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The current issue and full text archive of this journal is available at www.emeraldinsight.com/0960-0035.htm

IJPDLM 38,3

How procurement managers view low cost countries and geographies
A perceptual mapping approach
Joseph R. Carter, Arnold Maltz and Tingting Yan
W.P. Carey School of Business, Arizona State University, Tempe, Arizona, USA, and

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Received 28 August 2007 Revised 29 January 2008 Accepted 31 January 2008

Elliot Maltz
Atkinson School of Business, Williamette University, Salem, Oregon, USA

Abstract
Purpose – There is good evidence that the shift in global sourcing is toward so-called “low cost country suppliers.” Yet conditions in these countries are often not well-known. At the same time, best practices in integrated supply dictate a multi-faceted decision, rather than basing supplier location on a single attribute say, labor cost alone. With these issues in mind, a research project was formulated with two primary objectives. First, the authors wanted to compile the knowledge and perceptions of purchasing managers regarding low cost regions and their capabilities and to reflect the multiple factors involved in current sourcing strategies and supplier selection decisions in these low cost geographies. Second, the authors wanted to compare managers’ subjective perceptions with objective data regarding attributes of sourcing locations to identify the relationship between perceptions and reality. This paper aims to explore the issues. Design/methodology/approach – The authors surveyed over 100 sourcing professionals on their perceptions of various low cost sourcing alternatives. Perceptual mapping techniques were used to combine the rankings on some 12 different attributes to visualize how the various attributes relate to each other and how the low cost regions compare when rated against sourcing managers’ ideal perceptions. Findings – The research results show that procurement managers select regions for low cost sourcing based on both specific measures and individual and/or group perceptions of the region, whether these perceptions are correct or not. This paper probes these perceptions. Also the paper compares these subjective perceptions with objective data to show that cultural stereotypes may bias managers’ perception of location-specific characteristics. The paper closes with implications for procurement managers and opportunities for further research. Practical implications – The authors have demonstrated that purchasing managers choose sourcing locations using multiple criteria instead of only focusing on cost. But some perceptions are biased by cultural stereotypes and do not reflect reality. This suggests that managers have to be careful when using their subjective judgment in choosing sourcing locations. Originality/value – The authors believe that visual representations of alternative sourcing options have great potential to improve the efficiency of cross-disciplinary and multi-company teams that are increasingly responsible for global sourcing strategies. Comparing managers’ perception with objective data of location attributes shows that mangers’ perception may be biased by cultural stereotypes. Keywords Sourcing, Supplier evaluation, International business Paper type Research paper

International Journal of Physical Distribution & Logistics Management Vol. 38 No. 3, 2008 pp. 224-243 q Emerald Group Publishing Limited 0960-0035 DOI 10.1108/09600030810866995

Introduction Global sourcing is now an automatic expectation to respond to competition. But the choice of where to obtain goods and services is not a static decision. It is subject to continual reevaluation. As Table I shows, patterns of US sourcing can move very rapidly. Furthermore, there is good evidence that the shift will be toward so-called “low cost country suppliers” (LCCS) (Timmermans, 2005). Much literature in outsourcing focuses on specific supplier-related instead of location-related criteria. Thus, little is known about sourcing conditions in these countries. At the same time, best practices in sourcing dictate a multi-attribute, weighted decision, rather than basing supplier location on a single factor say, labor cost alone (Stalk, 2006; Timmermans, 2005; Butta and Huq, 1992). With these issues in mind, the authors formulated a research project with three primary objectives. First, the authors wanted to compile the knowledge and perceptions of purchasing managers relative to low cost regions and their capabilities. Second, the authors wanted to reflect the multiple factors involved in current sourcing strategies and supplier selection decisions (Butta and Huq, 1992; Kirkwood et al., 2005). Third, the authors wanted to compare managers’ subjective perceptions with objective data regarding attributes of sourcing locations to identify the relationship between perceptions and reality. Therefore, with the help of the Center for Advanced Procurement and Supply Research (CAPS Research), the authors surveyed over 100 procurement professionals on their perceptions of various low cost country sourcing alternatives. All of these responding firms were large US Fortune 500 multinationals. We asked for rankings on some 12 different attributes that have been identified as important drivers of global sourcing decisions (Maltz et al., 2004; Carter and Narasimhan, 1996). Then perceptual mapping (Hair, 1995) was used to combine these rankings to visualize how the various attributes relate to each other and how the low cost regions compare when rated against procurement managers’ ideal perceptions. Finally, conceptions are compared with objective data to find out whether these perceptions reflect the reality or are biased by cultural stereotypes.

