have experience with other Company X cars and as a result it influences their decisions about the car purchase. The full size car owners may be called as prestige segment due to benefits, which were pointed by them on average more often than by other customers. The analysis of key benefits, which are most important for Company X customers during the decision about car purchase, revealed that Company X customers can not only be segmented due to demographic characteristics, but also based on key benefits which they are searching for. Company X clientele can be segmented into three distinct groups: 1. compact car owners – so called functional segment. Customers within this group are more often than other customers searching for cars, which are safe, functional and economical and have high image. 2. mid size car owners – so called pleasure segment. Such customers focus more often on pleasure and comfort of driving than customers within remaining segments. 3. full size and large car owners – so called prestige segment. Clients within this segment are those most experienced with Company X and those searching for pleasure of car driving and prestige of car ownership The knowledge of key benefits, which are important for particular customer segments, enables the company to target each customer group with different car attributes which will 57
respond to different benefits. Such knowledge is of inestimable value in creating offerings tailored to customer needs, what in turn drives higher satisfaction and loyalty. 4.3. Company X customers – attitudes to vehicle During the survey, not only demographic characteristics of consumers and benefits driving car purchase were examined, but also general attitude to vehicle. Respondents were asked to agree or disagree with twelve statements describing their attitude to cars. The statements were ranging from “My car shall express my personality” to “I take care of my car myself”. The respondents were supposed to evaluate whether they agree with the statement (4) or disagree (1) or they have no opinion. In general, the statements, with which customers agreed to largest extent, corresponded with most important benefits taken into account during the car purchase process. Respondents to largest extent agreed with following statements:
“The vehicle shall guarantee maximum safety” – 97% of respondents agreed completely with this statement. This is in line with safety benefit, which was pointed out by largest percentage of respondents as important benefit taken into account during purchase decisions.
“I would like to have a feeling, that all latest technical advancements were used in the car” – 94% of those questioned agreed with this statement. This is in line with the technological advancements benefit, which was chosen 28% of Company X customers are key while making car purchase decision.
“I like the vehicles with unique design” and “The car gives me feeling of freedom and independence” – 92% of respondents agreed with both statements completely. This statement corresponds with two benefits; comfort and pleasure of driving, which was chosen by 56% of respondents as important for them and unique design, which is perceived as important factor during car purchase process by 27% of Company X customers.
There were some differences between customers’ demographics and their attitude to vehicle. In general, women are searching for cars, who give them sense of freedom and independence, which have unique design and which express their personality.
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When it comes to age groups, youngest consumers (up to 39 years old) enjoy dynamic driving more than any other group. On the opposite side are customers above 49 years old, who more often treat their car as locomotion only. With regards to differences between various customer segments, they were no strong differences. The only exception is the full size segment (prestige segment). Customers within this segment believe that the car shall reflect their social status and that it shall attract others attention. This is in line with the list of key benefits which are important for this customer group. As discussed before, customers from this segment are on average more often taking into account the prestige of the car ownership when they are making their purchase decisions. As customers within this group are most affluent ones and are most often on high managerial positions, naturally they will be searching for cars, which are prestigious because they believe that the car shall reflect their social status. 4.4. Summary of Company X customer’s profile To summarize the customer profile research study results from 2006, the analysis revealed, that Company X customers can be divided into three major groups. Customers within those groups are alike taking into account their demographic profile, their needs and attitudes towards vehicle. Moreover, those groups are similar in terms of car models that they choose. Contrary, the groups differ significantly between them. The characteristics of average Company X customer and specifics of the three customer segments are: 1. Company X customers in majority are men (75% of respondents) in the middle age – from 28 to 58 years old. 50% of respondent lives in a four persons households. In terms of occupations, almost half of Company X clients are managers, while almost 20% of them represent intellectuals’ group. Company X customers are most often interested in movies, house and garden, winter sports, travelling and music. The most often cited benefits or factors, which are important for Company X customers during car purchase are safety of the car, comfort of the vehicle and delight from driving and technological advancement of the vehicle and brand image. 2. Compact cars owners – functional segment. Among this segment, there is larger percentage of youngest and oldest customers (below 29 years old or above 59 years 59
old) than in remaining segments. Women are also driving compact cars than other models. Majority of this group belongs to intellectuals, pensioners and students and live in two person households more than customers from remaining segments. Compact car drivers have the lowest income compared to other groups and within this segment there is largest percentage of customers who declare, that this is their first Company X car. In terms of interest and hobbies, respondents within this group declared more often than customers within other groups that their hobbies are those least demanding in terms of financial input – cooking, house and garden. Customers within this group are more often than other customers searching for cars, which are safe, functional and economical and have high image. 3. Mid size cars owners – pleasure segment. 80% of customers within this group are men in the age between 39 to 58 years old (64% of respondents). They have households with three or four persons. Almost half of the customers in the mid size car segment are managers (45%) followed by intellectuals. Their income is on the level of average income observed for Company X customers. 50% of customers within this group have had a Company X car previously. In terms of interests, customers within this group statistically more often claim interest in pop music, tennis and soccer. Mid size car owners focus more often on pleasure and comfort of driving than customers within remaining segments. 4. Full size and large cars owners – prestige segment. Customers within this segment are almost only men (90%), in the age of 39 to 58 years old – within this group there is lowest percentage of youngest (below 29 years old) and oldest (above 59 years old) respondents. Full size car owners are in majority managers and their income is the highest among Company X customers. They also have larger families than average Company X customer – four persons within the household. Car owners within this group have largest experience with the Company X cars – 78% of them have had Company X car before. Customers within this group statistically more often than other segments declare, that they are interested in travelling, tennis, water sports and golf. They are also those most experienced owners of Company X and are searching for pleasure of car driving and prestige of car ownership. Furthermore, they more often than other customers believe that the car shall reflect their social status and that it shall attract others attention.
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5. STRUCTURAL EQUATION MODELING AND PARTIAL LEAST SQUARES Partial Least Squares approach is one of the data analysis techniques that is applied to similar problems as Structural Equation Modeling. PLS has been mainly developed by Herman Wold (Wold, 1985), Jan-Bernd Lohmöller (1984, 1989) and by Wynne W. Chin (1998, 1999, 2001). Some researchers claim that PLS is not one of the SEM methods due to different estimation procedures and objectives of the methods as well as different strengths and weaknesses of both techniques. On the other hand beside many differences both methods can be grouped under one set of techniques used to analyze similar problems with conceptually continuous latent constructs. 5.1. Structural Equation Modeling – covariance-based approach Many researchers identify SEM mainly with covariance-based approaches represented by such computer software programs as for example LISREL. This kind of approach is an evaluation of sample covariance or correlation matrix consistence with a theoretical model specified by the researcher. Therefore it concentrates on maximizing fit between sample correlations matrix and parameter estimates meaning that the estimating procedure changes the estimates to improve the fit function until no improvement is possible. The covariance-based techniques optimize parameters by maximizing fit but not variance explained. Therefore estimated models can have very good fit to sample data set which is crucial to interpretation however with low explanatory power. One of important limitations of this methodology is the assumption that the observations are independent and all indicators follow normal distribution which in most customer satisfaction studies is not fulfilled due to strong negative skewness of satisfaction scores. Furthermore SEM does not allow to predict value of latent variables specified in the structure of the model. This property is of high importance especially in customer satisfaction researches where calculation of latent scores is essential to further interpretation of the subject. To sum up covariance-based approaches are very demanding if it comes to distribution of the sample data set plus they concentrate on explaining covariation of all used indicators to prove the theory lying behind the research while not allowing for calculation of latent variable scores. Therefore if created structure of the model is proper in terms of explaining covariation structure of all manifest variables the SEM techniques produce optimal parameters. However there is certain amount of risk involved in the covariance-based 61
technique as under conditions of small sample size or data set violating assumptions about distribution incorrect solutions can result. Furthermore latent variable values are never calculated at the same time eliminating the possibility to predict observed variables. 5.2. Partial Least Squares On the other hand researchers can use PLS technique which is definitely less demanding in terms of assumptions about data distribution, measurement scales and size of sample. Parameter estimates are obtained by minimizing the variance of dependent variables therefore producing the best fit of collected sample data set to defined model structure proved by theory or research assumptions. PLS is aimed at obtaining determinate values of all unobservable constructs that are approximated by their respective set of manifest variables thus avoiding factor indeterminacy. Weighting scheme for each latent variable depends on the kind of relationship assumed between the construct and its indicators. It can be either reflective or formative while other SEM techniques allow only for reflective mode – the modes will be explained further in this chapter. Therefore having all the above mentioned arguments in hand the researchers can view PLS technique more suitable in cases where properties of sample data do not meet assumptions of multivariate normal distribution, where sample size is relatively small, where there is a certain amount of uncertainty between theory and data creating need for theory confirmation or where project requires calculation of scores for unobservable factors defined in the structure of the model for predictive purposes. 5.2.1. Specification of the model Before explaining PLS estimation technique some background on possible model structures as well as names of constructs used in this technique is needed. Let’s consider Figure 5.1. Circles named A and B represent latent (not observable) constructs. Rectangles named ax, ay and bx, by represent manifest variables (observable indicators) that form latent constructs A and B respectively. Arrow scheme represents inner relations of the model (relationships between latent variables) and outer relations (relationships between latent constructs and their respective indicators). Figure 5.1 represents one inner relation of A influencing B and two sets of outer relations – reflective mode of connection
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between A and its respective manifest variables ax, ay and formative mode of connection between B and its respective indicators bx, by. In the reflective mode indicators measure the same unobservable phenomenon in a way that if the level of the latent construct changes than all observable variables should also change in the same direction. The strength of change is dependent on how strong is the Figure 5.1. Structure of latent blocks model with formative and reflective modes
A
xa
B
ya
xb
yb
relationship between the indicator and the latent construct. The strength in the reflective mode is represented by loading (the amount of variance in the indicator that the respective latent phenomenon accounts for). Loadings of manifest variables on their latent construct represent the correlation between them. The question whether researcher should use reflective mode depends on several considerations: -
theory behind the measurement model – if researcher conceptualizes latent construct as a phenomenon influencing responses to the indicators scores the reflective mode should be used
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objective of the study – reflective specification should be used if the objective of the study is to explain and predict the observed variables (maximize variance of indicators)
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empirical conditions – reflective mode assures stable estimates in situations where either sample size is small or there is suspicion about multicollinearity among indicators.
The weights in the reflective specification are calculated in order to create LV that explains as much variance as possible in all its observed indicators. In the formative mode indicators do not represent the same unobserved factor and they are also not correlated to each other. The latter condition arises from the fact that in case of significant correlation of formative indicators the problem of multicollinearity may cause unstable estimates of multivariate regression of latent construct on its manifest variables. Therefore formative variables provide some kind of conditions under which the LV is being created. The aim of formative mode is to maximize the variance explained at the LV level. Therefore all indicators are weighted with the aim to maximize correlations in the inner structure of the model. The decision as to whether researcher should use the formative specification depends on the same 3 considerations as in reflective mode: knowledge on investigated theory, purpose of the research and empirical conditions. If the sample size is large enough, the indicators are not related to each other (no multicollinearity) and are conceptualized as the ones that form the latent construct meaning that the change in the level of latent phenomenon does not necessarily means changes in the same direction for all its indicators the formative mode should be used. Furthermore if the aim of the researcher is to maximize the variance explained in the latent abstracts level not the outer part of the model and there is a substantive theory confirming formative relationships the choice of formative specification is well-grounded. 5.2.2. Estimation PLS estimation procedure consists of 3 stages. In the first stage each block of indicators is assigned some weights to obtain latent variable estimates by performing iterations of simple and/or multiple regressions (outside approximation). Then the proxies for each latent construct are created based on its relations to other LVs (inside approximation). With the proxy estimates the regressions specified by the structure of the model are 64
performed in order to calculate new weights. For formative indicators the multivariate regression with their latent construct is performed opposed to individual regressions for reflective mode. The regressions’ estimates form a base for new weights to start another outside approximation. The whole procedure stops when next iteration does not produce better estimates according to applied stopping rule meaning that the percentage change in all estimated weights is for example less than 0,001. Therefore PLS iteratively performs estimation of latent variable scores in two ways. One mode is an outside approximation which calculates LVs by weighting their respective indicators. When researcher is operating on a set of observed measures representing unobservable construct without additional information it is advised to start approximation of LV by summation of its indicators. Next part of PLS estimation procedure is an inside approximation that concentrates on calculating LV scores by combining LVs most closely related to the LV in question. The inner weights can be calculated according to three schemes: the centroid scheme, the path weighting scheme and the factor weighting scheme. Assume that Ai and Aj are the estimated standardized latent variables representing real latent constructs Ei and Ej in the outside approximation and wij are the inner weights. The centroid scheme assumes that wij have the same signs as the correlation coefficient between Ai and Aj. The factor weighting scheme calculates inner weights wij as correlation coefficients between Ai and Aj. In the path weighting scheme the latent constructs are divided into predecessors of Ej meaning latent variables explaining Ej and successors of Ej , latent variables explained by Ej . For a predecessor Ei the inner weight wij is the regression coefficient of Ai from the regression of Aj on all Ai’s influencing predecessors of Ej. For a successor Ei the inner weight wij is equal to the correlation coefficient of Ai and Aj. To sum up the estimation procedure PLS operates and uses the information at both levels to estimate the next possible score of LV while maximizing variance explained of all dependent variables. PLS minimizes residual variance for a set of estimated parameters given fixed estimates or proxies for other parameters being estimated. Therefore it is partial in this sense that only part of the model is estimated in each iteration.
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Sample size requirements One important advantage of PLS modeling is small to medium sample size required for estimation. Taking a close look at all three stages of estimation procedure the requirements for sample size appears to be obvious and clear. PLS consists of simple and multiple regressions depending on the specification of latent constructs (formative vs. reflective) and inner relations of the model. As it has been mentioned before PLS is a partial procedure meaning that only part of the model is estimated at one time. Therefore the requirement of sample size for overall model comes down to the requirement for the sample size of the largest multiple regression. Therefore assuming that model consists of formative and reflective indicators the researchers has to find the biggest of the two possibilities: a) the latent phenomenon with the largest number of formative indicators b) the dependent latent construct with the largest number of independent other latent variables influencing it. Assuming well known rule for regression sample size requirements of ten cases for predicted variable the researcher has to make sure that ten times a) or b) cases are gathered (choosing greater value). If the model consists of only reflective indicators the sample size requirement is then limited to condition b). Standardization of manifest variables Lohmöller designed METRIC parameter for standardization of variables. It has 4 variants depending on 3 conditions put on the data: Condition 1: Comparability of the manifest variables’ scales. For example Satisfaction scores measured on the same scale 1-10 are comparable however height and weight are not comparable. Condition 2: Interpretability of the means of the manifest variables. Condition 3: The variances of the manifest variables reflect their importance. If variable scales are not comparable, meaning that condition 1 does not hold (METRIC 1) than standardization of variables is necessary (mean=0 with variance = 1). Standardization is also obligatory if scales are comparable but the other conditions do not hold (METRIC 66
2). In this case after standardization for the estimation phase the manifest variables are then rescaled to the original means and variances. If conditions number 1 and 2 hold but not condition 3 (METRIC 3) than the variables have to be standardized to unit variance but are not centered to the same mean equal to 0 for the estimation phase. After that the variables are rescaled to their original variances. In the last case of METRIC all conditions hold (METRIC 4). In this case the original values of variables are used in the whole process of estimation. 5.2.3. Validation of model In order to evaluate model estimated by PLS method researchers have to apply an approach which is consistent with assumptions of PLS estimation such as no distributional demands and prediction oriented specification. Therefore traditional parametric statistical tests are not appropriate for PLS model validation. Traditional R-square, the Stone Geisser test (Stone, 1974, Geiser, 1975) , average variance extracted measure (AVE) assesses predictiveness while bootstrapping and jackknifing validate the stability of estimates. R-square The R-square can be used as a first indicator of predictive power of specified model. Its interpretation is the same as in traditional regression. The indicator measures how much variance of dependent variable is explained by its predictors. It is possible to calculate R square for latent variables due to their determinacy during PLS estimation. Stone Geisser Q2 The technique is a combination of function fitting and cross-validation. It assumes that prediction of observed measures used in the estimation is of more importance than the artificial constructs’ parameters estimation.
The cornerstone of the methodology is the
blindfolding procedure that estimates parameters without part of the data for a particular set of manifest variables and then uses estimated parameters for estimating the omitted block. Such iteration is repeated until every data point has been withdrew and estimated. Let’s consider a data set and assume that N and K are omission numbers for cases and indicators respectively, and D is an omission distance. Wold (1982) suggests that D 67
should be an integer between K and N. Blindfolding procedure takes out NxK data points starting with first point and omitting every other D data point moving across all columns and rows until the end of matrix. All missing values are then replaced using pairwise deletion, mean replacement or procedure of imputation.
The sum of squares for
prediction error E is calculated and the withdrawn data points are predicted. The sum of squares errors based on the mean for prediction O is also calculated. The whole process is being repeated by returning omitted data points to the matrix and moving to the next data point - case 1 and indicator 2 – as a beginning of new round of withdrawal. During this iterative procedure D sets of Es and Os are calculated. The Stone-Geisser measure is defined as follows: Q2 = 1 – (ΣDED) / (ΣDOD)
(1)
Therefore Q2 represents a measure of how ell the specified model is able to reproduce the observable variables. If Q2 > 0 than the model is predictive and opposite when Q2 < 0. Jackknifing Jackknifing is a procedure that allows researchers to evaluate stability of particular statistic by measuring variability of data set used for calculations instead of using parametric assumptions. The technique provides estimates as well as confidence intervals for the estimates. Contrary to the blindfolding procedure it uses the algorithm of deleting n cases while estimating parameters in each iteration. Finally it examines variation of all obtained estimates. Detailed description of Jackknife procedure is for example described in Chin W.W. (1998). Bootstrapping Bootstrapping is the more advanced methodology. It is also the nonparametric approach that measures the stability of parameter estimates. Jackknifing is usually treated as an approximation to bootstrapping which is in most cases more efficient. Bootstrapping is aimed at obtaining N estimates for every parameter by creating N sample sets. By sampling with replacement from the original data set the N samples are created. The higher the number of resamples the more reasonable standard error estimates can be 68
usually obtained. The default number of bootstrap runs is usually 100, (Tenehaus et. al. 2005) however, the t-values obtained with a bootstrap of 500 runs tend to be quite similar each time the bootstrap is performed. Only rarely does the significance-level of an estimate change in between different bootstrap runs with 500 iterations. The literature also suggests choosing the bootstrap sample size equal to the number of cases in the dataset, because the standard error estimates are dependent upon the number of observations in each replication. Significance is determined against an ordinary t-statistic table, using the number of bootstrap runs as the degrees of freedom (df=500). For a typical one-sided test, the following t-values correspond to a given level of significance (df=500): 3.107 ~ p<0.001 2.334 ~ p<0.010 1.648 ~ p<0.050 1.283 ~ p<0.100 Generally the methodology is more time consuming than the jackknife procedure under the assumption that the number of resamples for bootstrapping is greater. Composite Reliability Composite reliability is a measure of internal consistency applicable only to reflective indicators which has been developed by Werts, Linn and Jöreskog (1974). It is similar in interpretation to Cronbach’s alpha which is usually lower estimate of composite reliability under the assumptions of parameter accuracy. The property is due to the fact that the composite reliability does not assume all indicators to be equally weighted. AVE –Average Variance Extracted Fornell and Larcker (1981) developed another measure applicable only to reflective specification called AVE. It represents the amount of variance that the latent construct in question captures from its manifest, observable variables. It is advised that AVE is greater than 50% meaning that the particular latent construct captures more than 50% of variance of its indicators. It is also suggested that AVE of each LV should be greater than the
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square of correlations between LVs confirming that more variance is shared between chosen LV and its respective manifest variables than with another latent phenomenon. Cross-Loadings Another measure for validating latent constructs and the structure of the model specified by researcher is the test of cross-loadings. It is obtained by calculating correlation coefficients between every set of indicators and every latent construct used in the model. Each block of indicators is expected to load higher on its respective latent component. If the condition is not met than the researcher should reconsider the structure of relationships between the set of manifest variables and latent components. Summary To sum-up PLS avoids serious problems with data distribution and sample size requirements which are crucial in covariance-based approaches. Furthermore its determinate nature allowing for calculation of unobservable components gives PLS the predictive sense and power and avoids parameter identification problems that may occur for covariance-based approaches. Finally PLS does not limit specification of models only to reflective mode allowing for formative specification where weights of indicators are estimated in order to maximize prediction of particular LV. All the arguments and advantages presented above prove PLS as the most suitable method for estimating Customer Satisfaction models such as Brand Satisfaction Model designed for Company X in Poland.
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6. MEASURING CUSTOMER SATISFACTION AT COMPANY X IN POLAND Until the Brand Satisfaction Model based on PLS methodology has been introduced at Company X in Poland as a complete measurement of customer satisfaction and loyalty there have been two unified approaches to exploring satisfaction of its customers. First one, Sales Service Quality CSI concentrates on measuring satisfaction with the sales service quality while the second one – After Sales Service CSI - measures satisfaction with after-sales service. These are two separate researches deeply investigating all aspects connected with the two areas which are the main responsibility of sales companies in different countries. While for example product quality is the sole responsibility of headquarter, the sales and after-sales service constitute the core business of the company locally. Therefore based on the Company X Global Board of Directors’ decision, the two above mentioned studies have been approved as the main measures of sales companies performance in particular markets. The methodology has been unified on every market meaning that research questionnaire is the same in all countries. Thus each sales company in every market is using sales service quality CSI and after-sales service quality CSI researches. Both measures has become extremely important for the whole company and became part of upper-level management bonus system in order to make sure that all respective employees are devoted to achieve the best possible score in both areas. Based on all the information written above it seems there has been no place for additional research investigating customers satisfaction beyond sales and after-sales service. Especially bearing in mind the fact that the CSI has been introduced as a global, obligatory project. However the authors realized that although both existing measurement methods are necessary and important for the organization, they do not allow for creating a local and complete picture of Company X customers’ feelings about the brand with regard to all the areas of their experience with the vehicle. Therefore the authors decided to propose the Brand Satisfaction Model methodology to the Board of Directors in Poland as the unique, complete measurement method for receiving comprehensive picture of Company X customers’ needs, wants and satisfaction. The comprehensive picture means not only investigating satisfaction in other areas of customer experience with vehicle such as: product quality, image, ownership costs etc. but also measuring importance of particular areas in generating satisfaction and loyalty. By introducing the new research the company could gain knowledge of the strength of particular areas influence on
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satisfaction and loyalty and thus would be able to make better sales, marketing and PR decisions. To better understand the advantages of BSM over CSI researches used currently at Company X, it is necessary to familiarize with assumptions and structure of both methodologies. 6.1. Customer Satisfaction Index at Company X – Sales Service Quality The main objective of the research is to deliver better knowledge about customers’ satisfaction with the process of purchase of the vehicle. Core aspects under investigation are: purchase situation process, quality of sales personnel, timing of vehicle delivery, vehicle reception by the customer and general satisfaction with the service provided by the dealer. Over 2 000 questionnaires are being sent to the customers twice a year by mail. The effective rate is around 20-30%. The study covers only those customers who bought the vehicle not earlier than 3 months before the research is actually conducted and at the same time not later than 4 years of vehicle usage. Structure consists of scaled, non-scaled as well as sociodemographic questions. Description of purchasing process, choice factors, willingness of next purchase and recommendation are the non-scaled parameters. Sociodemographic part is standard as in every other study. The most important part of the research is of course the one that measures satisfaction of customers with different elements constituting every-day business for sales companies in different countries. In case of CSI it is the section with scaled questions. It consists of inquires about: -
Satisfaction with overall dealer service o Satisfaction with visit to the dealer o Credibility of the dealer o Honesty and reliability of the dealer o Time spend during vehicle purchase o Ability to agree on vehicle pick-up based on customer needs and schedule
-
Showroom atmosphere o Overall satisfaction with the showroom (design and atmosphere) o Completeness of customers’ care (coffee, tea, resting sofas etc.) o Availability of sales materials 72
-
Telephone contact o Possibility of receiving trading information through the telephone
-
Sales representative o Easiness in dealing with purchase situations o Honesty o Clarity of information given to the customer o Customers’ time respectfulness o Knowledge about product offer o Helpfulness in choosing the right vehicle o Service provided between contract conclusion and vehicle delivery o Frequency of salesman contact o Behaviour of sales representative o Explanation of vehicle or leasing price o Credibility of salesman promises during purchase of the vehicle o Helpfulness of salesman in dealing with formalities.