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2000 US total Canada China Mexico Japan Brazil India Viet Nam South Africa Czech Republic Egypt Cambodia Romania 1,222.0 229.0 100.0 135.0 147.0 14.0 10.7 0.8 4.2 1.1 0.9 0.8 0.5

2005 1,671.0 288.0 244.0 170.0 138.1 24.4 18.8 6.6 5.9 2.2 2.1 1.8 1.2

Percentage of change 37.3 25.6 143.3 25.2 2 5.8 76.4 76.0 706.9 39.5 106.4 135.5 113.9 157.0

Source: US Department of Commerce (2007)

Table I. Selected US imports by value 2000 vs 2005 ($ in billions)

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The remainder of the paper is organized as follows. The first section includes a short literature review on previous studies in global sourcing and the limited treatments of low cost country sourcing, integrating procurement managers’ perception in supplier selection decision making and the role of cultural stereotypes in forming these perceptions. Then the authors explain the objectives and approach of the research in more detail, as well as the details of the survey and sample frame. The results follow, including both single attribute and multi-attribute perspectives on the various low cost regions. Then comparisons between the mapped perceptions of different areas and objective data of location attributes are conducted to identify biases. Finally, the paper closes with a discussion of implications of the results for academics and practitioners, including limitations which point to the need for further in-depth work on low cost region sourcing issues. Literature review Companies are establishing and executing global outsourcing plans in order to (Carter et al., 2005): . match competitors in their outsourcing endeavors; . improve non-competitive cost structures; . focus on core competencies and reduce capital investment and overall fixed costs; . achieve cost competitive growth in the supply base for goods, services and technologies in a company’s value chain; and . establish a future sales footprint in a low-cost country by outsourcing basic goods or business processes. Effective outsourcing requires good processes to evaluate the many factors related to where to outsource, that is, how to find the supplier locations globally that align best with future plans (Hedderich et al., 2005). Such processes will often include a screening step with respect to geography, since factors such as infrastructure, market attractiveness, and cost levels are characteristics of regions or countries rather than specific suppliers (Teng and Jaramillo, 2005). All these screening factors frequently lead procurement managers to consider low cost countries and geographies for their supply needs. Although the work being transferred to Indiaand China-based suppliers has received the majority of the headlines, countries such as the Brazil, Russia, and the Czech Republic are also significant locations for outsourcing (Hedderich et al., 2006). Thus, how managers perceive these potential geographies before they select specific suppliers within each area is an important unanswered question. The influence of managers’ perceptions on actual decisions is well-established. Webster and Wind (1972) in their book Organizational Buying Behavior suggested that both rational variables such as price, quality, flexibility, etc. and individual psychological variables, such as perceptions of the decision-making context, should be considered in explaining organizational purchasing behaviors. In fact, Sterman (1989) found that misperceptions of buyer-supplier communications can lead to poor performance. Similarly perceived risk has been shown to significantly affect complex decision making, such as make versus buy evaluations (Sitkin and Weingart, 1995; Heragu et al., 2005). In another study, perceptions of usefulness and ease of use were found to be direct antecedents of a buyer’s behavioral intention to use a new