-
Test drives o
-
Availability of test drives
Timing of delivery and basic instruction o Satisfaction with timing of delivery o Explanation of warranty conditions o Explanation of after-sales service conditions o Information given on principles of vehicle usage
-
Overall condition of the vehicle during receipt o Cleanliness of interior o Cleanliness of exterior
-
After purchase contact o Thankfulness expression after purchase o Contact of salesman after purchase and receipt of the vehicle
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-
Complaints handling o Overall dealing with complaints
-
Loyalty o Willingness to recommend the dealer o Willingness to purchase a vehicle at the same dealer o Evaluation of the dealer comparing to other brands’ dealers
6.2. Customer Satisfaction Index at Company X – After - Sales Service Quality The main purpose of the CSI-after-sales research is to measure performance of each aftersales service point in Poland. It concentrates on such areas as customers’ first contact with the reception and services advisor, quality of facility operation and infrastructure, competence of service advisor, transparency of service provided, timing, general vehicle reception process and overall quality of service provided. Over 2 000 questionnaires are being sent to the customers twice a year by mail. The effective rate is around 15-25%. The questionnaires are sent only to those customers who bought the vehicle not earlier than 3 months before the research and at the same time have not used the vehicle longer than 4 years. Below is the description of the areas under investigation: -
Booking in process o Schedule service within reasonable time o Effort to help you maintain normal schedule o Amount of time spent waiting to speak to someone
-
Facilities o Convenience of opening days and hours o Convenience of location o Ease of parking o Provision of comfortable waiting area o Overall cleanliness of waiting area o Amenities available
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-
Service advisor o Provision of advice with regard to service needs o Courtesy and respectfulness of service staff against customers o Honesty of service staff o Display of knowledge and expertise o Attentiveness to your inquiries o Extent to which they clarified your needs o Degree to which they understood problems with your car o Extent to which they kept their promises
-
Vehicles reception process o Promptness in having car ready when promised o Explanation of work performed on your car o Explaining charges for work performed o Process of paying for the service o Cleanliness and appearance of car o Amount of time for payment and collection of the vehicle
-
Quality of after-sales service o Amount of time spent waiting for service o Ability to diagnose problems o Quality of work performed o Thoroughness in fulfilling your requests o Availability of parts required o Extent to which they stand behind service
6.3. Brand Satisfaction Model at Company X in Poland – history, underpinnings and structure The need for more complete approach to measuring customer satisfaction and loyalty arisen together with the need of product management, marketing and PR departments of Company X in Poland for better knowledge about clients behavior and their way of thinking and making purchasing decisions. So far the two existing CSI studies offered a 75
limited amount of knowledge, which covered two areas: sales service quality and aftersales service quality. Until the Brand Satisfaction Model has been introduced there has been no official representative information on how Polish customers perceive Company X in terms of product quality, image, design, expectations, costs of ownership, comfort and functionality, value/price ratio etc. There was also no measurement of customers’ loyalty against dealers, against brand or their willingness for recommendation. But defining the areas of clients’ feelings about a particular brand is not that complex and is in fact easy to possess. The sales and marketing staff of each automotive company is definitely well experienced to define all the areas which should be investigated and those defined constructs can then be verified by focus groups or individual interviews with customers giving them a chance to add those important elements that are not covered in the research. After such process, researcher can be sure that his study covers all the important elements creating overall picture of customers’ brand perception. However there is also one more and very important aspect of knowledge about your customers. The sole satisfaction scores for all significant areas creating overall satisfaction and loyalty of the end-users have limited power for practical application in real business life unless the importance of all the elements is calculated. Computation of each element’s weight is crucial for creating complete picture of customers’ perception and the way they evaluate the brand performance. If the whole process ensures that (1) satisfaction areas definition is properly conducted internally in the company, (2) then the structure is verified and supplemented by the sample of customers and (3) the importance scores for all attributes are calculated, then it is guaranteed, that the whole approach is complete and offers number of advantages which help better understand the clients. One important aspect is the computation of importance weights. The question arises whether the weights should be calculated by asking customers straight questions about the importance of particular attributes or they should be computed statistically. Many researches proved that the latter one is a better approach as it is resistant to one important disadvantage of the first approach. Usually in case of having customers declare the importance of the areas of their satisfaction the distribution of answers is for most areas strongly negatively skewed meaning that all the elements are equally and very important. Such methodology in most cases creates a picture of equal importance of the elements by 76
limiting the distinction of the ones that are really important and that create the most significant part of customers’ satisfaction and loyalty from those which are not important and can be almost eliminated from the research. By statistical computation the importance weights are more reliable and less biased by human factor. Moreover, statistical computation allows for segmenting the results in satisfaction – importance matrix, as the weight are spread wider as opposed to importance weights declared by respondents. The satisfaction – importance matrix is presented in Figure 6.1.
High
Satisfaction
Figure 6.1. Segmentation of satisfaction with attributes according to their importance.
Potential for savings
Low
Needs improvement
Attribute’s importance
Low
High
Importance
The figure divides all attributes into four groups. Taking into account the importance declaration, all the elements would be almost equally important and as a result all of them would lie close to the middle of Importance axis. Thus the distinction of the real drivers of customers’ satisfaction would not be possible. On the other hand statistical computation of real importance scores of all areas included in the customer satisfaction study by using for example PLS approach offers the researcher practical ability to discover elements that need improvement and those where company can save some money. The most important
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field in the matrix presented in Figure 6.1. is the one with low satisfaction and high importance attributes. This quarter of the matrix is the starting point of every analysis as improvement of the areas which lie in this field has the biggest influence on overall satisfaction score improvement. The field, where company can save some money, is the one containing high satisfaction and low importance attributes meaning that customers evaluation of these areas is too high relative to their importance. In general, for business to be most effective, all measured variables should lie close to the diagonal - with some tolerance which is calculated by confidence intervals. This kind of satisfaction/importance analysis can be conducted for both overall satisfaction and customers’ loyalty. Thus first figure would present all attributes satisfaction scores and their influence (importance) on the overall satisfaction score while the second one would present the influence of these elements on customers’ loyalty. The two steps analysis is crucial for practical interpretation of the results. Although overall customers satisfaction plays an important role in every company strategy it may be useless if it does not create loyal customers. Loyal customers are the source of company’s higher incomes and form the strong and stable base for sales performance. Therefore company with quite satisfied but not loyal customers is definitely exposed for higher risk of loosing business and has to constantly seek for other customers, explore new segments by for example introducing new products which is extremely costly and may be successful only in a short term as the number of market opportunities is usually limited. One important aspect here is the definition of areas of responsibility for a company. Global companies operate with a structure led by headquarter and represented by sales companies or agents in different countries. In case of automotive sector the headquarter is usually responsible for inventing, designing and producing a certain product with very limited influence of sales companies on this process. Therefore such areas as product quality, comfort and functionality of vehicle are not dependent on sales companies’ performance locally in different countries. On the other hand, it is sales company that creates particular level of sales and after-sales service quality for customers in particular country. In this case, the headquarter has very limited influence on what level of service is provided beside producing some guidelines and pushing for their implementation. Therefore some areas lie mainly in the responsibility of the headquarter while sales companies are responsible for the other areas. Thus when conducting importance vs. 78
satisfaction analysis the researcher needs to remember about the aim of the study whether its objective is to analyze and improve total business or local performance of a brand. To sum up Brand Satisfaction Model has been designed in order to create a complete measurement method that would not only explore all the areas of customers satisfaction but would also measure their influence on customers’ satisfaction and loyalty. This kind of approach allows for confirmation and verification of different theories on customer satisfaction in the automotive market by understanding customers perception of Company X brand locally in Poland. It also forms a solid base for making practical recommendations useful for making tactical, operational and strategic decisions in sales, marketing and PR departments. Thus BSM is an universal tool that offers significant amount of knowledge with limited amount of effort. It would have more advantages when applied to most of the automotive producers selling new vehicles in Poland. This would allow for comparisons between satisfaction and loyalty scores between different companies as well as for comparisons of different brands’ customer profiles. 6.3.1. Questionnaire development In order to create a proper questionnaire exploring all areas of customers satisfaction with a brand, a 3 steps approach was applied. First a project group has been set at Company X in Poland. The group consisted of sales representatives from the dealer network and headquarter employees responsible for sales planning, product management, marketing, PR, customer relationship management including Customer Service employees that have frequent telephone contact with clients. The aim and preliminary structure of the research was presented in front of the project group. All the members were asked to give their input into definition of all the areas of clients satisfaction with a brand in order to build a complete measurement tool covering all aspects of the research. All in all, 3 meetings were held and finally the first official structure of the questionnaire was developed. In the second phase the research agency was contacted in order to give its input into development of the tool. The agency was presented the assumptions of the study as well as the questionnaire created during first phase of the research. It combined all its 79
experience in conducting customer satisfaction studies, analyzed the research objectives and suggested some changes in the questionnaire. Therefore the second version of the questionnaire arisen. In the third phase 10 individual interviews with Company X customers were carried out in order to verify the completeness of the questionnaire as well as to make it comprehensible and understandable. In this phase clients were firstly asked to state their definition of satisfaction with an automotive brand and then all the areas from the second version of the questionnaire were verified with respect to their clarity and completeness. Ultimately the third and final version of the research tool has been developed. It consists of questions defined by not only people working in sales and marketing, PR and CRM departments at Company X in Poland but also sales representatives who have day-to-day contact with clients. What is most important, it has been verified by customers with respect to its completeness and clarity. Below is the description of all the elements included in the final version of the questionnaire. It consists of 3 parts. First is the definition of the respondent, second is the main part of the questionnaire that consists of questions defining Brand Satisfaction Model (measured on a scale from 1 to 10 where 1 is the absolutely negative score and 10 is definitely positive score) and the third part is the demographic one. I. Definition of the respondent 1. Gender of a respondent 2. Definition of the concrete model that the respondent is driving (8 models that cover 95% of the total sales volume have been specified) 3. Definition of the type of the engine (petrol/diesel) 4. The date of the vehicle reception after purchase 5. Specification of the dealer where the vehicle was purchased II. Main part of the questionnaire 1. Expectations at the purchase of the vehicle a. Overall expectation of quality 80
b. Expectation of how well the product fits the requirements c. Expectation of reliability/How often things could go wrong 2. Overall Satisfaction a. Overall satisfaction with usage of the vehicle b. Overall satisfaction with the vehicle compared to an ideal vehicle c. Overall satisfaction with the vehicle compared to expectations at the purchase. 3. Image a. Overall satisfaction with image of a brand b. Assurance of safety when driving c. Stable position of a brand on the market d. Technological leadership of a brand e. Brand involvement in customers’ satisfaction improvement f. Brand involvement in social actions g. Brand involvement in promotional events (trades, advertising campaigns, sponsoring etc.) h. Brand involvement in environmental protection i. Brand involvement in making drivers’ lives easier 4. Sales service quality a. Overall satisfaction with sales service quality b. Professionalism of the sales representative c. Kindness and good manners of the sales representative d. Sales rep willingness to inform customer e. Contact renewal after customers visit in the dealership f. Ease of contact with the sales rep g. Atmosphere in the showroom h. Wide product offer i. Availability of additional services (financing, test drives etc.) j. Promptitude of service realization k. Abidance of timing of the service
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5. Quality of the vehicle a. Overall satisfaction with the quality of the vehicle b. Reliability of the vehicle c. Quality of exterior painting d. Quality of interior materials and finishing e. Quality of the upholstery f. Driving quality (driving and steering systems) g. Suspension quality h. Breaking quality 6. Design of the vehicle a. Overall satisfaction with the design of the vehicle b. Exterior design c. Interior design d. Modernity of design e. Uniqueness of design 7. Comfort and functionality of the vehicle a. Overall satisfaction with comfort and functionality b. Seats comfort c. Visibility from driver’s seat d. Functionality of steering elements e. Interior space f. Possibilities of interior space management (folding, removing seats etc.) g. Boot capacity h. Communication systems (radio, navigation etc.) i. Air-conditioning/ventilating systems 8. Costs of ownership a. Overall satisfaction with costs of ownership b. Fuel usage c. Insurance costs d. After-sales service costs e. Repairing costs 82
f. Spare parts exchange costs 9. After-sales service quality a. Overall satisfaction with after-sales service quality b. Professionalism of the after-sales representative c. Sales rep willingness to inform customer d. Atmosphere in the after-sales showroom e. Availability of substitute vehicle f. Availability of spare parts g. Promptitude of service realization h. Abidance of timing of the service 10. Value for money a. Evaluation of the quality with respect to the price of the vehicle b. Evaluation of the price with respect to the quality of the vehicle 11. Loyalty a. Willingness to recommend the brand b. Willingness to recommend the dealer where the vehicle was purchased c. Willingness to purchase a vehicle of the same brand If the answer is negative than the customer is asked to tick out the reasons: i. Bad quality of the vehicle ii. Bad quality of service received at the dealership iii. Design of the vehicle iv. Reliability of the vehicle v. Comfort vi. Too high price of the vehicle vii. Attractiveness of other brands viii. Too high ownership costs ix. The vehicle does not meet the expectations x. Other brands offer same quality vehicles with lower price xi. Other reasons d. Willingness to purchase a vehicle at the same dealership If the answer is negative than the customer is asked to tick out the reasons: 83
i. Poor quality of service ii. Inconvenient location iii. To high prices of after-sales service iv. Incompetent staff v. Poor quality of repairing vi. Negative experience with vehicle delivery vii. Timing/Promptitude of service viii. Poor atmosphere at the dealership ix. Poor availability of additional services such as for example substitute vehicle, financing etc. x. Other reasons III. Demographic questions 1. Age of the respondent 2. Education of the respondent 3. Number of family members living with the respondent 4. Profession/Occupation of the respondent 5. Number of habitants in the city of respondent 6. Voyevodship/Province/County of the respondent 7. Earnings of the respondent
6.3.2. Computer software for Partial Least Squares models The authors of this paper have conducted significant research on all the computer programs that could handle Partial Least Squares calculations and produce necessary output. Unfortunately not many programs support this methodology. Furthermore some programs supporting PLS calculations are not user friendly not allowing for graphical definition and representation of the model. However there are two programs with graphical interfaces helping researchers easily build the structure of relationships for particular study. These are: PLS Graph and Smart PLS. Ultimately the authors have chosen the latter one as the most complete, professional and at the same time easiest and most user friendly tool for performing PLS on BSM. The Smart PLS software has been 84
created by a group of developers sited at the University of Hamburg (Germany) and is so far available as a freeware for all academic users. 6.3.3. Working out the structure of the model The objective of the research was to build an industry specific model of customer satisfaction and loyalty which would completely cover all aspects of brand performance perception. The ACSI and ECSI models are the cornerstones of the structure for Brand Satisfaction Model. However the two models have been developed in order to serve as a universal tool for measuring satisfaction of different industries’ clients. Therefore a certain portion of generality have been applied in both American and European methodology. The Brand Satisfaction Model was designed as an automotive industry specific measurement method with strong attention to details. Thus the BSM had to cover more areas of customer satisfaction as well as some of the areas had to be divided into more detailed ones. The ACSI model consists of Perceived Quality, Perceived Value, Customer Expectations, Customer Satisfaction Index, Customer Complaints and Customer Loyalty scores. The ECSI model adds Image factor and divides Perceived Quality into “software” and “hardware” areas. According to all the research done during preparation of BSM structure and based on Company X employees experience as well as customers’ definition of satisfaction concept, the structure of the study had to be modified versus ACSI and ECSI models. If we take the ECSI methodology as a starting point than in order to create BSM structure the authors added 3 factors: Comfort and Functionality, Vehicle Design and Costs of Ownership. These 3 elements have been defined during first phase of study preparation as important elements of customer satisfaction and are rather specific for automotive industry. Furthermore Perceived quality of “software” and “hardware” has been divided into Product Quality, Sales Service Quality and After-Sales Service Quality. This distinction is justified by the fact that these 3 elements are clearly recognized by customers of passenger cars because in vast amount of cases there are 3 separate units responsible for each of the areas: Producer, After-Sales Service department of the dealership and Sales Service department of the dealer point. Furthermore The Customer complaints area has been replaced/covered by the After-Sales Service Quality factor. All
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these changes modified the ECSI model to make it more automotive industry specific as well as to make it more useful for management of Company X in Poland. Ultimately the structure of relationships between all latent variables had to be also altered and adjusted to the defined structure of Brand Satisfaction Model. This has not been an easy task due to higher number of variables included into specification. First attempt of the authors was to make the structure of relationships as much similar to ECSI as possible. Figure 6.2 presents the first structure of Brand Satisfaction Model with similar relationships as in ECSI methodology. Figure
6.2.
First
version
of
Brand
Satisfaction
Model
based
on
ECSI
methodology.
The latent variables not included in ECSI such as: Comfort and Functionality, Costs of Ownership and Vehicle Design have been connected to Value for Money and Customer Satisfaction Index variables, what was done based on theoretical knowledge and assumptions. However after validation of the model it appeared that the structure had to be significantly altered. Although Cross Loadings and AVE test confirmed proper specification of latent
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variables, the Bootstrapping algorithm (with 346 cases, 500 samples, construct level changes and mean replacement algorithm) which results are presented in Figure 6.3, confirmed that most of relationships are not significant therefore the arrows between such variables should be deleted from the model. Figure 6.3. Results of Bootstrapping algorithm for first version of Brand Satisfaction Model
After this failure the authors decided to apply different algorithm for defining structure relationships for industry specific model called Brand Satisfaction Model. The authors decided to firstly investigate the correlation matrix for all latent variables received from performing PLS on the first version of Brand Satisfaction Model (The matrix is attached in Appendix 1.). Furthermore an expert advisory had to be applied in order to build a model that could be justified by satisfaction theories and practical knowledge. Therefore some arrows were specified in order to confirm some theoretical assumptions of researchers although the correlation score did not necessarily justify the relationship. While creating new structure
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of models that have not been confirmed before by any kind of studies the researchers have to bear in mind that the model has to be proven not only by statistical tests but also by the theory lying behind the study. Therefore after many trials, the authors worked out the final structure of Brand Satisfaction Model which can be justified by model validation techniques and complies with the satisfaction theories as well as practical experience. The complete model is presented below in Figure 6.4. The detailed results of PLS algorithm application are attached in Appendix 3. Figure 6.4. Final structure of Brand Satisfaction Model for Company X in Poland
Figure 6.5 presents results of application of Bootstrapping algorithm to the final specification of BSM. Detailed Bootstrapping algorithm results are attached in Appendix 2. It confirms all relationships in a very significant manner. According to t-values received all path coefficients are significant (df = 500) with a confidence level of at least 99%. Thus this structure can represent a complete picture of how customers of Company X in Poland evaluate its brand performance. As the bootstrapping algorithm proves all the relationship in a very strong manner it would be worth verifying if the model could be also applied to other automotive brands in Poland but this topic would be touched upon in further course of this paper.
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Figure 6.5. Results of Bootstrapping algorithm for final version of Brand Satisfaction Model
6.3.4. Discussion on BSM structure To justify the structure and all the relationships of the Brand Satisfaction Model not only statistical tests or measures such as bootstrapping, AVE, Cronbach’s alpha or Cross Loadings have to prove the model. Beside statistical confirmation the theoretical and practical knowledge also has to stand behind the structure. Therefore the aim of this part of the chapter will be to explain what has already been confirmed by statistics. Some clarification regarding applied modes for latent constructs is needed. Firstly all the latent constructs are created in a reflective way due to the fact that they reflect particular feelings of customers regarding some aspect of their satisfaction i.e. Vehicle quality etc. Secondly the manifest variables in all cases do not completely define and form the latent
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construct to which they are related. Furthermore all latent constructs include one manifest variable that evaluates general satisfaction of customers with a specific latent construct thus forcing somehow the reflective mode. Finally all sets of manifest variables that form each specific construct are usually correlated to each other thus making it impossible for applying formative specification. Let’s move on to analysis of structure of inner relationships. Let’s take a closer look at Comfort and Functionality variable. It is the only latent construct related to the Vehicle Quality meaning that satisfaction of customers with comfort and functionality of driving the vehicle influences their opinion about vehicle quality. It can be reasonably explained because when the vehicle offers good comfort and is functional it creates better opinion about the product itself. When the customer has positively evaluated the vehicle in terms of comfort he/she also has a positive attitude for evaluating quality of a vehicle. The strength of the relationship should be quite strong as both latent constructs reflect practical elements of product evaluation. Moving on to Costs of ownership, this latent construct is related only to after-sales service quality variable as it partly reflects costs of service, spare-parts and repairs. However it does not prove any direct influence on value for money concept. It only has an indirect influence on the construct through the quality of after-sales service. This can be justified by the fact that the Costs of ownership construct does not include any evaluation of price of the vehicle or its quality which are the cornerstones of the Value for money factor. When analyzing Vehicle design concept the only proven relationship binds it to Image variable. This relationship can easily be proven as the exterior and interior outlook, modernity and innovativeness of a design create the image of the brand. If the design is modern and the exterior as well as interior catch the eye of customer, the evaluation of brand image performance should be higher than in the opposite case. Vehicle quality construct shows positive influence on Value for money, Overall Satisfaction and Image. The first two relationships have already been proven by for example ECSI methodology. The positive connection with Image concept confirms the
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theory that reliable, good quality vehicles such as i.e. Toyota have better perceived image than the ones from the lower part of the quality ranking. Image variable influences Value for Money and Expectations factors. The first relationship is also proven by i.e. ECSI model. The connection to expectations can be explained by the fact that the evaluation of brand Image has a positive influence on what customers will expect from the vehicle and the brand itself. If a brand is perceived as being environmental friendly, reliable, safe, involved in customers satisfaction improvement as well as strongly involved in communication campaigns than the customers will expect such attitudes when they decide to buy the vehicle of a particular brand. The expectations on the other hand are connected only to Sales service quality. Unfortunately no relationship between Expectations and Value for money, Vehicle Quality, Overall Satisfaction or Loyalty has been statistically proven. The only path approved by bootstrapping with stable parameter estimate is the path to Sales service quality. The reason for this kind of result is first of all the fact that in ACSI, ECSI and other customer satisfaction models usually the customer expectations have rather low influence on overall satisfaction and loyalty of customers. It seems that in the automotive industry in Poland in case of a premium brand like Company X the expectations have no direct influence on the 3 most important elements of the BSM: Value for Money, Overall Satisfaction and Loyalty. However they have a positive influence on Satisfaction with sales service quality. Such outcome can be explained in a way that when customers have some specific expectations about the brand and they consider buying the vehicle of this brand they first go to the showroom meaning that the first thing they evaluate is the sales service quality. Those customers in such process verify their expectations about the brand by direct contact with a dealer (representing brand) and the product itself (showroom and test drives). After buying a vehicle the expectations have no influence on customers’ evaluation of Perceived Value of the vehicle or their overall satisfaction with the car as customers begin to care more about real attributes of the product and soft elements of the service they receive than about the expectations they had before the purchase of the vehicle. The expectations have an indirect influence on loyalty through the sales service quality variable.