technology (Bala and Long, 2004). It seems clear that analytical reasoning alone cannot be effective unless it is guided by emotion and affect (Slovic et al., 2007). Perceptions can be as influential as objective knowledge on complex decision processes. However, the literature in supply management, especially in the supplier selection area, does not highlight the differing perceptions of purchasing managers. Supplier selection studies can be grouped into two major categories: supplier selection criteria (Wilson, 1994; Vonderembse and Tracey, 1999; Sharland, 2003; Choi and Hartley, 1996; Weber et al., 1991; de Boer et al., 2001) and supplier selection decision models (Sarkis and Talluri, 2002; Muralidharan, 2002; de Boer and van der Wegen, 2003; Khurrum and Faizul, 2002; Narasimhan et al., 2006). They emphasize the strategic importance of the supplier selection process and highlight the tradeoff among quality, cost, and delivery performance measures in the supplier selection process. Most of these studies ignore procurement managers’ perception as an important information source for outsourcing decision making. Also little research is done to explore purchasing managers’ criteria used to select sourcing areas instead of individual suppliers within a certain area. Although it was shown ( Verma and Pullman, 1998) that managers’ perception do not necessarily lead to their actual decisions in the individual supplier selection process, it does not necessarily mean managers’ perception of location-related advantages/disadvantages have no impact on their actual location choice. The reason is that many geography-specific criteria, such as security of intellectual property, government corruption, etc. unlike characteristics related with individual suppliers within a certain area, are often difficult to quantify and evaluate. Thus, experienced procurement managers’ perceptions may be a valuable source for understanding geographic areas selection. Managers’ perceptions, however, may be biased. White (1979) demonstrated empirically the existence of stereotypes US purchasing managers have about industrial products manufactured in England, France, Italy, and West Germany, as well as the USA. Chen et al. (2007) showed that culture could act as either a moderator or an independent variable to affect managers’ perceptions. Social psychologists have long been interested in stereotypes and prejudice, concepts that are typically viewed as being very much interrelated. Devine (1989) found out that the stereotype is automatically activated in the presence of a member (or some symbolic equivalent) of the stereotyped group and that low-prejudice responses require controlled inhibition of the automatically activated stereotype. Blair (2002) further found out that automatic stereotypes and prejudice are influenced by: . self- and social motives; . specific strategies; . the perceiver’s focus of attention; and . the configuration of stimulus cues. Literature in this field holds that prejudice is inevitable as long as subjects are knowledgeable of cultural stereotypes unless subjects consciously monitor and inhibit stereotypes activation. From this theoretical perspective, we propose that culture stereotypes play a role in forming managers’ perception of different sourcing areas. Furthermore, managers’ perception may be biased by these stereotypes and do not reflect the objective truth.

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This study contributes to the literature by filling a gap in and providing an extension of supplier selection decision-making theory. First of all, the authors extend previous literature on supplier selection and outsourcing by exploring dimensions of criteria used by managers to choose sourcing locations, instead of the individual supplier, in the context of low-cost-country sourcing. The perceptual mapping empirically derived in this research is a first attempt in outsourcing literature to map purchasing managers’ perception of different low-cost sourcing areas. Second, the authors find that cost is not the only dominating dimension in mangers’ perceptions. This is similar to findings in the literature regarding managers’ perception of individual suppliers, where quality and delivery performance are at least as important as cost. Finally, the perceptual mapping is further compared with objective data to show the role that culture stereotypes play in forming mangers’ perceptions, which are believed to be good predictors of their actual sourcing decisions. Objectives and focus of this research This research investigates perceived characteristics of locations where work can be transferred to an outside supplier in a low cost location. The overarching goal of the study is to gather and share beliefs from procurement managers in leading companies outsourcing globally to low cost countries and geographies in order to help businesses think through the complexity of their own strategies and achieve greater success from their global outsourcing endeavors. Low cost location activities that support sourcing decisions are the focus of this research. “Low Cost Country Sourcing” refers to the process of procuring products, parts and services from suppliers in countries with lower labor and materials costs. So-called “low cost countries and geographies” have become a target of opportunity for procurement managers based in developed nations, a trend predicted in the international business and development literatures sometime ago (Gereffi and Fonda, 1992; Czinkota and Ronkainen, 1997) This reality is reflected in the well-documented importance of unit costs in sourcing evaluation instruments and procedures as well as the responses of procurement managers in empirical research projects (Carter and Narasimhan, 1996; Kirkwood et al., 2005). Indeed, a recent survey found that over 50 percent of North American firms and nearly 40 percent of European companies plan to increase sourcing from China between 2005 and 2008. Substantial numbers of North American and Western European companies also will increase sourcing from Mexico, Southeast Asia, and Eastern Europe (Koudal and Engel, 2007). Clearly, purchasing managers are actively evaluating low cost opportunities virtually on a daily basis. However, there is little research in the purchasing and supply management arena comparing the perceived strengths and weaknesses of various low cost countries and geographies, even though there are clearly major differences between, for example, Mexico and China. Furthermore, it is not immediately clear how to formulate this kind of comparison, since sourcing decisions are often multi-dimensional, even if cost is “first among equals” (Weber et al., 1991). Although there is some empirical research with procurement managers in the sociology and development literature (Gereffi, 1994; Schmitz and Knorringa, 2002), the work is primarily descriptive. Yet for purchasing managers, evolving industry practice points to the importance of a “portfolio” of suppliers and locations to minimize supply risk