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Sales service quality opposite to perceived quality of “software” in ECSI model does not show any positive influence on Value for money or Overall satisfaction of clients. SSQ is only connected to Loyalty construct. This relationship can be justified as follows. Customers have direct contact with sales service quality usually when they aim to buy a vehicle. While actually using a vehicle they have no contact to sales representatives meaning that it should not influence their evaluation of their satisfaction with vehicle usage. Next contact with sales service is most often when a customer decides whether to buy a vehicle of the same brand at the same dealer or not. If the service received will be positively evaluated than it may also positively influence their decision whether to buy the vehicle of the same brand again. Therefore the above presented reasoning confirms the sole path connecting SSQ and Loyalty. After-sales service quality as the third part of Perceived quality construct in ACSI is related to Value for money factor which is the same as in ECSI and to Loyalty which can be explained similar to relationship between SSQ and Loyalty. If a client is well treated during each and every visit at the workshop than he/she will be more loyal against the dealer as well as the brand itself. The Value for money concept is related only to Overall Customer Satisfaction variable which is related only to Loyalty construct. This structure of relationships is no different to ACSI or ECSI and needs no explanation. 6.3.5. Quality criteria evaluation As discussed earlier the bootstrapping algorithm proved the structure of inner relations between all latent constructs used in the model. The three tables included in Appendix 2: Outer Model T-statistics, Path coefficients T-statistics, Total Effects T-statistics present the results of bootstrapping algorithm application to Brand Satisfaction Model. The results generally confirm inner and outer relations used in the structure applying the rule of tstatistic greater than 2. The are some inner relations (path coefficients and total effects) with t-statistic values between 1 and 2 meaning that the parameter estimate are not quite stable however the relations are proved by underlying theory of customer satisfaction therefore the authors decided to maintain the original structure of BSM. The problem of low t-statistic values exists mainly in bootstrapping algorithm of total effects and applies 92
mainly to indirect relations with usually low parameter estimates. Thus such relationships are rather harmless to the whole structure of the model as they have low influence on the interpretation of the results but on the other hand explain all the theoretical correlations of particular latent constructs. In order to evaluate the appropriateness of specification some other quality criteria described in PLS theory part of the thesis have to be analyzed. All the information on quality criteria is included in Appendix 3. The overview of quality criteria presents values for AVE, communality, composite reliability, Cronbachs Alpha and R square. In general AVE and communality values should be greater than 0,5 as well as greater than the square of correlations between all Latent Variables used in the model (Tenenhaus et al. 2005). Such condition is met with two exceptions of Comfort and Functionality and Image variables where the AVE values are equal to 0,48 and 0,49 respectively. This kind of deviation can be easily omitted as the value is very close to the minimum. In case of composite reliability and Cronbachs Alpha both statistics should be higher than 0,7 (Tenenhaus et al. 2005). All the values for latent constructs used in the Brand Satisfaction Model are greater than 0,84 further confirming the reliability of the outer structure. Analyzing the R-square values the only important variables in terms of predictive power of the model are Overall Satisfaction, Loyalty and Value for money. Other variables for which R-square was calculated serve as the connectors of indirect relations for other latent constructs and are not main elements in terms of predictive properties of the model. Therefore considering the three main variables in question all R-square values are high enough in order to give significant predictive power for the model. In general the minimum value is 0,5 (Rossiter 2002) therefore the Loyalty 0,6 value, the Overall Satisfaction 0,72 value and Value for money 0,69 value offer strong base for further analysis.
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The analysis of cross-loadings confirms the validity of the latent constructs and their respective indicators meaning that the appropriate indicators build up the latent constructs. The general rule is that the indicators should load higher on its respective latent construct and that the values of cross loadings for particular latent construct should be higher than 0,7. This conditions are met in most cases with some minor exceptions when crossloadings values are between 0,55 and 0,7. However this is a small scale problem which can be definitely omitted especially when the number of variables is so high and the number of cross-loadings parameters is equal to 528. Therefore in general the values of cross-loadings prove the outer structure of the model.
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7. RESULTS OF BRAND SATISFACTION MODEL FOR COMPANY X 7.1. Sample description Before any analysis, the detailed check of gathered data was applied. The database was checked for possible outliers as well as with regard to its consistency and possible logical mistakes. After data import to the software programs, the consistency of data with the original base was also investigated in order to assure the highest possible data validity and quality. Sample for the Brand Satisfaction Model study has been carefully selected in order to reflect the structure of Company X customers in Poland. The whole database of all the clients as well as the sales volume segmentation have been analyzed. Based on the analysis the sample of all the customers that purchased a vehicle one to four years before the research was extracted. The number of customers of particular vehicle models reflected the structure of sales volume as well as regionalization of sales with respect to dealerships shares in sales. The factors that have also been taken into account while creating sample database are gender, age group, education, occupation and earnings. From the total number of over 10 000 customers the database including 2 030 clients that meet the assumptions of the research was created. Firstly the mailing with the information about possible individual interview was sent out to all 2 030 customers. Finally the requested number of 346 responses was gathered which gives a reasonable response rate of 17%. The responses were collected through the individual interviews with the clients the method that assures customers about importance of the research by rising its prestige. It also offers lower possibility of collecting not proper responses through eye to eye contact what gives confidence that the appropriate person is responding to the questionnaire. Below are the figures describing the sample data set in detail presenting the main characteristics of the respondent group. The figures prove and are in line with the profile of Company X consumers. Respondents are mainly male according to profile of Company X customers.
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Figure 7.1. Gender of respondents 77% 80% 70% 60% 50% 23%
40% 30% 20% 10% 0% Man
Woman
The model range has been split into three categories: Compact, Mid-Size, Full-size and Large. Under compact category there are customers of two models: Compact vehicle and Compact MPV. Mid-size category is also represented by two vehicles which fall into a Mid-size sedans and Mid-size Specialty Coupes segments of passenger vehicles segmentation. Full-size and Large category is built up of 4 models: Full-size sedan, Largesize sedan, Full-size Off-road and Luxury Specialty Coupes. Figure 7.2. Model range 41% 45% 40% 35%
29%
29%
30% 25% 20% 15% 10% 5% 0% Compact
Mid-size
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Large
Figure 7.3. Engine type
100% 80%
52%
48%
60% 40% 20% 0% diesel
petrol
The shares of fuel types also are in line with actual state of vehicles sold to customers although the trend is strongly changing to diesel engines. Furthermore, the split would be different for different models as for example all sport-type vehicles as coupes or roadsters are sold mainly with petrol engines while at the same time all off-road vehicles are equipped mainly with diesel engines. Compact and limousine type vehicles sedan as well as estate wagons so far have a split of 60% diesel to 40% petrol engines with a moderate trend towards diesel. The figure presenting age of Company X customers in Poland confirms the fact that the majority of clients falls into 40 to 60 years old category. The group of 30 to 39 years old customers is already significant category with high potential for growth due to development of Polish economy which forces the growth of earnings especially for young people. Analyzing education of the customers there are two groups that cover over 90% of the total number. The biggest category consists of clients with higher/university type education. The other significant group is the one with only secondary education (38%). The group consists mainly of company owners that started their businesses and at the same time decided not to continue education. We have to bear in mind that those people
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attended schools 15-30 years ago when the number of schools offering higher education was significantly lower. This proportion changes at a high pace towards higher education category. Figure 7.4. Age groups
35%
40%
33%
35% 30% 25%
19%
20% 10%
15% 10% 5%
3%
0% 18 to 29
30 to 39
40 to 49
50 to 60
over 60
Figure 7.5. Education
60%
53%
50%
38%
40% 30% 20% 10%
1%
4%
5%
0% preliminary secondary technical
secondary general
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bachelors
masters
Occupation of Company X customers in Poland is dominated by two categories: owners of the companies and upper-level managers what is in line with clients’ profile. There are also 3 interesting categories with equal 5% share in the total sample: Pensioners, Highly qualified specialists and people with free occupation such as for example Artists and Farmers. While the first and the latter groups have rather stable share in the total number of customers the group consisting of highly qualified specialists is the one with extremely high potential for growth which is also connected with economy development and Poland accession to EU which in long term will significantly increase salaries. Figure 7.6. Occupation/Position
70%
64%
60%
50%
40%
30%
20%
14% 5%
5%
Free occupation/Artist/Agriculture
Owner of the company
Manager position
Highly qualified specialist
2% Qualified technical worker
1%
0%
Qualified physical worker
0%
Not qualified physical worker
2%
Buerau clerk
5%
Public clerk
0%
Unemployed
2%
Pensioner
10%
The total income of households doesn’t need any comment as this is clear that biggest group of Company X customers is of course the one that has the highest earnings and the trend will maintain as it is now. Figures 7.8 and 7.9 present the regional split of customers divided into the size of cities and name of voyevodship. Naturally the strongest demand for vehicles from Premium segment is visible in biggest cities. Analysts predict that in a long term there will be negative migration to the largest agglomerations which means that more and more
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wealthy people will move to smaller cities. Thus a higher share of customers living in cities with 50 to 200 thousands inhabitants shall be observed in future. Figure 7.7. Total household income (in PLN) 78% 80% 70% 60% 50% 40% 30% 20%
7%
4%
4%
10%
7%
0% below 4000
4000 - 6000
6000 - 8000 8000 - 10 000 over 10 000
Figure 7.8. Size of the city (in thousands of inhabitants)
49% 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0%
23%
9%
village
8%
10%
city up to 10city 10 to 50 city 50 to city over 200 200
100
There are 5 strongest sales regions in Poland when it comes to analysis of customers divided into voyevodships. The biggest voyevodship regarding sales of new vehicles is Mazowieckie with its capital – Warsaw. The second biggest region is Slaskie (Katowice) and Dolnoslaskie (Wroclaw) on the south of Poland which, when summed together, have the same share as Mazowieckie (23%). Moving to northern part of Poland there are three significant
regions
with
high
demand
potential:
Wielkopolskie
(Poznan),
Zachodnipomorskie (Szczecin) and Pomorskie (Gdansk) with 8%, 8% and 6% share respectively. Figure 7.9. Region/Voyevodships
25%
23%
20% 15%
15%
6%
Zachodniopomorskie
1% Wielkopolskie
Slaskie
2%
Warminskie
3%
Pomorskie
Podkarpackie
Opolskie
1% Mazowieckie
Malopolskie
3%
Podlaskie
4%
Swietokrzyskie
6%
Lodzkie
Lubelskie
Dolnoslaskie
3% 2%
5%
Lubuskie
5% 0%
8% 8%
8%
Kujawskie
10%
7.2. Estimation results for Brand Satisfaction Model – Total Brand The parameter estimates for inner model as well as R square values for all dependent variables are presented in Figure 7.10. To actually analyze the strength of impact of particular constructs on Satisfaction and Loyalty measures the total effects were calculated and are presented in Figure 7.11.
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Figure 7.10. Results of PLS algorithm application on final version of BSM.
Looking at differences of importance of particular latent constructs regarding satisfaction and loyalty it is obvious that satisfaction does not always mean loyalty. Even if the customer is satisfied he/she does not have to purchase or recommend a vehicle of the same brand until certain conditions are met. There are 2 elements Vehicle Quality and Comfort and Functionality that generate 75% of customers satisfaction while at the same time creating only 31% of customers loyalty. This example shows how different are both concepts and that company sole orientation on satisfying its customers is not enough to be successful. In order to make customers loyal an automotive company has to take care of many areas that altogether have strong influence on loyalty. Beside Vehicle Quality and Comfort and Functionality it is Overall Satisfaction, Sales Service Quality and After Sales Service quality that all together generate 79% of customers loyalty. The moderate influence on Loyalty (6% each) have cost/price variables: Costs of ownership and Value for money. Expectations, Image of a brand as well as Vehicle Design present rather low influence on both customers satisfaction and loyalty. The comparison of importance scores for each latent construct with regard to its influence on satisfaction and loyalty clears out the direction into which the strategy of Company X in Poland should be heading. To have satisfied and loyal customers, the headquarter of Company X has to produce good quality products that offer proper driving comfort and are functional, while 102
at the same time the sales company in Poland needs to take care mainly of the quality of sales service and after sales service. The sales company can not forget and disregard price positioning of the vehicles with respect to the value they represent in comparison to competition. The level of costs of vehicle ownership is also quite important and needs to be monitored and eventually adjusted to those offered by competitors. This general implications for the total brand might be different if applied to the 3 model groups Compact vehicles, Mid-size sedans and coupes
and Full-size and Large premium
vehicles. The possible differences will be investigated in further analysis. Figure 7.11. Comparison of relative Total Effects on Overall Satisfaction and Loyalty.
50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0%
43% 32% 21%
6%
ua l it y
n V
eh ic le Q
es ig
ey
eh ic le D
alu e V
V
ua l it y ce Q
Se rv i
Sa ti s f
ac ti o
Im ag ve ra ll
Overall satisfaction
18% 1% 1%
0% fo rm on
0% n
e
3% 3%
O
s ec ta tio n
p rsh i ow ne of
Ex p
fo rt Co m Co s ts
ua lit y
5% 0%
Sa le s
6% 1%
3%
al es q fte r-s A
16%
14%
13%
13%
Loyalty
In order to discover the areas where improvement is absolutely necessary, the importance versus satisfaction analysis has to be conducted. Table 1. presents the latent variable scores received from Brand Satisfaction model estimation by PLS procedure. In general for the total brand the score of 78% in overall satisfaction and 83% in loyalty was received. It is difficult to set the minimum value for both indices as there is no direct comparison to previous studies. However comparing BSM to CSI scores and in order to force some improvement of satisfaction and loyalty the authors decided that the minimum
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score for all investigated areas is 85%. Therefore all variables that rank below 85% should be deeply investigated for improvement plan. Table 1. Latent constructs’ scores (rescaled to 0-100).
Latent Variable Expectations Vehicle Design Sales Service Quality Comfort Vehicle quality Loyalty Image Overall satisfaction After-sales quality Value for money Costs of ownership
Score 93% 91% 89% 87% 86% 83% 82% 78% 75% 75% 68%
The highest two scores were noted for the two area, which have very low influence on customers’ satisfaction and loyalty: expectations at the time of purchase and design of the vehicle, which scored 93% and 91% respectively. Two highest scores are followed by 3 very important areas for company’s overall performance which are: Sales Service Quality (89%), Comfort and Functionality (87%) and Vehicle Quality (86%). These 3 constructs have the strongest influence on customer satisfaction and as they received scores above 86%, there is no negative signal for improvement within those 3 areas. Below the minimum score there are 4 quite important areas: Image 82%, After-Sales service quality 75%, Value for Money 75%, Costs of ownership 68%. The company definitely needs to concentrate on these areas in order to improve the overall satisfaction and loyalty of customers. In order to discover what needs to be done to improve evaluation of Company X, the analysis needs to be divided into two approaches. One would be headquarters’ while the other one would be local sales companies’ responsibilities. Such distinction is necessary as headquarter and sales companies are responsible for a bit different areas included in the study. The headquarter is designing and inventing vehicles meaning that it is solely responsible for the vehicle quality, design and the comfort and functionality they provide. At the same time sales companies have very limited influence on the product characteristics - what vehicles are being produced and what quality they provide. On the 104
other hand it is sales company in every country that is responsible for sales and after-sales service quality, costs of ownership. Furthermore, local sales companies in a large part create image of a brand, as well as they offer certain value for money to the consumer by applying certain pricing strategy. As the BSM is conducted on sales company level, the authors decided to split the analysis into: 1. presentation of all results for satisfaction and importance on one Figure 7.12 as an overall picture of Company X performance and importance of particular areas 2. the presentation of only those areas that are under strict or indirect supervision of sales companies as an analysis of local performance – Figure 7.13. Figure 7.12. Satisfaction scores vs. satisfaction importance analysis – overall
95% Satisfaction Score
90%
Vehicle design
85%
Comfort/Functionality
Image
Vehicle quality
80% After-Sales Quality
75%
Value for money
70%
Costs of ownership
65% 60% 0%
10%
20%
30%
40%
50%
Satisfaction Importance
Referring to the figure 7.12, the red line draws the minimum value score for all the areas. Therefore all the areas below this line should be pushed up in order to improve the overall satisfaction score. Looking at the figure it is obvious that among all constructs below the red line the highest influence on satisfaction is given by Value for money (16%) variable and than by After-Sales quality (3%) and Image (3%). Moving on to local sales company performance the spectrum of areas in question is smaller. There are 5 areas, on which performance sales company has some kind of influence. Among them only Sales Service quality is above the red line with unfortunately
105
no influence on customers overall satisfaction. Therefore there are 4 remaining areas which need improvement: Value for money, After Sales service quality, Image and Costs of ownership. They all have different priorities: 69%, 13%, 12% and 6% respectively. However as the responsibility of local sales company, they should all be taken care of. Figure 7.13. Satisfaction scores vs. satisfaction importance analysis – sales company
95%
Satisfaction Score
90%
Sales service quality
85% Image
80% 75%
After-Sales Quality Value for money
70%
Costs of ownership
65% 60% 0%
10%
20%
30%
40%
50%
60%
70%
80%
Satisfaction Importance
In order to discover detailed areas for improvement the importance versus satisfaction analysis have to be performed for each construct on a manifest variables level. Before this detailed approach is implemented, Loyalty concept and the areas that have the highest influence on Loyalty shall be explored. Here the two steps approach have also been applied – overall and sales company specific. As can be seen in Figure 7.14 there are repeating areas such as After-Sales Service Quality, Costs of Ownership, Value for Money and Image that lower the overall loyalty of Company X clients and therefore need improvement. Furthermore the Overall Satisfaction score is also not satisfying enough and has to be improved. If the above mentioned factors are improved, the overall satisfaction score will increase as well, as there are links between the satisfaction and the mentioned areas.
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Figure 7.14. Satisfaction scores vs. loyalty importance analysis - overall
95%
Expectations Sales service quality
Satisfaction Score
90%
Vehicle design
Comfort and functionality
Vehicle quality
85% 80%
Image Value for money
75%
Overall Satisfaction After-Sales Quality
70% Costs of ownership
65% 60% 0%
5%
10%
15%
20%
25%
Loyalty Importance
Figure 7.15. Satisfaction scores vs. loyalty importance analysis – sales company
95% Sales service quality
Satisfaction Score
90% 85% Image
80%
After-Sales Quality
75%
Value for money
70% Costs of ownership
65% 60% 0%
5%
10%
15%
20%
25%
Loyalty Importance
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30%
35%
40%
Moving on to Figure 7.15, local sales company performance on factors that have influence on Company X customers’ loyalty can be analyzed. Again it is After Sales service Quality, Value for Money, Costs of Ownership and Image Variables that negatively influence the level of clients’ loyalty. The only positive sign here is the performance of sales service at dealerships. It definitely pushes the loyalty score above average. After the general analysis of different areas performance and their influence on overall satisfaction and loyalty of Company X customers in Poland, detailed satisfaction vs. importance analysis of areas that need improvement shall be conducted. However there is a strong argument to stop here and make the summary of general analysis. The Brand Satisfaction Model has been designed as a tool for measuring and improving Company X customers’ satisfaction and loyalty in order to create better image of the brand, increase brand sales and its general position on Polish automotive market. Therefore BSM includes areas that are under strict supervision of company’s headquarter, on which sales companies have very poor influence such as vehicle quality, comfort and functionality of the vehicle as well as its design. BSM includes also areas which are either sole responsibility of sales companies or which performance can be improved by local sales companies. Within those areas there is Sales service quality, After-Sales service quality, Value for Money of the vehicle in terms of its pricing strategy, Costs of vehicle ownership and Image of a Brand. Although all the areas have very different weight in terms of generating higher overall satisfaction or loyalty of Company X customers, they should all be taken care of if their score is not satisfactory enough (below 85%). The priorities should be definitely accepted and respected but unless it doesn’t require too much effort from the sales company, all the negatively scoring areas should be analyzed, monitored and improved. Such methodology is not fully consistent with satisfaction vs. importance analysis however due to responsibility split between headquarter and sales company, it is much easier and effective to take care of more areas than the satisfaction vs. importance analysis would suggest. 7.3. Estimation results – Total brand - detailed analysis of performance Having in hand all the areas that need a reparation program, which were discovered in the general analysis of latent constructs performance and importance, the detailed analysis of 108
those areas can be implemented. The performance of headquarter in terms of providing good quality products which offer good design, are comfortable and functional in use is generally well enough. This means that these areas do not need any reparation program but definitely have to be monitored in order to assure at least the same level of customers satisfaction with those areas. What definitely has to be implemented is the program for Company X Polish customers in terms of their satisfaction with work of sales company as well as dealerships representing the brand in Poland. Four areas have been recognized as those that need improvement and the vast amount of responsibility for customers satisfaction with these areas lies in hands of sales company employees as well as the dealer network. The analysis of performance of manifest variables that create After Sales Service Quality, Value for Money, Costs of Ownership and Image will be now presented. The loyalty of customers creates higher value for the company than satisfaction, therefore the analysis will be conducted according to the strength of areas influence on customers’ loyalty (After Sales service quality 30%, Value for Money 15%, Costs of ownership 15%, Image 7% – relative local influence). Taking into consideration the after sales service quality, Company X customers evaluated all factors creating the overall perception of after sales service below 79% - as presented in the Figure 7.16. This creates a significant room for improvement in this area meaning that satisfaction with all elements creating perception of service during customers visits in the workshop is not satisfactory and significantly decreases customers satisfaction and loyalty. All manifest variables generating after sales service latent construct have an importance level of between 9 and 14%. The least significant element according to the research is the availability of substitute car when customer’s vehicle is being serviced. At the same time it has very negative evaluation. The recommendation is that Company X does not have to necessarily take care of this part of post purchase service as its influence on overall satisfaction with after sales service is at the bottom of the list. Than in the middle of importance scale we have availability of spare parts with a bit higher evaluation than in case of substitute car. The logistics issue in terms of proper stock
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management in the logistics center as well as faster delivery of required spare parts should be monitored but not considered as one of the most important factors. The most important elements of service that should definitely be improved as they have the highest influence on customers satisfaction and loyalty and at the same time do not meet customers requirements and expectations are: willingness to properly inform customer about required service, professionalism of after-sales representative, promptitude and timing abidance of service, overall service quality and after-sales service reception atmosphere. It seems that soft skills training for after sales representatives having direct contact with customers is needed. The reps should be trained in order to know what kind of attitude they shall represent in front of the customer meaning that they should serve as a credible source of information. When having contact with customer the rep should concentrate on providing as much information as necessary to make sure that the client knows what needs to be done with his vehicle, how long it will last and how much it shall cost. Furthermore the after sales representatives should be trained with respect to their professional knowledge about technical issues in order to behave professionally when serving a customer. The next important factor strongly affecting customers satisfaction and loyalty is the promptitude of service in terms of quickness of service. This negative evaluation can be connected to shorts of staff in particular after sales service workshops which cause longer waiting lines or to the availability of spare parts which has been negatively evaluated by customers. The whole service logistics process needs to be investigated and parts of the process which extend the service time have to be either eliminated or accelerated. Timing abidance is also a significant element in terms of its influence on satisfaction with after sales service. This can be partly connected to the promptitude of service but in a large part it is the pressure of customers who during the time when vehicle is in the service, do not want to wait too long time and force the after sales rep to declare the earlier vehicle pick up time. In some cases shorts of service staff can also cause the negative evaluation of this area. To summarize, improvement of promptitude of service factor requires that employee count is evaluated and discussed with the staff, but also soft
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skills training could also be valuable in order to train after sales reps to be assertive and to communicate rather longer than shorter service deadlines. The atmosphere in the workshop reception room needs improvement too as it is one of the most important elements of customers service. The client has to feel as someone special and needs to be treated well. Furthermore if customers like the atmosphere of the workshop reception it improves their evaluation of the image of the brand meaning that they feel as someone unique while using the vehicle of the brand. The overall service quality was evaluated negatively meaning that the quality of service provided needs to be improved as customers are definitely not satisfied with what is being done with their vehicles and how well they are served. Figure 7.16. Satisfaction scores vs. loyalty importance – after sales service quality 79 Atmosphere
78
Satisfaction score
77
Timing abidance Willingness to inform Professionalism of rep
76 75
Availability of spare parts
74
Promptitude of service
73
Overall service quality
72 71 70
Availability of substitute car
69 68 9%
10%
11%
12%
13%
14%
Loyalty importance
The value for money construct (figure 7.17) is built out of two elements: price and quality received. As vehicle quality is a separated from value for money latent construct in the analysis therefore value for money factor can be simplified to the pricing strategy of Company X in Poland with respect to the quality of vehicle and service provided. The area was evaluated close to 75% which is definitely too low score and it needs to be improved. It is difficult to judge whether the prices of vehicles should be drastically decreased. However the pricing list modification is required in order to make the price
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positioning against main competitors more acceptable for Company X customers. Probably customers do not see such a big difference between Company X and other brands in terms of vehicle quality, sales and after sales service, comfort and functionality of the vehicles etc. but they see the difference in price positioning. Improvement of this element could definitely increase customers satisfaction and loyalty against the brand. However the sales company has to be careful at the same time as price is also the antecedent of value of the vehicle provided that it offers proper quality and comfort of usage. Therefore too low pricing can deteriorate value of a brand in eyes of its clients.
Figure 7.17. Satisfaction scores vs. loyalty importance – Value for money
76 75
Vehicle quality with respect to its price
Satisfaction Score
75 74
Price of the vehicle with respect to its quality
74 73 73 72 72 71 49,0%
50,0%
51,0%
Loyalty Importance
Analyzing evaluation of costs of ownership (figure 7.18) it seems that the lowest score is given in the areas of after-sales service responsibility and costs of vehicle insurance. Insurance is the least important factor among the others however the difference in the importance levels is not that big to definitely ignore this element. Insurance can serve as first of all attractive sales incentive for customers as well as advertising keyword to attract customers to the showrooms.
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Coming back to satisfaction with costs of after sales service it seems like Company X in Poland has quite a problem with general perception of workshop service. It is not only expensive but at the same time not satisfactory enough. Again the pricing strategy needs to be revised in order to make brands of Company X more competitive and maybe some promotional events decreasing costs of Company X vehicle usage such as free service for winter and summer holidays could also be introduced. Figure 7.18. Satisfaction scores vs. loyalty importance – Costs of ownership
80 78
Costs of fuel
Satisfaction Score
76
Overall costs of vehicle usage
74 72 70 68
Costs of regular service
66 64
Costs of repairs
Costs of insurance
Costs of spare parts
62 60 13%
14%
15%
16%
17%
18%
19%
Loyalty Importance
Costs of fuel are not that important comparing to the costs of after sales service however some inexpensive improvement in this area could also be implemented. Fuel card with a limit of e.g. 3% of a price of the vehicle given with each car sold may be a good mean for improving customers satisfaction with costs of ownership. Next idea is to offer a fully tanked vehicle after each visit to a workshop which costs exceeds e.g. 100 PLN. Image of a brand (figure 7.19) is also in large portion a responsibility of sales company locally in particular country. In this case Company X in Poland should definitely increase its involvement in customers’ satisfaction improvement by e.g. allowing customers to
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express their opinion about the quality that they receive. The researches such as Brand Satisfaction Model give the possibility for each customer to speak up and evaluate the brand in terms of soft service and vehicle quality and comfort that they receive. It gives the strong feeling to the customers that the brand takes care about them and wants to listen to their opinions in order to improve its performance and at the same time its clients satisfaction. Figure 7.19. Satisfaction scores vs. loyalty importance – Image
93 Safety assurance
Satisfaction Score
88
Stable market position of a brand
83
Technological leadership Environmental care
Overall image
78 73
Making drivers' lives easier Brand involvement in improvement of customers satisfaction
Promotional Visibility (motorshows, sponsoring, advertising) Involvement in social actions
68 8,5%
9,5%
10,5%
11,5%
12,5%
13,5%
Loyalty Importance
Technological leadership is on the edge of 85% bottom line. Such position can be a result of the fact that either the competition is quite close to Company X in terms of technological advancements or Company X customers are not aware of its brand advantage over competitors. The best solution here is surely better communication of all most important advantages of Company X vehicles in terms of modern technology used in them. The area called “making drivers’ lives easier” also has to be improved and it may be definitely connected with the above mentioned factor which is technological advantage over its main competitors.
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Factors that increase customers evaluation of a brand with regard to its image are: safety assurance and its stable market position. This areas improve overall score meaning that Company X vehicles are definitely safe in the eyes of clients, the position of a brand is very stable on the market and is not deteriorating. The elements that are of lower importance are environmental care, company’s involvement in social actions and promotional visibility of a brand in terms of its presence on motor shows, in advertising campaigns and sponsoring. As the difference in importance levels is not that significant these above mentioned areas could also be improved in order to increase the score of overall image perception especially having in mind that they are some basic factors of company’s presence on particular market.
7.4. Estimation results for Brand Satisfaction Model – 3 segments of customers The analysis presented in previous chapter is applied to total brand, meaning Company X customers in general. However there are different groups of customers with different profiles depending on what vehicle they buy. Different customers have various demographic characteristics and needs which impact their requirements towards vehicles they drive.
Therefore the authors decided to perform 3 separate analysis based on
different customer groups: Compact vehicles owners, Mid-size vehicles owners and FullSize and Large vehicles owners. The aim of the study is to discover main differences between customer groups which have different requirements for the vehicle they drive as well as different demographic characteristics and the amount of income they want to spend on vehicle. 7.4.1. General estimation results for 3 customer segments The parameter estimates for inner model as well as R square values for all dependent variables are presented in Figure 7.20, 7.21 and 7.22 for three model groups respectively. We can see quite different parameter estimates for three vehicles groups. In order to analyze differences between the customer segments we should firstly take a look at the comparison of satisfaction scores presented in Table 1. 115
Table 1. Latent constructs’ scores for 3 model groups (rescaled to 0-100). Expectations
92%
92%
Full-size and Large 95%
Vehicle Design
89%
90%
92%
Sales quality
88%
89%
88%
Comfort
86%
86%
88%
Vehicle quality
85%
88%
85%
Loyalty
83%
86%
81%
Image
82%
83%
82%
Overall satisfaction
77%
81%
77%
After-sales quality
75%
78%
74%
Value for money
74%
77%
73%
Costs of ownership
67%
67%
70%
Variable
Compact
Mid-size
Generally, with minor exceptions, the overall evaluation of particular latent areas is similar concerning the hierarchy of scores meaning that the highest scores for all customer groups are given to expectations and vehicle design and than to sales service quality, comfort and functionality, vehicle quality followed by loyalty, image, overall satisfaction, after sales service quality, value for money and costs of ownership. Figure 7.20. Results of PLS algorithm application on BSM – Compact vehicles.
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Figure 7.21. Results of PLS algorithm application on BSM – Mid-size vehicles.
Figure 7.22. Results of PLS algorithm application on BSM – Full-size and Large vehicles.
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However looking at the Table 1 in more detail, significant differences between evaluation of particular latent constructs are discovered. First of all some trends are visible if we compare scores of one variable for all model groups. Rising expectations moving towards Full-size and Large vehicles customer group are observed what is understandable having in mind the fact that these clients are wealthiest segment and spend more money on their vehicles at the same time expecting more from quality and service they will receive. Secondly, the evaluation of vehicle design is also rising moving from Compact to Large vehicles group. This also does not require very deep investigation as simply the vehicle design of more expensive, more luxurious vehicles catches the eyes of most customers. Finally, similar relationship can be found for all model groups regarding comfort and functionality of the cars. Larger vehicles are usually more comfortable, better equipped and because they are usually more expensive they use modern technology what increases their functionality. In case of costs of ownership the wealthier the customer segment, the higher the satisfaction with costs of vehicle usage what is natural and does not require any comment. Two variables have almost constant satisfaction scores for all groups of customers. Image scores between 82 and 83 while sales service quality is evaluated at the level of 88 to 89% which positions this area at the top of the list. Regarding the sales service quality it can be argued as natural state however in real life its sometimes difficult to train the sales staff in order to maintain the same and high level of service provided for all customer groups. In case of Company X this is really a success that the sales staff does not prioritize the customers who are wealthier and able to spend more money which in the end reach pockets of sales representatives. The more expensive the vehicle the more money goes to the person that sold it to the customer. Naturally sales staff would like to earn more money thus providing better service for those customers who are wiling to buy more expensive vehicle. Therefore it is a big value of Company X dealer network responsible for sales service quality which offers high and at the same time similar level of service no matter how wealthy the customer is. Analyzing other variables we can also see a strong trend although it does not depend on the size and price of the vehicle. For vehicle quality, after-sales service quality, value for money and overall satisfaction as well as loyalty, one group stands out of the crowd. It is a group of mid-size vehicles customers that on average in all the above mentioned areas 118
scores better than other model groups. This means that these vehicles offer higher quality in terms of dependability, driving quality etc. therefore creating higher value for money for mid-size vehicles owners. Surprising is the fact that the after sales service quality received by this group of customers is also higher than for compact cars and large vehicles owners. Maybe the number of visits to the workshop was lower for the group which could go in line with higher vehicle quality evaluation meaning that mid-size vehicles customers were not able to receive so much not satisfactory service from after-sales service department. Because the score on vehicle quality, value for money and after sales service quality is higher than in other groups the overall satisfaction as well as loyalty of mid-size vehicles owners scores also above other model groups. 7.4.2. Total effects analysis – 3 customer segments Let’s compare the strength of influence of all latent constructs on satisfaction and loyalty between all customer groups included in the study. Figure 7.23 presents the influence of every latent variable on overall satisfaction scores divided into customer segments. It can be observed that in terms of overall satisfaction generation the customers are quite unanimous. There are 3 exceptions from the rule. First of all image of a brand is much more important for compact vehicles users than for midsize or full-size cars owners, what is in line with customer profile research results. It seems that customers that buy the least expensive vehicle in Company X portfolio very much appreciate the image that the brand acquired during its presence on the market. On the other hand brand image is of little importance for premium customers who buy expensive vehicles. For these customers the other factors count when it comes to creation of their overall satisfaction. They are satisfied not due to brand image, but because the vehicle offers high quality and comfort that also generates higher perceived value. If value for money factor is analyzed, it can be observed that it is of highest importance for compact vehicles users and the lowest important for mid-size cars users. Generally customers who buy compact vehicles of Company X brand expect decent value for money that they have to pay. This is understandable as, referring to the results of customer profile study, clients with lowest income are more price sensitive and they require more for what they pay. On the other hand, value for money factor is of lowest importance for 119
satisfaction of owners of mid-size cars, while it is more important for full size and large cars owners. Mid-size vehicles clients break out of the pattern probably because their evaluation of vehicle quality is better than in case of other clients. That is why the value for money factor is not as important for mid size cars owners as for other customer segments, because they perceive quality as more important driver of their satisfaction than other customer segments do. Figure 7.23. Influence of latent constructs on overall satisfaction – comparison between different customers’ groups
60% 50% 40% 30% 20% 10%
sa tis fa ct io n Sa le sq ua V lit alu y ef or m on Ve ey hi cl eD es ig V n eh ic le qu ali ty
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Moving to vehicle quality, comfort and functionality it seems that customers that pay more for their vehicles require higher dependability and quality as well as comfort of the car they drive. The importance of this latent constructs is almost equal for mid-size, fullsize and large vehicles clients (46-49% - vehicle quality, 35% comfort and functionality) while compact cars users pay less attention to both factors (36% and 30% respectively). This may be easily explained by the fact that wealthier customers expect higher values in their products
what means that they have to be of good quality and offer decent
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functionality as well as comfort of driving. On the other hand compact vehicles users pay more attention to the value for money that is offered by their products as well as image of the brand. Due to premium character of a brand the “compact” customers pay more for the Company X vehicles comparing to direct competition thus expecting higher perceived value and proper image of the brand they represent. . Let’s now move on to analysis of different satisfaction areas influence on customers loyalty. Taking a closer look at Figure 7.24 it seems that loyalty construct is definitely much more complicated than satisfaction and requires deeper insight. Among all factors, only vehicle design and overall satisfaction are the areas which have similar importance level for all customer groups. Analyzing the importance of after sales service quality we discover that the more customers pay for their vehicles the less they require from after sales service in order to become loyal to the brand and dealer. For ”mid-size”, “full-size” and “large” clients there are 2 other factors that they pay special attention too – vehicle quality and comfort and functionality. Costs of vehicle ownership and usage are of course more important for “compact” customers than for “mid-size” clients and the least important for those clients who pay the most for their cars. This can be easily explained by different income levels for the 3 analyzed clients’ groups, what was also observed in customer profile research. Moving to expectations it seems obvious that higher segments clients demand more from the vehicle and the brand what was confirmed by the Brand Satisfaction Model study. The importance of Image against Loyalty goes in line with Image importance against Overall Satisfaction and can be explained in the same manner. There is a big gap between strength of influence of sales service quality on customers loyalty between customers of compact vehicles and the rest. “Mid-size”, “full-size” and “large” customers demand much more from sales service quality and position this factor as the second important for their loyalty towards a brand. At the same time compact cars users diminish the importance of this factor placing it behind vehicle quality, comfort and functionality, after-sales service quality and value for money. This discrepancy gives the marketers quite important message that the “mid-size” and “full-size and large” customers
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need to receive extraordinary sales service in order to make them loyal to the Company X brand. Figure 7.24. Influence of latent constructs on loyalty – comparison between different customers’ groups
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Finishing the loyalty importance analysis it is discovered that value for money is definitely of highest importance for “compact” clients but at the same time it is the least important for “mid-size” customers. Clients of higher segments place the importance of this element somewhere in between the scores for two other groups. Again the lowest importance of this area for mid-size vehicle users can be explained by the highest quality level of vehicles they drive comparing to the rest of model groups. To sum up we discovered definitely different profiles of the three analyzed groups of clients. They differ not so much in terms of their definition of overall satisfaction however differences with regard to loyalty generation are significant in many aspects of customers satisfaction. We can in some part merge the mid-size, full-size and large vehicles’ clients but the “compact” customers differ a lot from the others. While “compact” clients are
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more price sensitive and pay a lot of attention to value for money of their vehicle as well as to the after-sales service quality they receive in the workshop, the remaining two customer segments require more from vehicle quality and especially from sales service quality. These findings are in line with customer profile research which revealed, than compact car customers are more price sensitive and more often than other customer segments search for vehicles, which are functional and economical. 7.4.3. Satisfaction vs. importance analysis - 3 clients segments - inner model Let’s analyze differences between the 3 model groups on a satisfaction vs. importance analysis figures. As discussed earlier we discovered 4 areas that definitely need improvement with regard to total brand. It will be good to know whether the same rule applies to all customers or there are some differences in approach to increase satisfaction and loyalty of customers. There might be either one strategy which could be applied to all customers segments or more strategies may arise in order to better serve needs of customers who, depending on the segment, may have different requirements against the brand performance. This part of analysis will help understand the differences between customers of Company X in Poland not only through comparison of the scores of satisfaction for specified areas but also by discovering different priorities lists for all the elements included in the study. The graphical representation of satisfaction versus importance analysis will not include the division of matrix into important and not important areas due to the fact that not all of the areas are under direct supervision of neither the headquarter nor sales company. Therefore further analysis will have to be adjusted to either sales company or headquarter perspective. The authors concentrate on performance of sales company thus such analysis should include only those factors that are directly controlled by Company X in Poland. Figures 7.25 to 7.30 present satisfaction scores for all latent variables versus their influence on either satisfaction or loyalty and are divided into 3 customers segments: Compact , Mid-size and Full-size and large vehicles owners. The analysis will allow for distinguishing important areas creating satisfaction and loyalty of customers in 3 segments.
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Figure 7.25. Satisfaction scores vs. satisfaction importance analysis – Compact vehicles
100% 95% Expectations
Satisfaction Score
90%
Vehicle design
Comfort and functionality
Sales service quality
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Vehicle quality
Image
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After sales service quality
Value for money
70% Costs of ownership
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Satisfaction Importance
Figure 7.26. Satisfaction scores vs. loyalty importance analysis – Compact vehicles
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Vehicle design
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Vehicle quality
Image
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Overall satisfaction
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Costs of ownership
65% 60% 0%
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20%
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Figure 7.27. Satisfaction scores vs. satisfaction importance analysis – Mid-size vehicles
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Expectations Vehicle design
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Image
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75% 70% Costs of ownership
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Figure 7.28. Satisfaction scores vs. loyalty importance analysis – Mid-size vehicles
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Vehicle design Comfort and functionality
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Vehicle quality Sales service quality
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Figure 7.29. Satisfaction scores vs. satisfaction importance analysis – Full-size and large vehicles
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90%
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Figure 7.30. Satisfaction scores vs. loyalty importance analysis – Full-size and large vehicles
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Expectations Vehicle design
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Sales service quality Vehicle quality
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Division of the analysis into different customer segments does not significantly change the overall picture. Again the most important is loyalty but the loyalty is in a large part created by overall satisfaction. Fortunately outcome from satisfaction importance and loyalty importance analysis is the same. There are definitely four areas that score much 126
below the minimum level of 85%. After sales service quality, value for money, costs of ownership and image need to be taken care of in order to improve overall satisfaction and loyalty of Company X customers in Poland. The strength of influence on satisfaction and loyalty generation is not that significant compared to e.g. vehicle quality or comfort and functionality however as discussed earlier this is the scope of responsibility for sales company in Poland. The other factors beside sales service quality (where score is high enough and positively influences satisfaction and loyalty) are beside the direct responsibility of sales company representing brand in Poland. Furthermore the score on those factors lies above the red line of 85% thus the improvement of brand performance in this respect is definitely more difficult to achieve. The segmentation of customers does not produce different results in terms of which areas score the lowest and have quite strong influence on satisfaction and loyalty creation. The only difference is prioritization of the four areas. For all groups of customers analyzed in the study between the four analyzed areas for improvement action the most important is the quality of after-sales service. Value for money is the second important element with exception of mid-size vehicles customers that place this element at the end of the list. Very close to value for money factor with regard to its strength of influence lies the costs of ownership variable. The least important element is the image of a brand. 7.4.4. Satisfaction vs. importance analysis - 3 customer segments –outer model In order to roll out some action plan the detailed analysis needs to be performed analogically to the one carried out for the total brand. Analyzing after sales service quality, for all customer groups professionalism of sales representatives, willingness to properly inform customers, overall service quality, promptitude of service and timing abidance are the most important elements generating the largest part of overall after-sales service satisfaction. For mid-size vehicles customers the atmosphere of showroom is placed at the 6th position of importance list while for the two other model groups it is one of the most important elements. Availability of spare parts is in the middle range of strength of influence for all customers. At the bottom of 127
the list for after sales service quality is the availability of substitute vehicle. It is the least important area and at the same time it scores the lowest for mid-size and full-size vehicles clients which is understandable as the more customers spend on their vehicle the more service they require if their car visits the workshop. If it comes to evaluation of customers satisfaction with particular elements of after-sales service it occurs that all of them score much below the minimum level of 85% which means that they all need to be taken care of however with different prioritization list for different model ranges. The most satisfied customers with after-sales service are the ones who drive the mid-size vehicles. However the score is not satisfactory enough to resign from reparation program. Therefore the action plan needs to be invented in order to improve customers’ satisfaction with service offered by after-sales department at the dealerships with accordance to the presented priorities list. It seems that a small “revolution” is needed in order fix all the problems as there is no positive sign of service which is satisfactory for the clients.
Figure 7.31. Satisfaction score vs. loyalty importance – After sales service– Compact vehicles
83,0% Satisfaction Score
81,0% 79,0%
Timing abidance
Atmosphere
77,0% 75,0%
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73,0%
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Figure 7.32. Satisfaction score vs. loyalty importance – After sales service – Mid-size
Satisfaction Score
vehicles
83% 81% 79% 77% 75% 73% 71% 69% 67% 65% 63%
Timing abidance Availability of spare parts
Professionalism of rep
Promptitude of service Atmosphere
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Figure 7.33. Satisfaction score vs. loyalty importance – After sales service – Full-size and large vehicles
83,0% Satisfaction Score
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79,0% 77,0%
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Moving on to value for money evaluation there are two elements that create it. It is generally perceived product quality with regard to its price. As the perception of product quality itself and its comfort and functionality is good enough the only element that needs improvement is the level of price. Generally customers perceive Company X vehicles as being too expensive with regard to the overall quality they offer. Therefore some repricing program might be useful in order to improve the perceived value of cars. This element might be also dangerous as too much intervention into pricing policy may diminish the value of particular brand vehicles. Price is also the factor that creates value of the car thus it needs to be carefully tailored to each model against competition. The value for money score is the lowest for full-size and large vehicles owners than for compact cars and the highest for mid-size range. Therefore it seems that pricing policy has to be definitely adjusted for the least and the most expensive vehicles and only slightly for the middle sized cars. Figure 7.34. Satisfaction score vs. loyalty importance – Value for money– Compact, Midsize, Full-size and large vehicles
78% Satisfaction Score
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Vehicle quality with respect to its price - Mid-size Price of the vehicle with respect to its quality - Mid-size
76% 75% 74% 73% 72% 48,0%
Vehicle quality with respect to its price - Compact Price of the vehicle with respect to its quality - Compact Vehicle quality with respect to its price - Full-size and large Price of the vehicle with respect to its quality - Full-size and large
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Loyalty Importance
Moving to detailed analysis of costs of ownership, it is apparent that comparing to results for the total brand there are not many differences. For all model groups the highest importance and at the same time the lowest scores are given for costs of regular service,
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costs of spare parts and repairs. After sales service pricing list needs to be adjusted in order to improve customers perception of this area and at the end their loyalty. Figure 7.35. Satisfaction score vs. loyalty importance – Costs of ownership – Compact vehicles
Overall costs of vehicle usage
Satisfaction Score
78,0% 76,0%
Costs of fuel
74,0% 72,0% 70,0% 68,0%
Costs of regular service
66,0% 64,0%
Costs of insurance Costs of spare parts
62,0% 60,0%
Costs of repairs
12,0% 13,0% 14,0% 15,0% 16,0% 17,0% 18,0% 19,0% 20,0% Loyalty Importance
Figure 7.36. Satisfaction score vs. loyalty importance – Costs of ownership – Mid-size vehicles
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Costs of repairs
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Furthermore costs of fuel are the least important for clients of full-size and large vehicles which is understandable. The strength of their importance rises while moving towards less expensive segments of cars. Costs of insurance are the least important for compact and mid-size vehicles customers and move one position up in the list for full-size and large vehicles owners. To sum up general evaluation of costs of ownership it seems that first thing that should be improved is the pricing policy of after sales service department. This result proves negative evaluation of this area in total. Next elements that could improve customers satisfaction and loyalty lie in the area of responsibility of sales department. Costs of fuel or insurance may be decreased by incentive campaigns where i.e. fuel card with particular limit or free insurance could be given to customers at the purchase of the vehicle. Figure 7.37. Satisfaction score vs. loyalty importance – Costs of ownership – Full-size and large vehicles
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Loyalty Importance
In terms of image, the company involvement in improvement of customers satisfaction definitely needs to be increased. Such researches as brand satisfaction model give clients the possibility to speak up and express their opinion about the brand and the offered products. This area is not evaluated as satisfactory enough and for all model groups lies at the top of the importance list. Customers evaluation of sales company involvement in 132
actions that make the driver’s lives easier scores also below 85% and is one of the most important elements creating brand image. As the area is not precise it needs to be investigated in more details by maybe a small, one time conversation with the group of customers. Stable market position and safety and technological leadership are also important elements for all model groups however their score lies above minimum level of 85% thus they need no improvement. Figure 7.38. Satisfaction score vs. loyalty importance – Image – Compact vehicles
95,0% Safety assurance
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Technological leadership
85,0% Environmental care
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Safety assurance gives very interesting field for analysis. The score for each model range is one of the highest and also does not need any reparation action. However for compact vehicles owners it is one of the most important factors, while for mid-size vehicles clients is the least important one and for full-size and large vehicles customers is placed in the middle of importance scale. These findings are in-line with customer profile research, which pointed out that safety is much more important factor for compact cars owners, than for remaining customer segments. Environmental care is not that much important for “compact” clients while it moves to the middle importance for the two other model groups. As it scores below 85% in each case it requires some action to be taken. One of
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the actions suggested would be more news about ecological properties of Company X vehicles given to press and media in order to improve brand image in this respect. Figure 7.39. Satisfaction score vs. loyalty importance – Image – Mid-size vehicles
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Figure 7.40. Satisfaction score vs. loyalty importance – Image – Full-size and large vehicles
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Involvement in social actions is evaluated as the worst element of brand image however its importance is the lowest for all models. The company may think about some action plan in this area provided that all other elements that have higher priority are taken care of. Generally promotional visibility of a brand is of middle importance for lower segments customers and is the least important for full-size and large vehicles owners. As its score is below 85% in each case the company may introduce some program that will improve brand visibility in media, press and outdoor visuals especially in the two lowest segments. To sum up the analysis of image it seems that beside safety assurance, customers evaluation of brand stability and technological leadership, the company needs to take care of all the other elements that create brand image. The priority list is a bit different for different model ranges however it can be merged in order to save resources and achieve a goal of image improvement. 7.4.5. Summary of analysis for 3 customer segments The three analyzed groups of customers present a bit different approach to purchasing and using a vehicle. While their satisfaction is generated in quite similar manner, the loyalty generation is much more complicated. The owners of compact vehicles place more importance in Value for Money and Costs of Ownership meaning that they are simply more price/costs sensitive. Such result is definitely understandable as limited amount of resources forces the more cost saving approach while deciding on vehicle purchase. Furthermore After-sales service is the most important element for compact cars users. The other two groups of customers place less importance in this area. Mid-size, Full-size and Large vehicles owners are more similar to each other compared to the compact cars customers. Instead of placing more importance to after-sales service quality, costs of ownership and Value for money, their loyalty is in a larger part generated by better sales service quality, vehicle quality as well as comfort and functionality. In order to implement some action plan the detailed analysis of the four areas that need improvement presented above in the chapter should be deeply investigated. Some detailed 135
areas score better or lower for different customer groups. Furthermore the importance of the areas is different for the three analyzed customer segments. All in all, the action plan for the total brand has to be adjusted according to differences in results achieved in the analysis. The acquired intelligence about levels of importance should be made wellknown across the whole company in order to prioritize or disregard taken operations.