and maximize overall performance. Understanding the location-specific advantages and disadvantages of various suppliers will facilitate the formation of such portfolios. Also, whether managers’ perception of these location-specific advantages and disadvantages reflects the reality or is biased by some stereotypes is an important question in terms of determining how much unbiased information could be obtained from exploring managers’ perception. Research hypotheses Derived from previous outsourcing literature, especially supplier selection literature, and the theory of stereotypes and prejudice in sociology, this section develops hypotheses examining purchasing managers’ perceptions of location-specific advantages and disadvantages of low cost countries in their sourcing decisions. Although the name “Low Cost Country Sourcing” seems to suggest that cost is the primary, even only, driver in sourcing from such low cost countries as China and India, we believe that experienced purchasing managers in leading companies do not base their location choice only on cost. As previous literature suggests (Kouvelis and Niederhoff, 2007; Sarkis and Talluri, 2002), low labor cost is no longer the only driver of much US offshoring/outsourcing activity. Furthermore, supply professionals have increasingly emphasized the need to take into account multiple factors when making sourcing/outsourcing/offshoring decisions. Thus, we propose: H1. Perceived location-specific advantages and disadvantages of various suppliers in low cost countries and geographies have multiple underlying dimensions not limited to cost. As argued above, sourcing country selection is a multi-attribute decision. Thus, it is possible that different geographical areas outperform the others on different individual attributes. Furthermore, different companies have different motivations for outsourcing, leading to different strategic preferences for sourcing locations. Therefore, it is less meaningful and efficient to use individual attributes to aid the selection than using aggregate attributes, which are the underlying driving constructs identified by perceptual analysis. Thus, we propose: H2. Managers’ perception of countries’ location-specific advantages and disadvantages at an aggregate-attribute level produce more meaingful insights for aiding location selection decisions than that examining perceptions one attribute at a time. Taking the theoretical perspective that the causal relationship between cultural stereotypes and prejudice is almost unavoidable (Devine, 1989), we suggest that managers’ perceptions of location-related characteristics are biased by their cultural sterotypes. Country-related characteristics, such as work ethic, intellectual property security, government corruption, etc. are usually hard to quantitatively verify. Sourcing managers have to rely on either their experience or general knowledge of that specific country or people from that country. From the theory of stereotypes and prejudice, we know that prejudice is inevitable as long as subjects are knowledgeable of cultural stereotypes, unless subjects consciously monitor and inhibit stereotype activation. Thus, we have reason to believe that:

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H3. Managers’ perception of some location-specific advantages and disadvantages of different suppliers in low cost countries and geographies is biased, and in some cases, incorrect. Research approach As our main source of primary data, the team developed a survey that profiled each respondent’s perception of sourcing from various low cost countries and geographies. The team surveyed over 100 procurement managers on their perceptions of ten low cost geographies across 12 evaluation criteria of attractiveness as supply sources (Maltz et al., 2004). Perceptual mapping techniques were used to condense the information provided into a two dimensional display showing not only the relative attractiveness of the various low cost regions, but also suggesting the sources of the relative competitive positions for the various geographies. Perceptual mapping is a graphics technique used by researchers that attempts to visually display the perceptions of respondents, usually in two dimensions that are composites of rankings on multiple factors. Displaying our survey respondents’ perceptions of related low cost countries and geographies is only half the story. Perceptual maps also display ideal vectors[1]. Ideal vectors reflect preferences among possible benefits and combinations of benefits summarized in two dimensions as seen by each respondent. Average ideal vectors can be generated based on the expressed preferences of each respondent in the overall sample. The direction of the ideal vector indicates the relative importance of the two dimensions to the overall ideal, while the length of the vector represents the magnitude of the combined ratings on the included benefits. The ideal vector for the full sample provides guidance as to the overall sample’s view of the relative importance of the benefits suggested by the composite dimensions. Similarly, ratings for each country can be combined and a position computed which represents the country’s composite ratings vs the two derived dimensions. Ideal vectors can also be generated at the individual level. In this case, clusters of ideal vectors can be identified to produce segments within the overall sample. As we note below, individual ideal vectors can radiate from the origin to anywhere on the map. As such it is possible to identify procurement manager segments with very different benefit profiles. A company considering outsourcing can use the map to identify the benefit profile that suits them and then identify the country that best fits that benefit profile. If sufficient industry information is available (e.g. company size, industry) a firm may also use the map to identify the benefit profiles attached to competitive firms. This allows a firm to reconsider whether the current benefit profile they are using to make sourcing decisions is consistent with the demographic group in which they are competing. Perceptual maps need not come from a detailed study, and in fact the data here are created based upon the respondents’ understanding of each country or geography using their best judgment. We do not claim “objective reality” for these results. But the perspectives summarized represent the current thinking of procurement managers who have significant input into the outsourcing, supplier selection, and location decisions.

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Survey and sample frame A survey instrument was formulated which asked each respondent to rate ten different geographical areas (geographies) on 12 attributes. A list of the geographies and their description on the survey is: . Coastal China (e.g. Beijing, Shanghai, Guangdong). . Inland China (e.g. Chongquing, Lanzhou, Kunming). . Less developed Asia (e.g. Vietnam, Cambodia). . Eastern Europe (e.g. Romania, Bulgaria, Ukraine). . Russia/Central Asia (e.g. Russia, Kazakhstan, Baluchistan). . Africa (other than South Africa and Botswana). . South America (other than Brazil, Chile, and Argentina). . Urban India (e.g. Bangalore, Mumbai, Delhi). . Rural India. . Mexico. A list of the relevant attributes is: . Labor cost – unit cost of direct labor, usually per hour or per piece. . Work ethic. . Security of intellectual property. . Attraction of local market. . Reliably meet customer requirements – deliver complete orders on time. . Transportation reliability – consistency of lead times. . Transportation cost – cost from source to buyer’s location. . Government support for business. . Political stability. . Flexibility – ability to react to changes in requirements. . Predictable border clearance times. . Government corruption. . Overall, attractiveness for sourcing. We also asked each respondent to rate his/her overall preference for each of the ten geographies. The survey was physically designed and administered online (Zoomerang) by CAPS Research in 2006. Attributes were chosen based on previous case study work (Maltz et al., 2004) as well as a review of previous articles on global sourcing criteria. We note that recently consultants and academics have suggested that US firms in particular have placed too much importance on lower labor costs in less developed countries and are often disappointed (Kouvelis and Niederhoff, 2007; Stalk, 2006). In addition, the supply management literature specifically advocates a multidimensional decision making process. However, other than checklists and ranking procedures, there are few examples of how to address the various decision drivers simultaneously and in a