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CONCLUSIONS AND RECOMMENDATIONS After detailed analysis of Brand Satisfaction Model results the following conclusions and recommendations arisen: -
The structure of BSM evolving mainly from ECSI and JD Power methodology for automotive industry is comprehensive, statistically well grounded and offers a great portion of knowledge for Company X in Poland. It covers all important aspects of customer satisfaction as total experience with a brand. The BSM not only covers evaluation of company’s performance in different areas but, what is most important, distinguishes the importance of specified areas to overall satisfaction and loyalty generation.
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The BSM model discovered that there are significant differences in how satisfaction and loyalty of customers are created. Satisfaction concept in the automotive industry is less complicated and is based mainly on vehicle quality, comfort and functionality which generate over 75% of customers satisfaction. On the other hand client’s loyalty is much more complex. Importance of vehicle quality, comfort and functionality decreases while at the same time the importance of sales and after sales service quality as well as costs of ownership drastically increases. Therefore there are not 2 but 5 factors that should be taken into account when implementing loyalty improvement programs.
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There are different perceptions of satisfaction and loyalty concepts between the 3 specified segments of customers. Compact vehicles users are much more price and costs sensitive. They also pay stronger attention to the image of a brand and post-purchase service they receive. Mid-size vehicles users are definitely closer in terms of their profile to the third group of customers however they are more vehicle comfort and quality oriented while at the same time do not expect so high value for money as other clients. The full-size and large vehicles owners are definitely the least price and costs sensitive. Vehicle quality, comfort and functionality and sales service quality are the most important elements strongly affecting the level of their loyalty.
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Company X should definitely conduct the Brand Satisfaction Model study at least on a yearly basis. The knowledge should be regularly spread across the entire organization and management should make sure that all employees understand their customers according to BSM findings. Marketing, sales and PR actions should always take into consideration the recommendations of BSM in order to create more satisfied and loyal customers. The 137
operations should be adjusted according to different customer profiles analyzed in the study as clients from different segments have different priorities lists. Therefore all measures such as incentive actions, communication, improvement of customer service processes should be targeted at specific wants and needs of particular segment. -
After the Brand Satisfaction Model was conducted, analyzed and the acquired knowledge was spread out across the whole company, the reparation program for after-sales service quality has started. First improvements are already visible in higher scores (+2 pp) for CSI in after-sales service quality. According to BSM findings the prioritization of actions has been set which helped to concentrate on those areas that have the strongest influence on quality of after-sales service. This is a short term success which hopefully will turn into long term trend.
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The next valuable step would be to propose the BSM as a unified tool for measuring satisfaction and loyalty of customers in the whole automotive sector in Poland. The model could be proposed to the Board of Directors of Polish Official Association of Automotive Importers in order to create a comprehensive platform for comparison of different brands performance in a field of customer satisfaction. Such platform would be not only valuable for automotive companies present on Polish markets but also for customers which would benefit from higher level of service provided. This step could ignite the positive improvement of competitiveness between automotive producers operating in Poland.
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REFERENCES ANDERSON, E.W., FORNELL, C., LEHMANN, D.R. (1994): “Customer satisfaction, market share and profitability: Findings from Sweden”. Journal of Marketing, vol. 58 (3), pp. 53-66 ANDERSON, E.W., FORNELL, C., RUST, R.T. (1994): “Customer satisfaction, productivity and profitability: differences between goods and services”. Marketing Science, vol. 16 (2), pp. 129 – 45 ANDERSON, E. W., BRYANT, B. E., CHA, J., FORNELL, C., JOHNSON, M.D. (1996): “The American Customer Satisfaction Index: Nature, Purpose and Findings”. Journal of Marketing, vol. 60, pp. 7 – 18 ANDREASSEN, T.W., CHA, J., GUSTAFSSON, A., JOHNSON, M.D., LERVIK, L. (2001): “The evolution and future of national customer satisfaction index models”. Journal of Economic Psychology, vol. 22, pp. 217 – 245 BAYOL M.P. DE LA FOYE A., TELLIER C., TENENHAUS M. (2000): “Use of PLS Path Modeling to Estimate the European Consumer Satisfaction Index (ECSI) Model”, Statistica Applicata – Italian Journal of Applied Statistics, vol. 12, no 3, pp. 361-375. CHIN W.W. (1998): “The partial least squares approach for structural equation modeling”, in G.A. Marcoulides , Modern Methods for Business Research, Lawrence Erlbaum Associates, pp. 295-336. CHIN W.W. & NEWSTED P.R. (1999): “Structural Equation Modeling Analysis with Small Samples using Partial Least Squares”, in:Hoyle R., Statistical STartegies for Small Sample Research, Sage Publications, pp. 307-341. CHIN W.W. (2001): “PLS-Graph User’s Guide”, C.T. Bauer College of Business, University of Houston, USA.
139
www.efqm.org FORNELL C., & LARCKER D. (1981): “Evaluating structural equation models with unobservable variables and measurement error”, Journal of Marketing Research, 18, pp.39-50. FORNELL C. (1992): “A National Customer Satisfaction Barometer: The Swedish Experience”, Journal of Marketing, Vol. 56, 6-21. FORNELL C. & CHA J. (1994): “Partial Least Squares”, in Advanced Methods of Marketing Research, R.P. Bagozzi, Basil Blackwell, Cambridge, MA., pp. 52-78. GRONHOLDT, L., KRISTENSEN, K., MARTENSEN, A. (2000): “The relationship between customer satisfaction and loyalty: cross-industry differences”. Total Quality Management, vol. 11, pp. 509 – 514 GRONHOLDT, L., KRISTENSEN, K., MARTENSEN, A. (2002): “Customer satisfaction and business performance” in “Business performance measurement: Theory and Practice”, Cambridge University Press, pp. 280 – 283 GUSTAFSSON, A., HERRMANN, A., HUBER, F., JOHNSON, M.D. (1997): “Customer retention in the automotive industry. Quality, satisfaction and loyalty”, Gabler, pp. 119 – 223 HOPTON, CH., MARKEY, R.G., REICHHELD, F.F. (2000): “The loyalty effect – the relationship between loyalty and profits”. European Business Journal, vol.12 no.3, pp. 134- 139 www.jdpower.com JOHNSON, M.D. (1996): “Customer orientation and market action”. Prentice Hall, pp. 42 – 108 KLINE, R. B. (1998). “Structural equation modeling”, London: The Guilford Press
140
LOHMÖLLER J.-B. (1984): LVPLS Program Manual, Version 1.6, Zentralarchiv für Empirische Sozialforschung, Universität zu Köln, Köln. LOHMÖLLER J.-B. (1989): “Latent Variables Path Modeling with Partial Least Squares, Physica-Verlag, Heildelberg. MUELLER, R. O. (1999). “Basic principles of structural equation modeling. An introduction to LISREL and EQS.”, Springer-Verlag: New York MYERS J.H., MULLET G.M. “Structural Equation Models”, chapter 15 of “Managerial Application of Multivariate Analysis in Marketing”, Thomson, 2003. TENENHAUS, M; VINZI, V. E.; CHATELINC, Y.-M. and LAUROB, C. (2005): “PLS path modeling.”, Computational Statistics and Data Analyses, no. 48, pp. 159-205 The EFQM Excellence Model 1999 manual. Aarhus School of Business, Business Performance Management Program WOLD, H. (1982). “Soft modelling: the basic design and some extensions.”, In Jöreskog, K.G. and Wold, H. “Systems under indirect observations, Part II”, Amsterdam: North Holland Press WOLD H. (1985): “Partial Least Squares”, in Encyclopedia of Statistical Sciences, vol. 6, Kotz, S&Johnson, N.L., John Wiley & Sons, New York, pp. 581-591.
141
APPENDICES Appendix 1. Latent Variables Correlation matrix (First Version of BSM) Aftersales qualit y
Comf ort
Costs of owner ship
Expect ations
Image
Loyal ty
Overall satisfa ction
Sales qualit y
Value Vehic Vehic for le le mone Desig qualit y n y
Aftersales quality
1,000 000
Comfort
0,462 303
1,000 000
Costs of ownersh ip
0,472 885
0,540 268
1,0000 00
Expectat ions
0,195 676
0,419 443
0,2336 57
1,00000 0
Image
0,467 905
0,723 528
0,4962 45
0,36794 3
1,0000 00
Loyalty
0,577 201
0,544 896
0,4430 39
0,19953 7
0,6073 74
1,000 000
Overall satisfact ion
0,473 978
0,594 959
0,4804 12
0,27064 4
0,6840 18
0,665 158
1,0000 00
Sales quality
0,436 633
0,541 961
0,3750 76
0,32045 7
0,4818 02
0,551 462
0,3487 33
1,0000 00
Value for money
0,561 808
0,643 671
0,5313 82
0,29853 7
0,6873 65
0,655 578
0,7730 88
0,4052 19
1,000 000
Vehicle Design
0,271 908
0,668 756
0,3893 03
0,39787 0
0,5674 09
0,400 030
0,4127 73
0,4628 21
0,431 422
1,000 000
Vehicle quality
0,507 657
0,744 820
0,5183 36
0,28770 4
0,7358 78
0,671 108
0,8412 18
0,4224 55
0,807 373
0,568 071
142
1,000 000
Appendix 2. Results of Bootstrapping algorithm application on the final structure of the Brand Satisfaction Model (sample size 346, number of iterations 500) Outer Model T-Statistic Costs AfterCom of sales fort owne quality rship comfor t
23,3 479 65
comfor t%a
30,1 337 15
comfor t%b
19,4 628 46
comfor t%c
16,7 891 08
comfor t%d
9,56 163 8
comfor t%e
16,0 563 96
comfor t%f
13,3 499 30
comfor t%g
10,3 806 44
comfor t%h
8,81 846 2
costs
18,04 5577
costs %a
12,35 5443
costs %b
13,25 4982
costs %c
43,04 7303
costs %d
41,80 3177
costs
40,78
Expec tation s
Imag e
Loyalt y
143
Overa Sales ll qualit satisf y action
Value for money
Vehicle Design
Vehicle quality
%e
8004
design
58,4998 48
design %a
41,3434 76
design %b
40,3026 58
design %c
58,7475 64
design %d
47,2310 27
image
17,03 3243
image %a
14,58 1061
image %b
17,07 4691
image %c
27,02 9983
image %d
24,12 7112
image %e
9,084 976
image %f
9,776 476
image %g
11,19 7843
image %h
20,87 3509
loyalty 1
35,31 6365
loyalty 2
32,05 0081
loyalty 3
28,20 4140
loyalty 4
15,11 8128
oczek %d
23,31 8976
oczek %f
23,67 6596
oczek %g
33,34 7890
sales
30,00 9971
sales
26,46
144
%a
1719
sales %b
29,92 6009
sales %c
26,38 0701
sales %d
33,18 0027
sales %e
34,55 3519
sales %f
16,71 1855
sales %g
15,77 3017
sales %h
16,19 3364
sales %i
15,71 6443
sales %j
12,89 3444
sat1
126,7 03100
sat1a
124,8 51939
sat1b
148,7 10726
service
69,8193 07
service 69,8322 %a 65 service 87,3355 %b 71 service 36,9407 %c 96 service 14,4349 %d 00 service 25,7976 %e 21 service 58,0036 %f 85 service 35,6557 %g 48 value1
472,423 591
value2
489,753 636
vehqua
47,9541
145
l
61
vehqua l%a
31,6665 12
vehqua l%b
11,9413 13
vehqua l%c
10,9076 35
vehqua l%d
14,5858 02
vehqua l%e
19,9560 50
vehqua l%f
20,4257 33
vehqua l%g
12,2437 94
Path Coefficients (Mean, STDEV, T-Values)
Original Sample (O)
Sample Mean (M)
Standard Deviation (STDEV)
Standard Error (STERR)
T Statistics (|O/STERR|)
After-sales quality > Loyalty
0,238271
0,239061
0,072230
0,072230
3,298767
After-sales quality > Value for money
0,187820
0,187318
0,044108
0,044108
4,258204
Comfort -> Vehicle quality
0,747348
0,747459
0,033822
0,033822
22,096331
Costs of ownership > After-sales quality
0,483602
0,485781
0,044575
0,044575
10,849238
Expectations -> Sales quality
0,325988
0,332319
0,055971
0,055971
5,824281
Image -> Expectations
0,369774
0,374751
0,059031
0,059031
6,264093
Image -> Value for money
0,167117
0,171554
0,054613
0,054613
3,059988
Overall satisfaction > Loyalty
0,447200
0,444217
0,076290
0,076290
5,861885
Sales quality -> Loyalty
0,294576
0,299933
0,067905
0,067905
4,338093
Value for money -> Overall satisfaction
0,297836
0,298635
0,069204
0,069204
4,303737
Vehicle Design -> Image
0,224727
0,222102
0,061789
0,061789
3,637015
Vehicle quality -> Image
0,603007
0,602738
0,051742
0,051742
11,654194
146
Vehicle quality -> Overall satisfaction
0,591712
0,589664
0,062870
0,062870
9,411712
Vehicle quality -> Value for money
0,585819
0,579589
0,060972
0,060972
9,607931
Total Effects (Mean, STDEV, T-Values)
Original Sample (O)
Sample Mean (M)
Standard Deviation (STDEV)
Standard Error (STERR)
T Statistics (|O/STERR|)
After-sales quality > Loyalty
0,263287
0,263663
0,068598
0,068598
3,838100
After-sales quality > Overall satisfaction
0,055940
0,055355
0,016876
0,016876
3,314835
After-sales quality > Value for money
0,187820
0,187318
0,044108
0,044108
4,258204
Comfort -> Expectations
0,166641
0,168877
0,031725
0,031725
5,252745
Comfort -> Image
0,450656
0,450739
0,045892
0,045892
9,819875
Comfort -> Loyalty
0,282105
0,281160
0,050080
0,050080
5,633063
Comfort -> Overall satisfaction
0,595041
0,593675
0,032774
0,032774
18,155782
Comfort -> Sales quality
0,054323
0,056662
0,016462
0,016462
3,299916
Comfort -> Value for money
0,513122
0,510928
0,037349
0,037349
13,738612
Comfort -> Vehicle quality
0,747348
0,747459
0,033822
0,033822
22,096331
Costs of ownership > After-sales quality
0,483602
0,485781
0,044575
0,044575
10,849238
Costs of ownership > Loyalty
0,127326
0,128075
0,035859
0,035859
3,550800
Costs of ownership > Overall satisfaction
0,027052
0,026942
0,008732
0,008732
3,098027
Costs of ownership > Value for money
0,090830
0,091187
0,023729
0,023729
3,827742
Expectations -> Loyalty
0,096028
0,099249
0,026947
0,026947
3,563543
Expectations -> Sales quality
0,325988
0,332319
0,055971
0,055971
5,824281
Image -> Expectations
0,369774
0,374751
0,059031
0,059031
6,264093
Image -> Loyalty
0,057767
0,060417
0,015713
0,015713
3,676356
147
Image -> Overall satisfaction
0,049773
0,051291
0,020562
0,020562
2,420635
Image -> Sales quality
0,120542
0,125779
0,033990
0,033990
3,546394
Image -> Value for money
0,167117
0,171554
0,054613
0,054613
3,059988
Overall satisfaction > Loyalty
0,447200
0,444217
0,076290
0,076290
5,861885
Sales quality -> Loyalty
0,294576
0,299933
0,067905
0,067905
4,338093
Value for money -> Loyalty
0,133192
0,133208
0,040312
0,040312
3,304033
Value for money -> Overall satisfaction
0,297836
0,298635
0,069204
0,069204
4,303737
Vehicle Design -> Expectations
0,083098
0,082224
0,023415
0,023415
3,548991
Vehicle Design -> Image
0,224727
0,222102
0,061789
0,061789
3,637015
Vehicle Design -> Loyalty
0,012982
0,013184
0,004496
0,004496
2,887577
Vehicle Design -> Overall satisfaction
0,011185
0,011109
0,004972
0,004972
2,249745
Vehicle Design -> Sales quality
0,027089
0,027531
0,009785
0,009785
2,768330
Vehicle Design -> Value for money
0,037556
0,037089
0,013870
0,013870
2,707606
Vehicle quality -> Expectations
0,222977
0,225960
0,041241
0,041241
5,406681
Vehicle quality -> Image
0,603007
0,602738
0,051742
0,051742
11,654194
Vehicle quality -> Loyalty
0,377475
0,376180
0,064792
0,064792
5,825977
Vehicle quality -> Overall satisfaction
0,796203
0,794373
0,028609
0,028609
27,830996
Vehicle quality -> Sales quality
0,072688
0,075799
0,021703
0,021703
3,349242
Vehicle quality -> Value for money
0,686592
0,683642
0,040862
0,040862
16,802540
148
Appendix 3. Results of PLS algorithm application on the final structure of the Brand Satisfaction Model – Total Brand (Path Weighting Scheme, Mean replacement algorithm for missing values, Mean 0 and Var 1 data metric, Abort Criterion 1.0E-5, Initial Weights 1.0) Quality Criteria
Overview AVE
Composite Reliability
R Square
Cronbachs Alpha
After-sales quality
0,743979
0,958390
0,233871
0,949202
0,743979
Comfort
0,482429
0,892422
0,864926
0,482429
Costs of ownership
0,610747
0,902457
0,870282
0,610747
Expectations
0,690098
0,869728
0,136733
0,776171
0,690098
0,094039
Image
0,495642
0,897251
0,570014
0,872570
0,495642
0,102415
Loyalty
0,677321
0,893289
0,595556
0,840668
0,677320
0,148198
Overall satisfaction
0,921945
0,972553
0,721920
0,957658
0,921945
0,342770
Sales quality
0,596738
0,941729
0,106268
0,931259
0,596738
0,064057
Value for money
0,975887
0,987796
0,690302
0,975291
0,975887
0,171579
Vehicle Design
0,808352
0,954709
0,940627
0,808352
Vehicle quality
0,544042
0,904136
0,878112
0,544042
0,558528
Communality Redundancy 0,172559
0,306066
Cross Loadings Afte rsale Com s fort qual ity
Costs Expec of tation owne s rship
Imag e
comfort
0,41 0,77 518 0665 3
0,404 223
0,328 513
comfort %a
0,35 0,79 404 3244 7
0,430 350
comfort %b
0,33 0,71 293 4081 6
comfort 0,27 0,73 %c 680 4312
Loyal ty
Overa ll Sales satisf qualit actio y n
Value Vehicle for Design money
0,657 844
0,598 381
0,626 970
0,377 897
0,6422 43
0,5221 35
0,728104
0,322 557
0,622 905
0,434 095
0,518 745
0,415 753
0,5663 67
0,5214 15
0,631213
0,333 370
0,376 840
0,507 730
0,306 953
0,356 747
0,473 658
0,4280 11
0,4923 00
0,496822
0,295 233
0,345 748
0,476 674
0,347 658
0,374 541
0,467 008
0,4009 78
0,5675 81
0,507877
149
Vehicle quality
9 comfort %d
0,30 0,62 058 7962 0
0,279 222
0,257 976
0,314 571
0,277 699
0,330 457
0,351 621
0,3536 77
0,4554 56
0,454317
comfort %e
0,31 0,72 130 5196 7
0,414 829
0,245 186
0,499 085
0,330 134
0,350 544
0,311 385
0,4063 73
0,4392 08
0,475461
comfort %f
0,25 0,68 119 7559 5
0,398 984
0,227 010
0,454 725
0,327 627
0,343 565
0,303 355
0,3609 40
0,4386 60
0,460855
comfort %g
0,27 0,58 927 2573 4
0,357 147
0,228 855
0,431 754
0,288 484
0,322 177
0,325 045
0,3306 19
0,3146 90
0,371115
comfort %h
0,32 0,58 927 0688 9
0,295 748
0,251 586
0,451 390
0,335 876
0,333 032
0,343 880
0,3767 34
0,3947 46
0,411571
costs
0,34 0,52 056 4954 6
0,737 651
0,207 349
0,478 685
0,374 383
0,437 970
0,345 899
0,4629 75
0,4168 96
0,492386
costs% a
0,26 0,45 469 2463 9
0,656 791
0,231 846
0,411 347
0,318 954
0,393 485
0,335 405
0,3946 96
0,3919 63
0,433479
costs% b
0,27 0,37 572 6959 4
0,636 457
0,176 097
0,343 324
0,248 807
0,279 896
0,240 078
0,3923 83
0,2325 66
0,340275
costs% c
0,49 0,45 157 6671 4
0,867 725
0,188 785
0,428 528
0,397 181
0,424 120
0,284 023
0,4744 82
0,3047 13
0,450861
costs% d
0,43 0,34 300 8362 0
0,877 533
0,160 271
0,324 645
0,370 097
0,377 997
0,271 003
0,3926 83
0,2275 27
0,373318
costs% e
0,39 0,31 462 4541 2
0,872 290
0,131 860
0,282 688
0,331 793
0,290 175
0,242 410
0,3367 33
0,2060 15
0,288161
design
0,22 0,60 923 0900 9
0,331 491
0,363 685
0,528 830
0,343 476
0,406 151
0,455 968
0,4107 13
0,9195 60
0,546477
design %a
0,19 0,57 872 1377 2
0,292 561
0,405 965
0,457 387
0,296 767
0,299 219
0,411 820
0,3468 32
0,8991 03
0,456093
design %b
0,29 0,61 149 3764 1
0,306 746
0,340 915
0,517 063
0,390 298
0,414 257
0,443 990
0,4245 85
0,8817 53
0,569434
design %c
0,23 0,62 451 0817 6
0,335 826
0,371 381
0,535 218
0,379 453
0,354 769
0,399 881
0,3900 44
0,9215 50
0,519393
design %d
0,26 0,60 288 1991 2
0,369 807
0,335 811
0,523 198
0,371 789
0,362 871
0,363 611
0,3539 26
0,8723 76
0,486892
150
image
0,39 0,48 755 7995 0
0,386 380
0,218 654
0,701 045
0,562 129
0,780 180
0,291 337
0,6336 81
0,2930 73
0,683729
image %a
0,28 0,59 387 2018 2
0,326 940
0,301 642
0,704 244
0,393 883
0,441 665
0,328 708
0,4871 33
0,4828 71
0,557372
image %b
0,35 0,55 377 6210 6
0,305 367
0,303 942
0,731 372
0,424 540
0,491 362
0,333 849
0,5158 19
0,4419 12
0,556405
image %c
0,33 0,60 725 0184 1
0,338 403
0,302 684
0,798 033
0,418 049
0,474 734
0,349 939
0,5257 82
0,4996 44
0,557637
image %d
0,42 0,56 835 7990 0
0,392 895
0,298 147
0,801 905
0,540 814
0,523 949
0,347 597
0,5455 08
0,4577 48
0,591331
image %e
0,21 0,35 328 3444 6
0,288 737
0,162 197
0,571 081
0,310 326
0,300 137
0,287 903
0,3013 89
0,2847 67
0,313185
image %f
0,26 0,36 468 3756 7
0,323 750
0,226 507
0,589 476
0,251 352
0,256 501
0,335 371
0,2966 40
0,3147 30
0,273876
image %g
0,27 0,44 957 8949 3
0,272 204
0,230 241
0,641 581
0,264 844
0,355 340
0,350 556
0,3483 69
0,3657 22
0,363895
image %h
0,33 0,51 343 8644 3
0,358 198
0,269 058
0,757 166
0,488 783
0,484 440
0,426 619
0,5247 12
0,4420 51
0,553281
loyalty1
0,48 0,54 340 2229 5
0,422 210
0,165 258
0,654 117
0,858 884
0,730 237
0,350 103
0,7088 25
0,4195 05
0,717310
loyalty2
0,49 0,39 124 3705 8
0,360 559
0,150 659
0,388 519
0,849 768
0,409 149
0,601 351
0,4471 47
0,2846 13
0,443346
loyalty3
0,46 0,48 243 9677 3
0,399 238
0,162 518
0,597 794
0,832 810
0,668 537
0,302 142
0,6436 57
0,3532 62
0,640383
loyalty4
0,46 0,32 802 3256 3
0,241 284
0,160 352
0,284 187
0,745 602
0,320 568
0,599 213
0,2996 79
0,2330 10
0,339920
oczek% d
0,20 0,38 893 7432 9
0,169 969
0,819 162
0,317 313
0,223 781
0,281 840
0,273 308
0,2789 32
0,3446 53
0,275686
oczek% f
0,12 0,29 499 2288 0
0,175 901
0,812 377
0,288 441
0,112 014
0,170 220
0,214 761
0,2456 70
0,2482 57
0,207826
oczek% g
0,13 0,35 856 3935 3
0,213 511
0,859 832
0,314 003
0,142 032
0,203 527
0,314 813
0,2090 67
0,3973 06
0,229824
0,36
0,252
0,246
0,397
0,528
0,316
0,822
0,3822
0,3493
0,350412
sales
0,45
151
526 4
5753
875
057
370
009
121
780
28
66
sales% a
0,32 0,42 784 3849 2
0,298 947
0,287 025
0,336 650
0,419 545
0,248 279
0,811 570
0,2955 02
0,3626 91
0,291633
sales% b
0,32 0,38 839 1770 3
0,208 227
0,296 067
0,315 855
0,357 203
0,225 193
0,821 681
0,2884 70
0,3517 13
0,277101
sales% c
0,30 0,39 504 9836 6
0,286 708
0,263 665
0,321 495
0,392 029
0,252 964
0,815 307
0,2904 97
0,3850 53
0,292211
sales% d
0,27 0,38 027 9058 3
0,294 132
0,261 081
0,319 880
0,411 527
0,206 702
0,816 170
0,2367 89
0,4508 88
0,277261
sales% e
0,27 0,40 622 6462 9
0,271 066
0,308 866
0,329 426
0,383 189
0,199 607
0,829 765
0,2654 71
0,3792 45
0,281593
sales%f
0,30 0,40 826 3858 0
0,212 616
0,270 649
0,346 995
0,417 746
0,205 749
0,808 609
0,2730 74
0,3770 13
0,296421
sales% g
0,40 0,47 436 2152 1
0,332 306
0,249 525
0,450 652
0,427 141
0,283 768
0,695 434
0,3528 68
0,3441 20
0,397562
sales% h
0,37 0,39 720 4668 0
0,312 984
0,201 336
0,420 483
0,450 126
0,303 961
0,694 660
0,3146 24
0,3088 30
0,325406
sales%i
0,36 0,45 587 4564 1
0,324 306
0,197 376
0,421 795
0,395 518
0,316 973
0,702 338
0,3562 75
0,3495 71
0,400534
sales%j
0,33 0,37 059 9938 9
0,238 499
0,180 078
0,376 948
0,460 754
0,339 650
0,648 593
0,3238 25
0,2576 65
0,371654
sat1
0,41 0,55 786 6977 7
0,430 503
0,227 884
0,654 572
0,635 319
0,958 058
0,337 111
0,7367 71
0,3978 83
0,801064
sat1a
0,49 0,57 157 0757 2
0,468 881
0,264 398
0,639 015
0,634 799
0,955 991
0,315 372
0,7371 37
0,4015 69
0,777754
sat1b
0,45 0,57 739 1887 2
0,445 007
0,271 523
0,654 514
0,634 422
0,966 457
0,334 284
0,7528 72
0,3834 40
0,814336
service
0,91 0,39 085 7577 0
0,432 903
0,159 438
0,418 893
0,534 221
0,448 605
0,361 303
0,5428 32
0,2263 92
0,459934
service %a
0,91 0,37 114 6071 5
0,430 566
0,126 537
0,421 646
0,540 981
0,429 138
0,376 452
0,5349 53
0,1971 69
0,449369
service %b
0,93 0,39 124 9419
0,415 085
0,163 067
0,425 608
0,551 151
0,446 226
0,371 266
0,5297 04
0,2359 09
0,457422
152
0 service %c
0,88 0,35 438 9159 2
0,362 684
0,226 747
0,373 055
0,499 078
0,336 338
0,391 197
0,4275 78
0,2081 34
0,362109
service %d
0,66 0,33 484 8446 9
0,371 706
0,140 057
0,347 030
0,413 316
0,276 660
0,337 838
0,3394 94
0,2177 35
0,309927
service %e
0,79 0,44 644 1042 9
0,433 435
0,180 463
0,423 007
0,448 083
0,447 569
0,372 279
0,4928 49
0,3119 35
0,485847
service %f
0,90 0,46 405 7676 2
0,495 106
0,161 749
0,432 259
0,494 987
0,452 318
0,394 942
0,5190 78
0,2643 89
0,498021
service %g
0,86 0,39 544 4507 5
0,384 298
0,166 703
0,363 543
0,489 400
0,405 165
0,380 300
0,4549 30
0,2165 42
0,439719
value1
0,56 0,64 326 0399 5
0,515 694
0,284 279
0,675 551
0,650 288
0,757 064
0,400 800
0,9878 03
0,4263 08
0,793564
value2
0,54 0,62 702 2089 7
0,506 996
0,294 617
0,675 118
0,637 679
0,770 308
0,389 200
0,9879 37
0,4223 85
0,793294
vehqual
0,46 0,59 276 2375 7
0,409 694
0,212 044
0,677 228
0,644 525
0,899 455
0,351 119
0,7592 66
0,4018 98
0,863618
vehqual %a
0,50 0,51 293 5642 9
0,459 355
0,201 739
0,581 245
0,589 465
0,813 009
0,255 949
0,7037 83
0,3258 62
0,812594
vehqual %b
0,26 0,45 150 1192 6
0,314 975
0,106 089
0,445 967
0,287 377
0,401 476
0,218 691
0,4305 03
0,3602 62
0,600098
vehqual %c
0,35 0,54 409 9219 9
0,327 104
0,225 812
0,470 070
0,393 356
0,466 195
0,378 855
0,4817 96
0,4524 00
0,659822
vehqual %d
0,38 0,60 404 6278 5
0,351 052
0,239 984
0,525 130
0,409 600
0,486 742
0,306 893
0,5038 18
0,5124 30
0,710773
vehqual %e
0,32 0,54 360 2878 8
0,314 562
0,191 736
0,536 490
0,497 961
0,622 123
0,289 875
0,6127 21
0,4180 84
0,769276
vehqual %f
0,37 0,60 220 5111 8
0,371 688
0,247 211
0,519 143
0,537 681
0,588 587
0,359 426
0,6430 92
0,4497 20
0,767180
vehqual %g
0,27 0,56 306 8867 4
0,382 380
0,274 130
0,533 741
0,464 865
0,473 031
0,329 764
0,5216 26
0,5364 10
0,682027
153
Total Effects After sales quali ty
Comf ort
Costs Expe of ctatio Image owne ns rship
Aftersales quality 0,166 641
Comfort Costs of ownersh ip
0,4506 56
0,483 602
Expectat ions
Loyalt y
Over all Sales Value satisf qualit for actio y money n
0,2632 87
0,055 940
0,18782 0
0,2821 05
0,595 041
0,054 0,51312 323 2
0,1273 26
0,027 052
0,09083 0
0,0960 28 0,369 774
Image
0,0577 67
Vehicle Design
Vehicle quality
0,74734 8
0,325 988 0,049 773
0,120 0,16711 542 7
Loyalty Overall satisfact ion
0,4472 00
Sales quality
0,2945 76
Value for money
0,1331 92
0,297 836
Vehicle Design
0,083 098
0,2247 27
0,0129 82
0,011 185
0,027 0,03755 089 6
Vehicle quality
0,222 977
0,6030 07
0,3774 75
0,796 203
0,072 0,68659 688 2
Calculation Results Outer Loadings After sales quali ty
Comfor t
comfort
0,77066 5
comfort %a
0,79324 4
comfort %b
0,71408 1
comfort %c
0,73431 2
Costs of owne rship
Expec tation s
Imag e
Loyalt y
154
Overa Sales ll qualit satisf y action
Value for mone y
Vehicle Design
Vehicle quality
comfort %d
0,62796 2
comfort %e
0,72519 6
comfort %f
0,68755 9
comfort %g
0,58257 3
comfort %h
0,58068 8
costs
0,737 651
costs% a
0,656 791
costs% b
0,636 457
costs% c
0,867 725
costs% d
0,877 533
costs% e
0,872 290
design
0,91956 0
design %a
0,89910 3
design %b
0,88175 3
design %c
0,92155 0
design %d
0,87237 6
image
0,701 045
image %a
0,704 244
image %b
0,731 372
image %c
0,798 033
image %d
0,801 905
image %e
0,571 081
image %f
0,589 476
155
image %g
0,641 581
image %h
0,757 166
loyalty1
0,858 884
loyalty2
0,849 768
loyalty3
0,832 810
loyalty4
0,745 602
oczek% d
0,819 162
oczek% f
0,812 377
oczek% g
0,859 832
sales
0,822 780
sales% a
0,811 570
sales% b
0,821 681
sales% c
0,815 307
sales% d
0,816 170
sales% e
0,829 765
sales% f
0,808 609
sales% g
0,695 434
sales% h
0,694 660
sales%i
0,702 338
sales% j
0,648 593
sat1
0,958 058
sat1a
0,955 991
sat1b
0,966 457
156
service
0,910 850
service 0,911 %a 145 service 0,931 %b 240 service 0,884 382 %c service 0,664 849 %d service 0,796 %e 449 service 0,904 %f 052 service 0,865 %g 445 value1
0,987 803
value2
0,987 937
vehqual
0,86361 8
vehqual %a
0,81259 4
vehqual %b
0,60009 8
vehqual %c
0,65982 2
vehqual %d
0,71077 3
vehqual %e
0,76927 6
vehqual %f
0,76718 0
vehqual %g
0,68202 7
157
Outer Weights
After Costs Comfo of Expectat sales rt owners ions quali hip ty comfort
0,2281 24
comfort %a
0,1977 67
comfort %b
0,1556 61
comfort %c
0,1591 24
comfort %d
0,1423 43
comfort %e
0,1489 68
comfort %f
0,1443 92
comfort %g
0,1162 75
comfort %h
0,1289 50
costs
0,1944 64
costs% a
0,1511 44
costs% b
0,1574 39
costs% c
0,2806 90
costs% d
0,2472 44
costs% e
0,2253 30
Imag e
Loyal ty
Value Vehic Vehic Overall Sales for le le satisfac qualit mone Desig qualit tion y y n y
design
0,229 616
design %a
0,198 596
design %b
0,224 507
design %c
0,232 390
design
0,227
158
%d
170
image
0,192 667
image %a
0,172 659
image %b
0,174 731
image %c
0,178 627
image %d
0,183 037
image %e
0,100 752
image %f
0,101 445
image %g
0,121 345
image %h
0,173 047
loyalty1
0,338 436
loyalty2
0,296 380
loyalty3
0,309 419
loyalty4
0,267 946
oczek% d
0,412285
oczek% f
0,352844
oczek% g
0,436863
sales
0,139 212
sales% a
0,121 809
sales% b
0,110 031
sales% c
0,113 265
sales% d
0,116 978
sales% e
0,116 967
sales%
0,119
159
f
434
sales% g
0,118 792
sales% h
0,117 647
sales%i
0,105 878
sales%j
0,117 243
sat1
0,34735 2
sat1a
0,34297 6
sat1b
0,35111 2
service
0,15 6899
service %a
0,15 6584
service %b
0,15 5714
service %c
0,13 4208
service %d
0,11 6158
service %e
0,14 2107
service %f
0,15 5768
service %g
0,13 8065
value1
0,504 755
value2
0,507 524
vehqual
0,217 690
vehqual %a
0,194 552
vehqual %b
0,127 356
vehqual %c
0,144 981
vehqual %d
0,156 144
vehqual
0,171
160
%e
400
vehqual %f
0,174 276
vehqual %g
0,154 366
Path coefficients
Aftersales Comf qualit ort y
Costs of owner ship
Expecta tions
Image
Aftersales quality
Loyal ty
Value Overall Sales for satisfac qualit mone tion y y
0,238 271
0,187 820 0,747 348
Comfort Costs of ownersh ip
0,483 602
Expectat ions Image
Vehi Vehicl cle e Desi qualit gn y
0,325 988 0,36977 4
0,167 117
Loyalty Overall satisfact ion
0,447 200
Sales quality
0,294 576
Value for money
0,29783 6
Vehicle Design
0,2247 27
Vehicle quality
0,6030 07
161
0,59171 2
0,585 819
Index values Index Values for Latent Variables LV Index Values After-sales quality
7,761776
Comfort
8,816234
Costs of ownership
7,148388
Expectations
9,386072
Image
8,388493
Loyalty
8,490361
Overall satisfaction
8,025636
Sales quality
8,973071
Value for money
7,715634
Vehicle Design
9,150832
Vehicle quality
8,710951
162
Appendix 4. Results of PLS algorithm application on the final structure of the Brand Satisfaction Model – Compact Vehicles (Path Weighting Scheme, Mean replacement algorithm for missing values, Mean 0 and Var 1 data metric, Abort Criterion 1.0E-5, Initial Weights 1.0) Quality Criteria Overview AVE
Composite Reliability R Square Cronbachs Alpha
After-sales quality
0,772868
0,964042
0,321751
0,955294
Comfort
0,615318
0,933864
0,918409
Costs of ownership 0,594624
0,896510
0,860870
Expectations
0,669758
0,858374
0,112756
0,752665
Image
0,530648
0,909568
0,710467
0,888146
Loyalty
0,710878
0,907125
0,526028
0,866536
Overall satisfaction 0,914288
0,969696
0,679328
0,953114
Sales quality
0,603427
0,943242
0,219643
0,933588
Value for money
0,975473
0,987584
0,655323
0,974863
Vehicle Design
0,838080
0,962769
Vehicle quality
0,610209
0,925904
0,951549 0,661250
0,908580
Communality Redundancy After-sales quality
0,772868
0,246238
Comfort
0,615318
Costs of ownership
0,594624
Expectations
0,669758
0,076245
Image
0,530648
0,106508
Loyalty
0,710877
0,177967
Overall satisfaction
0,914288
0,420520
Sales quality
0,603427
0,127688
Value for money
0,975473
0,169007
Vehicle Design
0,838080
Vehicle quality
0,610209
0,408075
Cross Loadings After-sales quality Comfort Costs of ownership Expectations comfort
0,368551
0,908322
0,499223
0,311158
comfort%a
0,327109
0,893459
0,499673
0,257111
comfort%b
0,361751
0,803184
0,460079
0,372541
163
comfort%c
0,302326
0,840362
0,394585
0,317704
comfort%d
0,361084
0,763051
0,354829
0,227643
comfort%e
0,199894
0,749876
0,390077
0,111858
comfort%f
0,186670
0,736981
0,451857
0,160103
comfort%g
0,363920
0,780359
0,514510
0,320726
comfort%h
0,489744
0,516300
0,317839
0,296705
costs
0,323558
0,604837
0,676427
0,161764
costs%a
0,405242
0,577586
0,702207
0,242610
costs%b
0,314904
0,393787
0,633019
0,161419
costs%c
0,578369
0,534594
0,866037
0,216390
costs%d
0,497287
0,255268
0,856442
0,156119
costs%e
0,425561
0,264512
0,856077
0,145133
design
0,287264
0,664686
0,428636
0,250960
design%a
0,300855
0,669477
0,434323
0,337540
design%b
0,411170
0,729221
0,456849
0,335446
design%c
0,305569
0,703783
0,440488
0,314366
design%d
0,285438
0,599688
0,410695
0,229690
image
0,398424
0,526238
0,205550
0,283699
image%a
0,359292
0,743258
0,435439
0,250016
image%b
0,460009
0,537668
0,341913
0,258252
image%c
0,280902
0,666360
0,312323
0,248947
image%d
0,414474
0,582726
0,439095
0,234541
image%e
0,219540
0,380064
0,393251
0,178537
image%f
0,388467
0,459375
0,465197
0,253475
image%g
0,223394
0,425230
0,294965
0,147012
image%h
0,358957
0,540787
0,333553
0,310490
loyalty1
0,458454
0,479358
0,345089
0,128059
loyalty2
0,506714
0,301610
0,311258
0,233225
loyalty3
0,536437
0,508535
0,389942
0,238747
loyalty4
0,519625
0,249811
0,284650
0,237279
oczek%d
0,275680
0,299216
0,202976
0,750044
oczek%f
0,127218
0,287645
0,121946
0,827469
oczek%g
0,257396
0,252971
0,243957
0,872927
sales
0,404769
0,442999
0,237130
0,350181
sales%a
0,381844
0,436183
0,346435
0,352979
sales%b
0,293988
0,366277
0,270342
0,351298
sales%c
0,188020
0,345695
0,203641
0,293284
sales%d
0,301803
0,314968
0,261372
0,329294
164
sales%e
0,299072
0,380650
0,269954
0,425858
sales%f
0,374332
0,489102
0,354409
0,375734
sales%g
0,444635
0,504594
0,404195
0,473086
sales%h
0,417590
0,383684
0,399467
0,375602
sales%i
0,398822
0,492094
0,310554
0,298625
sales%j
0,336892
0,336203
0,233454
0,306225
sat1
0,504947
0,564225
0,374221
0,292436
sat1a
0,535152
0,555470
0,471571
0,271302
sat1b
0,538631
0,603846
0,417269
0,262348
service
0,924823
0,369664
0,545683
0,237857
service%a
0,939795
0,322607
0,544257
0,171778
service%b
0,955505
0,380540
0,537828
0,240033
service%c
0,942639
0,345214
0,522347
0,272474
service%d
0,614823
0,323734
0,437543
0,276801
service%e
0,804694
0,411014
0,400930
0,209357
service%f
0,931314
0,435218
0,576036
0,203998
service%g
0,866021
0,315132
0,391975
0,290829
value1
0,526192
0,693837
0,444741
0,393231
value2
0,556832
0,662393
0,439332
0,412993
vehqual
0,491381
0,605398
0,433815
0,244930
vehqual%a
0,516622
0,528989
0,436933
0,261298
vehqual%b
0,290631
0,593782
0,451570
0,220136
vehqual%c
0,420471
0,661912
0,439413
0,203009
vehqual%d
0,364674
0,755923
0,457825
0,264613
vehqual%e
0,263166
0,630274
0,336632
0,184753
vehqual%f
0,417013
0,685958
0,330493
0,323697
vehqual%g
0,341722
0,654619
0,376165
0,339362
Image comfort
Loyalty
Overall satisfaction Sales quality
0,754672 0,549088
0,647363
0,438249
comfort%a 0,730202 0,493370
0,622558
0,406887
comfort%b 0,583248 0,328100
0,450903
0,467230
comfort%c 0,594069 0,392949
0,478213
0,561639
comfort%d 0,455845 0,391088
0,409851
0,487933
comfort%e 0,507905 0,290753
0,349771
0,378407
comfort%f 0,549891 0,249086
0,358570
0,245879
comfort%g 0,575915 0,286322
0,401313
0,444689
comfort%h 0,469960 0,290676
0,436499
0,337467
165
costs
0,480153 0,320673
0,490458
0,308860
costs%a
0,561985 0,384154
0,576437
0,390137
costs%b
0,279476 0,085663
0,217221
0,267759
costs%c
0,495916 0,451528
0,395165
0,373683
costs%d
0,233201 0,297785
0,234874
0,278985
costs%e
0,197189 0,233616
0,164818
0,211063
design
0,636785 0,331077
0,458280
0,471075
design%a
0,631628 0,342133
0,428524
0,403599
design%b
0,695114 0,516884
0,560308
0,480789
design%c
0,644403 0,373852
0,415969
0,372850
design%d
0,555452 0,388670
0,377373
0,332598
image
0,775949 0,568405
0,828879
0,296067
image%a
0,775879 0,485195
0,559352
0,387512
image%b
0,799332 0,460316
0,718094
0,269166
image%c
0,777067 0,275709
0,548401
0,182650
image%d
0,804154 0,503103
0,629020
0,201691
image%e
0,611620 0,337185
0,434025
0,229895
image%f
0,636556 0,228182
0,418841
0,272683
image%g
0,604099 0,120880
0,390861
0,238497
image%h
0,733552 0,467777
0,591210
0,450810
loyalty1
0,639892 0,880996
0,753689
0,249019
loyalty2
0,233753 0,825759
0,304632
0,529759
loyalty3
0,643355 0,920330
0,744416
0,348400
loyalty4
0,183991 0,733808
0,247049
0,518657
oczek%d
0,321902 0,270106
0,326801
0,276801
oczek%f
0,250976 0,151076
0,197608
0,384053
oczek%g
0,262132 0,182082
0,200995
0,469960
sales
0,347974 0,427017
0,304894
0,753118
sales%a
0,312176 0,326912
0,255750
0,796759
sales%b
0,186679 0,239523
0,213803
0,803543
sales%c
0,088585 0,156231
0,123442
0,761355
sales%d
0,174630 0,336700
0,152535
0,781378
sales%e
0,206593 0,203987
0,167502
0,848090
sales%f
0,279980 0,381372
0,260731
0,899755
sales%g
0,392661 0,442698
0,381117
0,772912
sales%h
0,391562 0,340626
0,370779
0,643172
sales%i
0,445318 0,364946
0,440641
0,760951
sales%j
0,349042 0,504882
0,430442
0,693442
166
sat1
0,797655 0,615742
0,954712
0,383589
sat1a
0,745893 0,613281
0,949013
0,336583
sat1b
0,754752 0,650965
0,964760
0,370669
service
0,486682 0,547504
0,579499
0,404216
service%a
0,402038 0,523575
0,462961
0,415584
service%b
0,453194 0,562715
0,484813
0,438358
service%c
0,382281 0,560829
0,463280
0,416586
service%d 0,308607 0,455986
0,295031
0,341641
service%e
0,493007 0,540754
0,553773
0,417783
service%f
0,486378 0,498535
0,532701
0,403423
service%g
0,350801 0,448881
0,456908
0,423829
value1
0,742745 0,549651
0,737279
0,503510
value2
0,735974 0,525044
0,778980
0,476037
vehqual
0,794575 0,607016
0,880075
0,361486
vehqual%a 0,694599 0,580618
0,795334
0,370588
vehqual%b 0,647227 0,409009
0,591498
0,328690
vehqual%c 0,552084 0,422845
0,402185
0,417867
vehqual%d 0,656758 0,462371
0,489199
0,388314
vehqual%e 0,616650 0,401348
0,602246
0,319883
vehqual%f 0,557686 0,502996
0,444612
0,488590
vehqual%g 0,657414 0,438577
0,572402
0,463896
Value for money Vehicle Design Vehicle quality comfort
0,712730
0,687441
0,794166
comfort%a
0,698607
0,645204
0,805647
comfort%b
0,601338
0,588098
0,637560
comfort%c
0,558592
0,666439
0,666711
comfort%d
0,528462
0,573384
0,592607
comfort%e
0,380165
0,554615
0,553722
comfort%f
0,402825
0,503301
0,538826
comfort%g
0,464557
0,565825
0,587421
comfort%h
0,374374
0,366866
0,465039
costs
0,454806
0,495524
0,582239
costs%a
0,504564
0,548883
0,647319
costs%b
0,330916
0,303975
0,304578
costs%c
0,415018
0,453915
0,503085
costs%d
0,234755
0,231700
0,254675
costs%e
0,187220
0,214586
0,181882
167
design
0,571507
0,900610
0,681746
design%a
0,578582
0,941631
0,649038
design%b
0,638644
0,904622
0,778274
design%c
0,519481
0,947728
0,672265
design%d
0,418929
0,880969
0,598435
image
0,700385
0,471843
0,726129
image%a
0,582580
0,717619
0,694918
image%b
0,627994
0,522354
0,717465
image%c
0,522483
0,545757
0,595983
image%d
0,548802
0,501566
0,638817
image%e
0,389807
0,374189
0,423211
image%f
0,452090
0,383334
0,485405
image%g
0,395712
0,417817
0,432659
image%h
0,586856
0,558723
0,646043
loyalty1
0,612411
0,462091
0,691900
loyalty2
0,306701
0,258431
0,348208
loyalty3
0,605995
0,453942
0,648796
loyalty4
0,185048
0,198109
0,280320
oczek%d
0,350518
0,244451
0,258087
oczek%f
0,337788
0,271976
0,283668
oczek%g
0,322329
0,276661
0,263122
sales
0,502144
0,364339
0,384655
sales%a
0,428005
0,424800
0,360741
sales%b
0,371157
0,342401
0,294043
sales%c
0,284391
0,265476
0,214434
sales%d
0,200163
0,349407
0,292422
sales%e
0,271003
0,404204
0,318533
sales%f
0,353524
0,413347
0,389772
sales%g
0,476481
0,379817
0,454920
sales%h
0,398824
0,257749
0,412825
sales%i
0,477194
0,356862
0,539603
sales%j
0,362766
0,271507
0,463181
sat1
0,764842
0,507511
0,780181
sat1a
0,718662
0,443496
0,713547
sat1b
0,718588
0,463178
0,747491
service
0,559483
0,291251
0,471896
service%a
0,478728
0,244507
0,396507
service%b
0,490427
0,291477
0,433071
168
service%c
0,454239
0,235901
0,399983
service%d
0,348076
0,288809
0,322507
service%e
0,538369
0,483845
0,565999
service%f
0,494196
0,357989
0,496701
service%g
0,467562
0,270357
0,418240
value1
0,987265
0,603624
0,755166
value2
0,988056
0,583587
0,763376