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rigorous, orderly fashion. Thus, one of the contributions of this research is a possible approach to combining the various recommended criteria for global outsourcing. The choice of geographies was based on other research (Crnic et al., 2006) and upon previous case study work, conversations with practitioners, and in depth scanning of practitioner journals. We deliberately elected to go beyond the typical country designation in the case of China and India because several practitioners had pointed out the wide variation between regions in those countries. On the other hand, comparison procedures such as perceptual mapping have a practical upper limit in terms of the number of alternatives respondents can evaluate. Therefore, we used regional country groupings in the case of Southern Asia, South America, and Eastern Europe. Finally, we culled out Mexico separately because of its large volume of trade with the USA and the continuing effects of NAFTA. Our initial sample frame was approximately 1,000 purchasing managers and executives from the CAPS Survey database. Over 170 managers responded, but many had little or no data to share on the various geographies. Our final sample consists of 101 fairly complete surveys, although actual responses vary by geography. Analysis for non-response bias was performed by comparing early vs late responses on ten randomly selected questions (Armstrong and Overton, 1977). For all ten questions unequal variance t-tests could not reject the hypothesis of equal mean values. Actual t-statistics ranged from 0.35 to 0.97. Around 81 respondents were employed by organizations headquartered in North America, twelve were from Western Europe, and eight were from Asia (4), the Middle East (2), Australia (1) and South America (1). In terms of industry classification, the largest groups were “industrial manufacturing” (16), aerospace/defense (7), chemical (7), consumer products (7), food and beverage (6), and financial services (6). Parent organizations were large, with mean employment of nearly 40,000. Forty of the respondents worked for companies with over $10 billion in revenue in 2005, ten for companies between $5 and $10 billion, and 39 companies recorded 2005 revenues between $1 billion and $5 billion. Results Individual attribute findings The outsourcing decision is driven by multiple considerations, but prior research has established the continuing importance of cost as “first among equals” (Kirkwood et al., 2005). Previous research has also identified and evaluated a variety of possible influences on the sourcing/outsourcing decision. In conversations with procurement managers, we similarly found that one, two, or three specific concerns often emerged in addition to the need for cost reduction. Thus, we begin our analysis of supply manager’s views on geographies by looking at how these geographies ranked on individual attributes. Table II summarizes key findings from our analysis at the individual attribute level. Respondents were asked to rate each region on all attributes (column 1) on a scale from 1 to 7, with 7 indicating a very favorable impression of the region on the attribute, and 1 indicating a very unfavorable impression of the region on the specific attribute. The second column of the table shows the mean for all respondents across all regions on the particular attribute, the third column lists the two regions with the highest mean

Attribute Labor cost Work ethic Security of intellectual property Attraction of local market Reliably meet customer requirements Transportation reliability Transportation cost Government support for business Political stability Flexibility Predictable border clearance times Government corruption Overall attractiveness for sourcing

Mean 5.18 4.93 3.55 4.79 4.55 4.29 3.97 4.49 4.41 4.28 4.33 3.67 4.62

Two regions with highest scores Inland China (5.93) Less developed Asia (5.90) Coastal China (5.69) Urban India (5.50) Mexico (4.51) Urban India (4.39) Coastal China (6.12) * Urban India (5.59) Coastal China (5.22) Urban India (5.18) Coastal China (5.26) Mexico (5.08) Mexico (5.00) Coastal China (4.44) Coastal China (5.18) Urban India (5.06) Urban India (5.35) Mexico (5.33) Coastal China (5.05) Urban India (4.88) Mexico (5.41) Urban India (4.92) Urban India (4.45) Mexico (4.18) China (5.80) Urban India (5.47)