vehqual
0,731346
0,522453
0,829399
vehqual%a
0,683846
0,413127
0,774443
vehqual%b
0,556052
0,508740
0,755625
vehqual%c
0,503735
0,646114
0,730919
vehqual%d
0,536518
0,685336
0,806023
vehqual%e
0,574611
0,643254
0,816924
vehqual%f
0,585655
0,631184
0,726910
vehqual%g
0,590505
0,640185
0,802099
Total Effects After-sales quality Comfort Costs of ownership Expectations After-sales quality Comfort Costs of ownership
0,194786 0,567231
Expectations Image
0,335792
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design
0,055312
Vehicle quality
0,239539
Image After-sales quality
Loyalty
Overall satisfaction Sales quality
0,306112
0,078102
0,580080 0,277585
0,591317
Costs of ownership
0,173636
0,044302
Expectations
0,076069
Image
0,081926
Comfort
0,468661 0,126879
Loyalty Overall satisfaction
0,091289
0,444377
169
0,157373
Sales quality
0,162313
Value for money
0,181322
0,408035
Vehicle Design
0,164722 0,013495
0,020900
0,025923
Vehicle quality
0,713354 0,341360
0,727172
0,112262
Value for money Vehicle Design Vehicle quality After-sales quality
0,191411
Comfort
0,516269
Costs of ownership
0,108574
0,813173
Expectations Image
0,310951
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design
0,051221
Vehicle quality
0,634882
Outer Loadings After-sales quality Comfort Costs of ownership Expectations comfort
0,908322
comfort%a
0,893459
comfort%b
0,803184
comfort%c
0,840362
comfort%d
0,763051
comfort%e
0,749876
comfort%f
0,736981
comfort%g
0,780359
comfort%h
0,516300
costs
0,676427
costs%a
0,702207
costs%b
0,633019
costs%c
0,866037
costs%d
0,856442
costs%e
0,856077
design design%a
170
design%b design%c design%d image image%a image%b image%c image%d image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d
0,750044
oczek%f
0,827469
oczek%g
0,872927
sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service
0,924823
service%a
0,939795
service%b
0,955505
service%c
0,942639
service%d
0,614823
171
service%e
0,804694
service%f
0,931314
service%g
0,866021
value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Image
Loyalty
Overall satisfaction Sales quality
comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design design%a design%b design%c design%d image
0,775949
image%a
0,775879
image%b
0,799332
172
image%c
0,777067
image%d
0,804154
image%e
0,611620
image%f
0,636556
image%g
0,604099
image%h
0,733552
loyalty1
0,880996
loyalty2
0,825759
loyalty3
0,920330
loyalty4
0,733808
oczek%d oczek%f oczek%g sales
0,753118
sales%a
0,796759
sales%b
0,803543
sales%c
0,761355
sales%d
0,781378
sales%e
0,848090
sales%f
0,899755
sales%g
0,772912
sales%h
0,643172
sales%i
0,760951
sales%j
0,693442
sat1
0,954712
sat1a
0,949013
sat1b
0,964760
service service%a service%b service%c service%d service%e service%f service%g value1 value2 vehqual
173
vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Value for money Vehicle Design Vehicle quality comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design
0,900610
design%a
0,941631
design%b
0,904622
design%c
0,947728
design%d
0,880969
image image%a image%b image%c image%d image%e image%f image%g image%h
174
loyalty1 loyalty2 loyalty3 loyalty4 oczek%d oczek%f oczek%g sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service service%a service%b service%c service%d service%e service%f service%g value1
0,987265
value2
0,988056
vehqual
0,829399
vehqual%a
0,774443
vehqual%b
0,755625
vehqual%c
0,730919
vehqual%d
0,806023
vehqual%e
0,816924
vehqual%f
0,726910
175
vehqual%g
0,802099
Outer Weights After-sales quality Comfort Costs of ownership Expectations comfort
0,177406
comfort%a
0,179971
comfort%b
0,142422
comfort%c
0,148934
comfort%d
0,132380
comfort%e
0,123694
comfort%f
0,120367
comfort%g
0,131222
comfort%h
0,103884
costs
0,162277
costs%a
0,203244
costs%b
0,157936
costs%c
0,290074
costs%d
0,249408
costs%e
0,213435
design design%a design%b design%c design%d image image%a image%b image%c image%d image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d
0,357005
176
oczek%f
0,396709
oczek%g
0,462771
sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service
0,157215
service%a
0,147306
service%b
0,151640
service%c
0,146665
service%d
0,118517
service%e
0,140880
service%f
0,149264
service%g
0,124452
value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Image
Loyalty
Overall satisfaction Sales quality
comfort comfort%a
177
comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design design%a design%b design%c design%d image
0,185528
image%a
0,173121
image%b
0,176278
image%c
0,151102
image%d
0,156924
image%e
0,109200
image%f
0,127162
image%g
0,110384
image%h
0,167391
loyalty1
0,339297
loyalty2
0,243649
loyalty3
0,361820
loyalty4
0,227432
oczek%d oczek%f oczek%g sales
0,131173
sales%a
0,114939
sales%b
0,100061
sales%c
0,076234
178
sales%d
0,112523
sales%e
0,106877
sales%f
0,127922
sales%g
0,154808
sales%h
0,121097
sales%i
0,111994
sales%j
0,136657
sat1
0,355462
sat1a
0,338477
sat1b
0,351815
service service%a service%b service%c service%d service%e service%f service%g value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Value for money Vehicle Design Vehicle quality comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g
179
comfort%h costs costs%a costs%b costs%c costs%d costs%e design
0,219799
design%a
0,218019
design%b
0,239932
design%c
0,222428
design%d
0,191725
image image%a image%b image%c image%d image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d oczek%f oczek%g sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i
180
sales%j sat1 sat1a sat1b service service%a service%b service%c service%d service%e service%f service%g value1
0,498178
value2
0,514309
vehqual
0,193525
vehqual%a
0,173547
vehqual%b
0,153884
vehqual%c
0,136810
vehqual%d
0,157488
vehqual%e
0,156039
vehqual%f
0,146490
vehqual%g
0,159477
Index Values Results Index Values for Latent Variables LV Index Values After-sales quality
7,707890
Comfort
8,739694
Costs of ownership
7,066291
Expectations
9,291980
Image
8,389854
Loyalty
8,469529
Overall satisfaction
7,889300
Sales quality
8,960235
Value for money
7,690175
Vehicle Design
9,006335
Vehicle quality
8,632728
181
Appendix 5. Results of PLS algorithm application on the final structure of the Brand Satisfaction Model – Mid-size vehicles (Path Weighting Scheme, Mean replacement algorithm for missing values, Mean 0 and Var 1 data metric, Abort Criterion 1.0E-5, Initial Weights 1.0) PLS Quality Criteria Overview AVE
Composite Reliability R Square Cronbachs Alpha
After-sales quality
0,705925
0,949731
0,207406
0,937509
Comfort
0,477433
0,889969
0,859571
Costs of ownership 0,605441
0,899726
0,867366
Expectations
0,721923
0,886158
0,315686
0,808046
Image
0,435126
0,871934
0,434305
0,838482
Loyalty
0,597603
0,855461
0,629035
0,780341
Overall satisfaction 0,881843
0,957246
0,681052
0,932998
Sales quality
0,539511
0,927087
0,116399
0,912917
Value for money
0,963072
0,981189
0,639334
0,961658
Vehicle Design
0,748316
0,936884
Vehicle quality
0,433883
0,856771
0,915850 0,497074
Communality Redundancy After-sales quality
0,705925
0,143231
Comfort
0,477433
Costs of ownership
0,605441
Expectations
0,721923
0,227853
Image
0,435126
0,097289
Loyalty
0,597602
0,109489
Overall satisfaction
0,881843
0,157824
Sales quality
0,539511
0,062490
Value for money
0,963072
0,204720
Vehicle Design
0,748316
Vehicle quality
0,433883
0,213887
182
0,807901
Cross Loadings After-sales quality Comfort Costs of ownership Expectations comfort
0,308752
0,783414
0,412866
0,429905
comfort%a
0,392647
0,673697
0,492601
0,305820
comfort%b
0,325933
0,576920
0,253288
0,376092
comfort%c
0,324076
0,634751
0,258848
0,373511
comfort%d
0,368962
0,751996
0,428558
0,319650
comfort%e
0,365378
0,821899
0,544734
0,305516
comfort%f
0,217808
0,745449
0,403458
0,226113
comfort%g
0,201183
0,565853
0,306022
0,252304
comfort%h
0,135515
0,613711
0,254531
0,201124
costs
0,327053
0,508553
0,774391
0,226708
costs%a
0,288790
0,471841
0,660889
0,264715
costs%b
0,139414
0,340539
0,556635
0,140856
costs%c
0,429941
0,464214
0,827629
0,200236
costs%d
0,404361
0,443280
0,911505
0,195620
costs%e
0,421943
0,385126
0,877803
0,144413
design
0,258299
0,523393
0,363193
0,411304
design%a
0,126542
0,523524
0,289120
0,383848
design%b
0,323992
0,522699
0,407946
0,284960
design%c
0,235131
0,563868
0,267012
0,408389
design%d
0,265372
0,572632
0,348402
0,330201
image
0,394457
0,436110
0,370251
0,295115
image%a
0,045427
0,400365
0,290620
0,352588
image%b
0,182039
0,498763
0,359325
0,442809
image%c
0,197907
0,520551
0,322750
0,489439
image%d
0,457271
0,503274
0,375328
0,506104
image%e
0,118870
0,259327
0,161160
0,232050
image%f
0,128174
0,313669
0,189707
0,317089
image%g
0,212006
0,373238
0,247957
0,297562
image%h
0,143441
0,360514
0,406030
0,290159
loyalty1
0,449200
0,603369
0,480556
0,221409
loyalty2
0,476286
0,419578
0,295457
0,200192
loyalty3
0,318066
0,399337
0,475625
0,103996
loyalty4
0,364914
0,328934
0,209691
0,114329
oczek%d
0,136680
0,462026
0,196352
0,874321
oczek%f
0,069130
0,268173
0,224955
0,825496
oczek%g
0,031583
0,399661
0,206882
0,848461
183
sales
0,290037
0,456063
0,276385
0,238430
sales%a
0,206820
0,436130
0,329059
0,298692
sales%b
0,158164
0,325877
0,115696
0,267963
sales%c
0,288450
0,479698
0,407889
0,315613
sales%d
0,218621
0,554479
0,372548
0,333404
sales%e
0,162124
0,443950
0,286325
0,305336
sales%f
0,140842
0,287470
0,156298
0,204494
sales%g
0,275020
0,530494
0,280986
0,262864
sales%h
0,363254
0,401764
0,260901
0,140518
sales%i
0,310068
0,466105
0,345423
0,158220
sales%j
0,148726
0,390157
0,213028
0,179351
sat1
0,429349
0,502421
0,446556
0,201576
sat1a
0,415239
0,613185
0,475102
0,294473
sat1b
0,329843
0,546482
0,436096
0,378687
service
0,934754
0,388721
0,393166
0,091033
service%a
0,901923
0,366785
0,449997
0,099025
service%b
0,938874
0,386548
0,403345
0,089459
service%c
0,769283
0,278074
0,204724
0,114576
service%d
0,610486
0,300189
0,356267
0,021815
service%e
0,751032
0,388057
0,428134
0,071878
service%f
0,894927
0,425357
0,406080
0,095758
service%g
0,865595
0,336381
0,383524
0,026495
value1
0,555860
0,604494
0,565361
0,333318
value2
0,534136
0,570017
0,583718
0,346989
vehqual
0,411798
0,537057
0,361586
0,224805
vehqual%a
0,448304
0,461375
0,481538
0,191582
vehqual%b
0,144237
0,265801
0,206763
0,029286
vehqual%c
0,241615
0,333578
0,111133
0,245830
vehqual%d
0,379203
0,438931
0,361180
0,197741
vehqual%e
0,164634
0,586594
0,318908
0,324709
vehqual%f
0,326688
0,467251
0,527871
0,254507
vehqual%g
0,326000
0,566660
0,637906
0,308630
Image comfort
Loyalty
Overall satisfaction Sales quality
0,499146 0,450938
0,493559
0,408250
comfort%a 0,469256 0,383535
0,425850
0,416263
comfort%b 0,442506 0,305192
0,317228
0,444659
comfort%c 0,334085 0,275475
0,424768
0,357509
184
comfort%d 0,426097 0,524615
0,420760
0,488123
comfort%e 0,553928 0,447311
0,382615
0,385671
comfort%f 0,426195 0,479140
0,466926
0,439320
comfort%g 0,411985 0,354294
0,376957
0,338288
comfort%h 0,418178 0,367472
0,340569
0,426516
costs
0,465327 0,457412
0,447024
0,375072
costs%a
0,396150 0,476783
0,445455
0,332420
costs%b
0,251541 0,273421
0,299824
0,164197
costs%c
0,436205 0,372556
0,372110
0,325408
costs%d
0,354102 0,396203
0,397737
0,315469
costs%e
0,332908 0,358656
0,335459
0,284766
design
0,501816 0,369159
0,488219
0,472939
design%a
0,362796 0,348715
0,283510
0,463244
design%b
0,455043 0,405743
0,530696
0,422975
design%c
0,482972 0,437275
0,336702
0,505521
design%d
0,514930 0,405844
0,455662
0,386809
image
0,612705 0,580233
0,738605
0,311307
image%a
0,558133 0,243627
0,224097
0,343926
image%b
0,699180 0,454425
0,431886
0,456570
image%c
0,764794 0,344335
0,378394
0,456332
image%d
0,806129 0,450317
0,396707
0,513104
image%e
0,509472 0,125331
0,137816
0,067978
image%f
0,654318 0,169139
0,211457
0,320316
image%g
0,655640 0,272753
0,342951
0,413105
image%h
0,622939 0,251595
0,217031
0,294143
loyalty1
0,603379 0,830309
0,757562
0,487273
loyalty2
0,334404 0,770412
0,268209
0,601662
loyalty3
0,424506 0,785952
0,671154
0,370646
loyalty4
0,200314 0,699817
0,218398
0,486825
oczek%d
0,460332 0,186505
0,258695
0,350156
oczek%f
0,477104 0,173191
0,302937
0,159021
oczek%g
0,495491 0,181525
0,238027
0,339963
sales
0,471630 0,554155
0,370551
0,818970
sales%a
0,401170 0,537192
0,307661
0,782944
sales%b
0,355684 0,321913
0,223589
0,780680
sales%c
0,470640 0,598582
0,435024
0,821675
sales%d
0,504127 0,472071
0,283816
0,816178
sales%e
0,426730 0,429376
0,207567
0,792365
185
sales%f
0,229444 0,379938
0,119058
0,672968
sales%g
0,491701 0,355670
0,297747
0,638617
sales%h
0,405922 0,507686
0,376317
0,606046
sales%i
0,445724 0,428493
0,316544
0,701865
sales%j
0,274575 0,271176
0,258624
0,593031
sat1
0,506581 0,627164
0,936009
0,378612
sat1a
0,542748 0,619161
0,944008
0,373638
sat1b
0,557773 0,625754
0,937158
0,389331
service
0,337991 0,501633
0,390205
0,288323
service%a
0,340608 0,460621
0,401281
0,278644
service%b 0,362982 0,525353
0,408137
0,315646
service%c
0,237963 0,408676
0,163748
0,278043
service%d 0,296633 0,346311
0,213807
0,236343
service%e
0,250121 0,356742
0,389503
0,220560
service%f
0,290049 0,470631
0,424604
0,277936
service%g 0,199636 0,389397
0,330235
0,266995
value1
0,637283 0,644650
0,635171
0,370359
value2
0,629540 0,658703
0,674506
0,403114
vehqual
0,524711 0,563923
0,792004
0,432705
vehqual%a 0,443824 0,543471
0,668893
0,160704
vehqual%b 0,245626 0,220350
0,335432
0,094903
vehqual%c 0,369118 0,330209
0,448417
0,356268
vehqual%d 0,379023 0,414369
0,534652
0,275173
vehqual%e 0,347887 0,377637
0,408615
0,349617
vehqual%f 0,339184 0,425700
0,467986
0,289904
vehqual%g 0,518538 0,556644
0,532064
0,355763
Value for money Vehicle Design Vehicle quality comfort
0,475532
0,472732
0,560491
comfort%a
0,519348
0,382030
0,518859
comfort%b
0,336533
0,371001
0,400768
comfort%c
0,286365
0,431626
0,458778
comfort%d
0,444658
0,615776
0,553677
comfort%e
0,519851
0,485424
0,537796
comfort%f
0,411389
0,447878
0,508234
comfort%g
0,299135
0,255572
0,384356
comfort%h
0,373593
0,369247
0,417634
costs
0,449348
0,422911
0,499244
186
costs%a
0,457795
0,221919
0,458798
costs%b
0,414334
0,086670
0,298991
costs%c
0,536476
0,379086
0,512281
costs%d
0,488924
0,341875
0,506274
costs%e
0,429455
0,267497
0,457530
design
0,356722
0,908290
0,548997
design%a
0,260709
0,813503
0,385783
design%b
0,369991
0,889411
0,597482
design%c
0,291826
0,867795
0,424100
design%d
0,334324
0,843018
0,471438
image
0,668747
0,339963
0,693426
image%a
0,311555
0,318575
0,417938
image%b
0,519289
0,316762
0,480622
image%c
0,449668
0,493586
0,409509
image%d
0,484416
0,519980
0,432793
image%e
0,221357
0,201947
0,166161
image%f
0,242265
0,327241
0,188118
image%g
0,292835
0,321140
0,278872
image%h
0,369763
0,258330
0,286404
loyalty1
0,735828
0,521314
0,731981
loyalty2
0,352228
0,276390
0,327543
loyalty3
0,572570
0,359737
0,631823
loyalty4
0,283854
0,171784
0,279171
oczek%d
0,313367
0,356669
0,312039
oczek%f
0,375863
0,166838
0,297116
oczek%g
0,210968
0,512143
0,270074
sales
0,367428
0,305614
0,393529
sales%a
0,267069
0,350798
0,336866
sales%b
0,166184
0,324944
0,225457
sales%c
0,343287
0,549620
0,473235
sales%d
0,304071
0,647422
0,382309
sales%e
0,283773
0,355637
0,256205
sales%f
0,161354
0,262864
0,185119
sales%g
0,274446
0,311356
0,377426
sales%h
0,364066
0,351201
0,334936
sales%i
0,361275
0,356044
0,331316
sales%j
0,238279
0,258994
0,219035
sat1
0,605676
0,449900
0,769066
187
sat1a
0,652056
0,479701
0,761919
sat1b
0,622555
0,454056
0,775451
service
0,560380
0,248188
0,458067
service%a
0,564136
0,239262
0,467364
service%b
0,539122
0,262069
0,454964
service%c
0,356811
0,106547
0,238792
service%d
0,303684
0,201607
0,264684
service%e
0,437300
0,307401
0,389073
service%f
0,521502
0,262279
0,484615
service%g
0,360624
0,267513
0,406240
value1
0,981114
0,349506
0,720335
value2
0,981610
0,387951
0,709617
vehqual
0,568566
0,415946
0,784338
vehqual%a
0,591599
0,327433
0,759266
vehqual%b
0,299595
0,203319
0,471343
vehqual%c
0,371766
0,310619
0,541233
vehqual%d
0,491295
0,546857
0,708736
vehqual%e
0,378512
0,362391
0,596198
vehqual%f
0,503552
0,258179
0,629480
vehqual%g
0,552686
0,501805
0,714346
Total Effects After-sales quality Comfort Costs of ownership Expectations After-sales quality Comfort Costs of ownership
0,179940 0,455418
Expectations Image
0,561859
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design
0,160371
Vehicle quality
0,255221
Image After-sales quality
Loyalty 0,239531
Overall satisfaction Sales quality 0,037155
188
Comfort
0,320258 0,256940
0,559518
Costs of ownership
0,109087
0,016921
Expectations
0,129261
Image
0,091344
0,061391
0,341173 0,044817
0,191691
Loyalty Overall satisfaction
0,417647
Sales quality
0,378873
Value for money
0,063140
0,151180
Vehicle Design
0,285429 0,026072
0,012792
0,054714
Vehicle quality
0,454244 0,364436
0,793604
0,087075
Value for money Vehicle Design Vehicle quality After-sales quality
0,245768
Comfort
0,396431
Costs of ownership
0,111927
0,705034
Expectations Image
0,296450
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design
0,084615
Vehicle quality
0,562286
Outer Loadings After-sales quality Comfort Costs of ownership Expectations comfort
0,783414
comfort%a
0,673697
comfort%b
0,576920
comfort%c
0,634751
comfort%d
0,751996
comfort%e
0,821899
comfort%f
0,745449
comfort%g
0,565853
comfort%h
0,613711
costs
0,774391
costs%a
0,660889
costs%b
0,556635
189
costs%c
0,827629
costs%d
0,911505
costs%e
0,877803
design design%a design%b design%c design%d image image%a image%b image%c image%d image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d
0,874321
oczek%f
0,825496
oczek%g
0,848461
sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b
190
service
0,934754
service%a
0,901923
service%b
0,938874
service%c
0,769283
service%d
0,610486
service%e
0,751032
service%f
0,894927
service%g
0,865595
value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Image
Loyalty
Overall satisfaction Sales quality
comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design design%a design%b
191
design%c design%d image
0,612705
image%a
0,558133
image%b
0,699180
image%c
0,764794
image%d
0,806129
image%e
0,509472
image%f
0,654318
image%g
0,655640
image%h
0,622939
loyalty1
0,830309
loyalty2
0,770412
loyalty3
0,785952
loyalty4
0,699817
oczek%d oczek%f oczek%g sales
0,818970
sales%a
0,782944
sales%b
0,780680
sales%c
0,821675
sales%d
0,816178
sales%e
0,792365
sales%f
0,672968
sales%g
0,638617
sales%h
0,606046
sales%i
0,701865
sales%j
0,593031
sat1
0,936009
sat1a
0,944008
sat1b
0,937158
service service%a service%b service%c service%d service%e
192
service%f service%g value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Value for money Vehicle Design Vehicle quality comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design
0,908290
design%a
0,813503
design%b
0,889411
design%c
0,867795
design%d
0,843018
image image%a image%b image%c
193
image%d image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d oczek%f oczek%g sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service service%a service%b service%c service%d service%e service%f service%g value1
0,981114
value2
0,981610
vehqual
0,784338
vehqual%a
0,759266
194
vehqual%b
0,471343
vehqual%c
0,541233
vehqual%d
0,708736
vehqual%e
0,596198
vehqual%f
0,629480
vehqual%g
0,714346
Path Coefficients After-sales quality Comfort Costs of ownership Expectations After-sales quality Comfort Costs of ownership
0,455418
Expectations Image
0,561859
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design Vehicle quality
Image After-sales quality
Loyalty
Overall satisfaction Sales quality
0,224013
Comfort Costs of ownership Expectations
0,341173