Two regions with lowest scores South America (4.60) Mexico (4.62) Africa (3.66) * Russia (4.36) Inland China (2.40) Coastal China (2.63) Africa (3.41) * Russia (4.34) Africa (3.50) * Russia (4.12) Africa (3.23) Less dev. Asia (3.58) Africa (3.10) Rural India (3.37) Africa (3.31) Russia (3.73) Africa (2.60) * Russia (3.71) Africa (3.14) * Russia (3.84) Africa (3.04) * Russia (3.67) Africa (2.76) Russia (3.02) Africa (2.86) * Russia (3.75)

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Note: *Indicates difference between the two regions is statistically significant at p ¼ 0.05 based on two sample t-test

Table II. Overview of attribute evaluation by geography (all variables scored from 1 to 7, with 7 being very favorable and 1 unfavorable)

scores, and the fourth column shows the two regions with the lowest mean scores. Actual means by region are in parentheses[2]. Any screening process requires a well-defined ranking procedure which produces clear results. Interestingly, Table II suggests that Africa can typically be eliminated from consideration because it is statistically worse than even the second lowest area on the criteria of work ethic, local market attraction, reliability, political stability, flexibility, border clearance times, and overall attractiveness. Furthermore, Africa was also rated lowest, though not statistically distinct, on transportation reliability, transportation cost, government support for business, and government corruption. In fairness we should note that only 50 or so of our respondents rated Africa at all, vs 70-80 raters for the other geographies, suggesting that lack of knowledge, rather than first hand experience of poor performance, may be driving the higher perceived risk of sourcing products and services from Africa. It is possible that companies that have never sourced from Africa will have a better experience, but we cannot conclude that from our information. To avoid these possible biases, we elected to eliminate Africa from the multi-attribute analysis which is shown below.

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Consideration of the highest scoring regions on each attribute resulted in a much less clear result. Although Coastal China was ranked the highest on six attributes – work ethic, local market attraction, reliability, transportation reliability, government support, flexibility, and overall attractiveness – only one of these scores, for local market attractiveness, was statistically different ( p ¼ 0.05) from the next highest region. There was no statistically distinct “winner” on the other attributes. Inland China and Less Developed Asia were essentially tied on labor cost, Mexico and Urban India were rated roughly equal on intellectual property, political stability, border clearance, and corruption, and Mexico and Coastal China were roughly equal on transportation issues[3]. This lack of clarity reinforces the need for a multi-attribute perspective on the evaluation of competing geographies. Porter (1990) found that specific regions successfully specialized based on a combination of local conditions, and a number of procurement scholars have suggested that sourcing decisions should be based on multiple considerations, rather than one dominant advantage. Sarkis and Talluri (2002) and Kirkwood et al. (2005) both set forth analytically consistent, auditable approaches to the multi-attribute sourcing problem for supplier selection. Below we propose and demonstrate a different approach as applied to the issue of regional sourcing selection. In so doing we attempt to combine all of the single attribute information available to display the relative positions of all the regions in a spatially consistent, helpful visual perspective. Geographies and multi-attribute analysis Although low labor cost was the initial driver of much US offshoring/outsourcing activity, this is no longer the case (Kouvelis and Niederhoff, 2007). Furthermore, supply professionals have increasingly emphasized the need to take into account multiple factors when making sourcing/outsourcing/offshoring decisions (Sarkis and Talluri, 2002). However, analytical approaches to simultaneously incorporate multiple influences and communicate the interaction of these influences have been relatively rare in the supply management literature. Marketing also recognized early on that consumer purchasing decisions involved balancing many factors. Recognizing that new products were particularly risky, marketers looked for ways to better understand how consumers combined multiple buying criteria and how to communicate the subtleties of the consumer decision process to new product developers. Borrowing from psychology, marketers began constructing perceptual maps of consumer product evaluations. These maps represent a visual summary of multidimensional customer evaluations of products and services. Perceptual mapping techniques allow managers to see comparisons of many objects at once, with the assurance that the relative distance between the objects on the map is calculated to mirror the combined ratings of each of the objects on several dimensions by several evaluators. There are a variety of methods for transforming multiple evaluation ratings into two-dimensional (or higher) maps, depending on the distance rules used, the availability of overall preferences in addition to individual dimensions, and whether ideal points/vectors are a goal of the analysis. (Hair, 1995). The authors collected 101 observations for ten low cost geographies on 12 attributes. We applied the “CPM System for Composite Product Mapping” from