Image Loyalty Overall satisfaction
0,417647
Sales quality
0,378873
Value for money
0,151180
Vehicle Design
0,285429
Vehicle quality
0,454244
0,708597
Value for money Vehicle Design Vehicle quality After-sales quality
0,245768
195
Comfort
0,705034
Costs of ownership Expectations Image
0,296450
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design Vehicle quality
0,427625
Outer Weights After-sales quality Comfort Costs of ownership Expectations comfort
0,185464
comfort%a
0,171688
comfort%b
0,132612
comfort%c
0,151808
comfort%d
0,183209
comfort%e
0,177954
comfort%f
0,168172
comfort%g
0,127182
comfort%h
0,138193
costs
0,202320
costs%a
0,178649
costs%b
0,086243
costs%c
0,265967
costs%d
0,250143
costs%e
0,261020
design design%a design%b design%c design%d image image%a image%b image%c image%d
196
image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d
0,406008
oczek%f
0,346104
oczek%g
0,423485
sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service
0,170441
service%a
0,171948
service%b
0,171614
service%c
0,114346
service%d
0,115953
service%e
0,141448
service%f
0,163219
service%g
0,131030
value1 value2 vehqual vehqual%a vehqual%b
197
vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Image
Loyalty
Overall satisfaction Sales quality
comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design design%a design%b design%c design%d image
0,231491
image%a
0,155932
image%b
0,204714
image%c
0,204584
image%d
0,216027
image%e
0,093189
image%f
0,117729
image%g
0,131753
image%h
0,138858
loyalty1
0,406386
loyalty2
0,301708
198
loyalty3
0,332320
loyalty4
0,241415
oczek%d oczek%f oczek%g sales
0,145619
sales%a
0,149058
sales%b
0,099722
sales%c
0,164081
sales%d
0,139278
sales%e
0,126925
sales%f
0,104634
sales%g
0,106300
sales%h
0,124301
sales%i
0,109543
sales%j
0,078584
sat1
0,354658
sat1a
0,353523
sat1b
0,356725
service service%a service%b service%c service%d service%e service%f service%g value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
199
Value for money Vehicle Design Vehicle quality comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design
0,249801
design%a
0,180597
design%b
0,226517
design%c
0,240420
design%d
0,256329
image image%a image%b image%c image%d image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d oczek%f oczek%g sales
200
sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service service%a service%b service%c service%d service%e service%f service%g value1
0,506136
value2
0,512854
vehqual
0,245772
vehqual%a
0,219700
vehqual%b
0,115829
vehqual%c
0,153286
vehqual%d
0,186449
vehqual%e
0,172461
vehqual%f
0,179454
vehqual%g
0,216891
201
Index Values Results Index Values for Latent Variables LV Index Values After-sales quality
8,053256
Comfort
8,736349
Costs of ownership
7,043332
Expectations
9,275809
Image
8,467164
Loyalty
8,736364
Overall satisfaction
8,274511
Sales quality
9,021823
Value for money
7,960828
Vehicle Design
9,138596
Vehicle quality
8,890804
202
Appendix 6. Results of PLS algorithm application on the final structure of the Brand Satisfaction Model – Full-size and large vehicles (Path Weighting Scheme, Mean replacement algorithm for missing values, Mean 0 and Var 1 data metric, Abort Criterion 1.0E-5, Initial Weights 1.0) PLS Quality Criteria Overview AVE
Composite Reliability R Square Cronbachs Alpha
After-sales quality
0,756338
0,961199
0,220759
0,953577
Comfort
0,417075
0,862975
0,825457
Costs of ownership 0,631850
0,910180
0,882212
Expectations
0,688444
0,868744
0,101650
0,772819
Image
0,515331
0,903972
0,540174
0,881729
Loyalty
0,683263
0,895821
0,668624
0,844064
Overall satisfaction 0,939084
0,978835
0,772297
0,967552
Sales quality
0,631180
0,948994
0,069712
0,939794
Value for money
0,980902
0,990359
0,752208
0,980530
Vehicle Design
0,821036
0,958165
Vehicle quality
0,556229
0,906952
0,945447 0,575419
Communality Redundancy After-sales quality
0,756338
0,165511
Comfort
0,417075
Costs of ownership
0,631850
Expectations
0,688444
0,069946
Image
0,515331
0,094646
Loyalty
0,683262
0,132700
Overall satisfaction
0,939084
0,336551
Sales quality
0,631180
0,044446
Value for money
0,980902
0,159029
Vehicle Design
0,821036
Vehicle quality
0,556229
0,321525
203
0,880875
Cross Loadings After-sales quality Comfort Costs of ownership Expectations comfort
0,486584
0,701444
0,358895
0,302654
comfort%a
0,379716
0,785724
0,348787
0,353190
comfort%b
0,338939
0,714064
0,297551
0,358419
comfort%c
0,236001
0,682580
0,256100
0,385769
comfort%d
0,247213
0,451548
0,142889
0,218285
comfort%e
0,382478
0,659463
0,353861
0,333402
comfort%f
0,366883
0,606493
0,355257
0,245082
comfort%g
0,284473
0,527113
0,322851
0,206239
comfort%h
0,274856
0,619692
0,307845
0,255494
costs
0,386846
0,456552
0,776274
0,233476
costs%a
0,165649
0,309901
0,637468
0,145489
costs%b
0,332093
0,386249
0,678024
0,197377
costs%c
0,469630
0,416694
0,893648
0,193685
costs%d
0,413690
0,377911
0,869240
0,125562
costs%e
0,367094
0,313662
0,876489
0,114905
design
0,172556
0,587421
0,245510
0,438682
design%a
0,145712
0,491685
0,188848
0,531135
design%b
0,174418
0,556224
0,115859
0,410043
design%c
0,180344
0,578444
0,303586
0,389941
design%d
0,261063
0,625606
0,359490
0,428830
image
0,399395
0,535569
0,508721
0,175029
image%a
0,336038
0,550161
0,286933
0,320668
image%b
0,351798
0,621586
0,252952
0,203443
image%c
0,440366
0,603556
0,382295
0,235845
image%d
0,418318
0,641452
0,401432
0,291397
image%e
0,254347
0,425490
0,328220
0,135004
image%f
0,270540
0,356726
0,349798
0,143900
image%g
0,376664
0,533043
0,279515
0,289664
image%h
0,403120
0,599637
0,366024
0,229804
loyalty1
0,512689
0,612642
0,467497
0,195850
loyalty2
0,484392
0,495551
0,440663
0,086442
loyalty3
0,476453
0,562117
0,384430
0,174686
loyalty4
0,464469
0,405859
0,247259
0,150493
oczek%d
0,217163
0,411070
0,122880
0,790053
oczek%f
0,235346
0,323431
0,195756
0,826712
oczek%g
0,153565
0,410431
0,206856
0,870456
204
sales
0,370460
0,481707
0,265872
0,196862
sales%a
0,368645
0,430058
0,259101
0,233853
sales%b
0,429625
0,436230
0,227805
0,316616
sales%c
0,389417
0,429925
0,281320
0,242127
sales%d
0,283848
0,359523
0,277888
0,158366
sales%e
0,331734
0,418245
0,265890
0,229892
sales%f
0,358292
0,418498
0,159242
0,277565
sales%g
0,425825
0,444385
0,321235
0,136097
sales%h
0,362657
0,443438
0,309245
0,186311
sales%i
0,369058
0,451953
0,334545
0,197408
sales%j
0,403004
0,427782
0,268307
0,112262
sat1
0,356390
0,610812
0,468097
0,221811
sat1a
0,496962
0,581794
0,476182
0,255537
sat1b
0,446464
0,601986
0,487976
0,259751
service
0,891576
0,431957
0,402760
0,176200
service%a
0,894955
0,446260
0,378132
0,148404
service%b
0,912642
0,428400
0,362681
0,182187
service%c
0,900188
0,422797
0,352342
0,294909
service%d
0,784663
0,404870
0,370116
0,180126
service%e
0,812486
0,517402
0,475678
0,265185
service%f
0,885154
0,534140
0,510663
0,217410
service%g
0,867337
0,517744
0,410374
0,235519
value1
0,587218
0,660415
0,555849
0,220129
value2
0,543788
0,656576
0,530888
0,219318
vehqual
0,456868
0,667845
0,444476
0,245849
vehqual%a
0,511586
0,587148
0,484406
0,219857
vehqual%b
0,293151
0,425623
0,280357
0,067521
vehqual%c
0,365287
0,577256
0,374623
0,218713
vehqual%d
0,406049
0,577041
0,279144
0,257162
vehqual%e
0,402442
0,538878
0,339559
0,202613
vehqual%f
0,364311
0,626742
0,344546
0,217115
vehqual%g
0,210936
0,521364
0,276647
0,220795
Image comfort
Loyalty
Overall satisfaction Sales quality
0,662560 0,695889
0,655821
0,337419
comfort%a 0,665404 0,483882
0,543719
0,445745
comfort%b 0,508045 0,353709
0,346294
0,531378
comfort%c 0,470020 0,374716
0,291116
0,472384
205
comfort%d 0,198086 0,135793
0,276695
0,200980
comfort%e 0,471679 0,326035
0,362254
0,225314
comfort%f 0,425086 0,387703
0,319339
0,305911
comfort%g 0,383435 0,270345
0,281171
0,274535
comfort%h 0,462597 0,355790
0,260550
0,329058
costs
0,494821 0,430027
0,436368
0,383500
costs%a
0,329866 0,257025
0,285571
0,331358
costs%b
0,458229 0,355972
0,319883
0,264686
costs%c
0,378019 0,374106
0,461891
0,213744
costs%d
0,374292 0,401561
0,450663
0,251026
costs%e
0,315602 0,381746
0,347942
0,242843
design
0,469513 0,392449
0,357143
0,458396
design%a
0,349744 0,276832
0,220791
0,408554
design%b
0,435562 0,347048
0,272388
0,473404
design%c
0,495616 0,396902
0,344947
0,372807
design%d
0,526840 0,395221
0,338722
0,391876
image
0,703457 0,561065
0,774887
0,292171
image%a
0,707365 0,409327
0,459711
0,287959
image%b
0,713735 0,426688
0,367014
0,348544
image%c
0,824082 0,566679
0,469841
0,428460
image%d
0,800597 0,590742
0,503559
0,389015
image%e
0,583350 0,383945
0,296413
0,426618
image%f
0,553195 0,369520
0,218649
0,404790
image%g
0,696339 0,434967
0,362858
0,439194
image%h
0,825874 0,622906
0,529532
0,480704
loyalty1
0,693729 0,858880
0,708885
0,365961
loyalty2
0,525380 0,885788
0,514963
0,649274
loyalty3
0,648846 0,788246
0,631226
0,254410
loyalty4
0,417124 0,767739
0,405118
0,726514
oczek%d
0,254600 0,236988
0,285617
0,241158
oczek%f
0,264277 0,092023
0,116269
0,188079
oczek%g
0,274213 0,120435
0,221913
0,225251
sales
0,416742 0,610626
0,306903
0,876228
sales%a
0,341776 0,456658
0,227086
0,849399
sales%b
0,410572 0,463508
0,231161
0,855927
sales%c
0,414405 0,455673
0,249660
0,850556
sales%d
0,341424 0,458515
0,209312
0,845315
sales%e
0,387441 0,508878
0,228113
0,842762
206
sales%f
0,482676 0,473198
0,217528
0,823817
sales%g
0,483542 0,439269
0,219931
0,669414
sales%h
0,461684 0,503751
0,251426
0,776448
sales%i
0,408678 0,417268
0,256908
0,664272
sales%j
0,448981 0,521209
0,317422
0,633991
sat1
0,627899 0,667030
0,966102
0,308483
sat1a
0,615213 0,671882
0,964621
0,290163
sat1b
0,629980 0,642692
0,976425
0,309832
service
0,412514 0,540259
0,382202
0,378064
service%a
0,477303 0,572075
0,410383
0,402454
service%b
0,446144 0,554400
0,436812
0,365524
service%c
0,449371 0,487477
0,333232
0,443502
service%d
0,425084 0,480436
0,328529
0,418970
service%e
0,443966 0,423765
0,400220
0,408544
service%f
0,459418 0,489041
0,412027
0,445882
service%g
0,441900 0,520552
0,394840
0,403760
value1
0,659258 0,718975
0,806262
0,358275
value2
0,661473 0,704921
0,800878
0,335814
vehqual
0,661258 0,695790
0,938753
0,332606
vehqual%a 0,564415 0,614300
0,869479
0,239796
vehqual%b 0,359425 0,243625
0,299708
0,204830
vehqual%c 0,476505 0,424111
0,552200
0,373482
vehqual%d 0,509388 0,385121
0,477798
0,275832
vehqual%e 0,561994 0,591955
0,681101
0,269071
vehqual%f 0,569625 0,596753
0,711340
0,317015
vehqual%g 0,465631 0,456070
0,400253
0,246163
Value for money Vehicle Design Vehicle quality comfort
0,664926
0,444845
0,741440
comfort%a
0,551400
0,519356
0,624199
comfort%b
0,394224
0,482644
0,482133
comfort%c
0,359097
0,564153
0,424692
comfort%d
0,233716
0,260167
0,365169
comfort%e
0,390681
0,315698
0,431073
comfort%f
0,357687
0,333296
0,430835
comfort%g
0,295682
0,245100
0,289719
comfort%h
0,395963
0,433617
0,364341
costs
0,513348
0,330894
0,466261
207
costs%a
0,328155
0,342579
0,312130
costs%b
0,439696
0,263282
0,399437
costs%c
0,480751
0,162574
0,403281
costs%d
0,443364
0,167005
0,408087
costs%e
0,387377
0,169018
0,297152
design
0,340317
0,951949
0,465140
design%a
0,215935
0,901079
0,333651
design%b
0,316908
0,849767
0,411623
design%c
0,368710
0,933445
0,463358
design%d
0,345271
0,890844
0,436989
image
0,585685
0,184422
0,673724
image%a
0,510536
0,336713
0,512497
image%b
0,446873
0,428563
0,473477
image%c
0,562427
0,483582
0,585734
image%d
0,562297
0,451074
0,607668
image%e
0,292138
0,289659
0,314508
image%f
0,263021
0,296337
0,218211
image%g
0,361392
0,345050
0,374045
image%h
0,555650
0,466454
0,593347
loyalty1
0,749828
0,376810
0,730284
loyalty2
0,561475
0,346122
0,538444
loyalty3
0,690450
0,302772
0,640725
loyalty4
0,384183
0,310550
0,395111
oczek%d
0,231454
0,439052
0,301536
oczek%f
0,145876
0,337763
0,162649
oczek%g
0,171937
0,411157
0,227419
sales
0,313214
0,370407
0,315818
sales%a
0,234957
0,316560
0,241437
sales%b
0,281869
0,379559
0,278850
sales%c
0,273477
0,398764
0,277198
sales%d
0,231830
0,407975
0,236709
sales%e
0,266370
0,376516
0,288328
sales%f
0,283630
0,435985
0,292145
sales%g
0,302195
0,364573
0,361965
sales%h
0,247126
0,367063
0,284307
sales%i
0,287436
0,370262
0,355627
sales%j
0,333372
0,255317
0,372273
sat1
0,766175
0,322736
0,827692
208
sat1a
0,778694
0,353568
0,827803
sat1b
0,813528
0,327862
0,867137
service
0,523042
0,156771
0,439373
service%a
0,555610
0,142634
0,470256
service%b
0,553706
0,168962
0,474773
service%c
0,447946
0,254798
0,387653
service%d
0,388077
0,217009
0,358713
service%e
0,480422
0,173475
0,462421
service%f
0,528232
0,196900
0,498958
service%g
0,471426
0,170463
0,458337
value1
0,990470
0,360181
0,841739
value2
0,990339
0,347947
0,844406
vehqual
0,832742
0,355462
0,907941
vehqual%a
0,750984
0,304548
0,858737
vehqual%b
0,403120
0,298963
0,531512
vehqual%c
0,554009
0,330215
0,691101
vehqual%d
0,499262
0,324846
0,664484
vehqual%e
0,696997
0,344251
0,788866
vehqual%f
0,732261
0,429057
0,837131
vehqual%g
0,471919
0,494689
0,602734
Total Effects After-sales quality Comfort Costs of ownership Expectations After-sales quality Comfort Costs of ownership
0,144802 0,469850
Expectations Image
0,318826
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design
0,072960
Vehicle quality
0,190889
Image After-sales quality Comfort
Loyalty
Overall satisfaction Sales quality
0,220640
0,043816
0,454172 0,318870
0,639516
209
0,038232
Costs of ownership
0,103668
Expectations
0,097741
Image
0,041322
0,020587 0,264030 0,021322
0,084180
Loyalty Overall satisfaction
0,476481
Sales quality
0,370188
Value for money
0,125661
0,263727
Vehicle Design
0,228841 0,009456
0,004879
0,019264
Vehicle quality
0,598727 0,420360
0,843061
0,050401
Value for money Vehicle Design Vehicle quality After-sales quality
0,166142
Comfort
0,574451
Costs of ownership
0,078062
0,758564
Expectations Image
0,080849
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design
0,018501
Vehicle quality
0,757288
Outer Loadings After-sales quality Comfort Costs of ownership Expectations comfort
0,701444
comfort%a
0,785724
comfort%b
0,714064
comfort%c
0,682580
comfort%d
0,451548
comfort%e
0,659463
comfort%f
0,606493
comfort%g
0,527113
comfort%h
0,619692
costs
0,776274
costs%a
0,637468
costs%b
0,678024
costs%c
0,893648
210
costs%d
0,869240
costs%e
0,876489
design design%a design%b design%c design%d image image%a image%b image%c image%d image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d
0,790053
oczek%f
0,826712
oczek%g
0,870456
sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service
0,891576
211
service%a
0,894955
service%b
0,912642
service%c
0,900188
service%d
0,784663
service%e
0,812486
service%f
0,885154
service%g
0,867337
value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Image
Loyalty
Overall satisfaction Sales quality
comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design design%a design%b design%c
212
design%d image
0,703457
image%a
0,707365
image%b
0,713735
image%c
0,824082
image%d
0,800597
image%e
0,583350
image%f
0,553195
image%g
0,696339
image%h
0,825874
loyalty1
0,858880
loyalty2
0,885788
loyalty3
0,788246
loyalty4
0,767739
oczek%d oczek%f oczek%g sales
0,876228
sales%a
0,849399
sales%b
0,855927
sales%c
0,850556
sales%d
0,845315
sales%e
0,842762
sales%f
0,823817
sales%g
0,669414
sales%h
0,776448
sales%i
0,664272
sales%j
0,633991
sat1
0,966102
sat1a
0,964621
sat1b
0,976425
service service%a service%b service%c service%d service%e service%f
213
service%g value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
Value for money Vehicle Design Vehicle quality comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design
0,951949
design%a
0,901079
design%b
0,849767
design%c
0,933445
design%d
0,890844
image image%a image%b image%c image%d
214
image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d oczek%f oczek%g sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service service%a service%b service%c service%d service%e service%f service%g value1
0,990470
value2
0,990339
vehqual
0,907941
vehqual%a
0,858737
vehqual%b
0,531512
215
vehqual%c
0,691101
vehqual%d
0,664484
vehqual%e
0,788866
vehqual%f
0,837131
vehqual%g
0,602734
Path Coefficients After-sales quality Comfort Costs of ownership Expectations After-sales quality Comfort Costs of ownership
0,469850
Expectations Image
0,318826
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design Vehicle quality
Image After-sales quality
Loyalty
Overall satisfaction Sales quality
0,199762
Comfort Costs of ownership Expectations
0,264030
Image Loyalty Overall satisfaction
0,476481
Sales quality
0,370188
Value for money
0,263727
Vehicle Design
0,228841
Vehicle quality
0,598727
0,643344
Value for money Vehicle Design Vehicle quality After-sales quality
0,166142
Comfort
0,758564
Costs of ownership
216
Expectations Image
0,080849
Loyalty Overall satisfaction Sales quality Value for money Vehicle Design Vehicle quality
0,708882
Outer Weights After-sales quality Comfort Costs of ownership Expectations comfort
0,271227
comfort%a
0,228339
comfort%b
0,176370
comfort%c
0,155357
comfort%d
0,133583
comfort%e
0,157692
comfort%f
0,157604
comfort%g
0,105982
comfort%h
0,133280
costs
0,223340
costs%a
0,095635
costs%b
0,191729
costs%c
0,271134
costs%d
0,238838
costs%e
0,211937
design design%a design%b design%c design%d image image%a image%b image%c image%d image%e image%f
217
image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d
0,410311
oczek%f
0,379351
oczek%g
0,416126
sales sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service
0,149729
service%a
0,154507
service%b
0,151026
service%c
0,131583
service%d
0,126007
service%e
0,138867
service%f
0,154127
service%g
0,142760
value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d
218
vehqual%e vehqual%f vehqual%g
Image
Loyalty
Overall satisfaction Sales quality
comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design design%a design%b design%c design%d image
0,180053
image%a
0,166860
image%b
0,150272
image%c
0,184022
image%d
0,188729
image%e
0,099408
image%f
0,084730
image%g
0,128439
image%h
0,182850
loyalty1
0,315840
loyalty2
0,319585
loyalty3
0,268910
loyalty4
0,304374
219
oczek%d oczek%f oczek%g sales
0,139083
sales%a
0,111480
sales%b
0,119984
sales%c
0,111997
sales%d
0,105346
sales%e
0,121582
sales%f
0,118556
sales%g
0,099577
sales%h
0,116801
sales%i
0,100462
sales%j
0,113910
sat1
0,341292
sat1a
0,343210
sat1b
0,347400
service service%a service%b service%c service%d service%e service%f service%g value1 value2 vehqual vehqual%a vehqual%b vehqual%c vehqual%d vehqual%e vehqual%f vehqual%g
220
Value for money Vehicle Design Vehicle quality comfort comfort%a comfort%b comfort%c comfort%d comfort%e comfort%f comfort%g comfort%h costs costs%a costs%b costs%c costs%d costs%e design
0,227457
design%a
0,169434
design%b
0,211009
design%c
0,240102
design%d
0,255229
image image%a image%b image%c image%d image%e image%f image%g image%h loyalty1 loyalty2 loyalty3 loyalty4 oczek%d oczek%f oczek%g sales
221
sales%a sales%b sales%c sales%d sales%e sales%f sales%g sales%h sales%i sales%j sat1 sat1a sat1b service service%a service%b service%c service%d service%e service%f service%g value1
0,506563
value2
0,503125
vehqual
0,220447
vehqual%a
0,197553
vehqual%b
0,104167
vehqual%c
0,152303
vehqual%d
0,144527
vehqual%e
0,175684
vehqual%f
0,187009
vehqual%g
0,130075
222
Index Values Results Index Values for Latent Variables LV Index Values After-sales quality
7,630681
Comfort
8,952333
Costs of ownership
7,290020
Expectations
9,542902
Image
8,345158
Loyalty
8,331630
Overall satisfaction
7,950921
Sales quality
8,957169
Value for money
7,559792
Vehicle Design
9,264105
Vehicle quality
8,656681
223