Sawtooth Software to obtain two composite dimensions for mapping purposes, and then to produce perceptual maps which show the position of both the geographies and the attributes vs the two composite dimensions. The makeup of the two dimensions is shown in Table III, and the derived map is shown in Figure 1[4]. Vector 1, which is the horizontal or x-axis in Figure 1, is characterized by high levels of attributes associated with reliability or predictability. Thus, geographies with larger values of vector 1 are perceived as being more reliable and stable areas to source from. As Figure 1 indicates, Coastal China and Urban India stand out on this basis, while Russia and less developed Asia (Vietnam, Cambodia, etc.) are seen as much riskier and less dependable locations. Vector 2, the vertical or y-axis in Figure 1, represents the well-known trade-off (especially associated with China) of low labor cost and good productivity vs high risk to intellectual property. Thus, China, both Coastal and Inland, scores well on labor cost but badly on intellectual property safeguards, while Mexico is nearly 180 degrees opposite from Coastal China on the map. The above observations go to the face validity of our findings. The map and dimensions are generally consistent with concerns raised by practitioners and in the practitioner literature. Note, for example, that the “reliability” axis is in the same general direction as flexibility, political stability, and reliable production, each of which contributes to order filling capability. Similarly, transport cost, transport reliability, border crossing predictability, and government corruption have similar orientations, which is not surprising to transportation professionals. Border crossings can only be consistent where government corruption is relatively low, and international transportation service and cost in turn depend on predictable border crossings. From these results, one can see that H1 and H2 are supported by the data. Managers do use multiple criteria to make sourcing location selections. For example, the first dimension considered is the reliability dimension which accounts for approximately 35 percent of the variance. The second dimension, the trade-off between cost and intellectual property protection accounts for approximately 15 percent of the variance. This suggests that procurement managers may consider reliability prior to the consideration of cost. This is contrary to conventional wisdom which considers cost first among equals. Analyzing different countries’ position along these same criteria at

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Attribute Labor cost Work ethic Intellectual property Market attraction Reliable delivery Reliable transportation Transportation cost Government support for business Political stability Flexibility Predictable border crossing Corruption

Vector 1 2 0.175 0.462 0.210 0.669 0.966 0.830 0.723 0.910 0.925 0.973 0.927 0.827

Vector 2 0.748 0.773 20.938 0.697 0.110 20.219 20.372 0.365 20.017 0.136 20.215 0.827

Table III. Composite attribute vectors for preference map

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Lacost

Weth CChina Matt

LDAsia Gsupp Flex RProd Pstab RIndia Russia EEur SAM UIndia Border Rtran Gcorr Tcost

Mexico Intprop

CChina – Coastal China EEur –Eastern Europe IChina – Inland China LDAsia – Less Developed Asia

MAP ABBREVIATIONS KEY Mexico – Mexico RIndia – Rural India Russia – Russia/Central Asia SAM – South America

UIndia – Urban India

Figure 1. Perceptual map of attributes and geographies

Border – Predictable border clearance times Flex – Flexibility Gcorr – Government Corruption Gsupp – Government Support Intprop – Security of Intellectual property Lacost –Labor Cost

Matt – Attraction of local market RProd – Reliability to meet customer requirements Pstab – Political Stability Rtran – Transportation Reliability Tcost – Transportation Cost Weth – Work Ethic

an aggregate level provides new insights which may be masked when considered at individual attribute level. However, the power of the technique is its ability to show all geographies on the same surface and understand their strengths and weaknesses vs each other at a glance. This is strengthened by the fact that we have overlaid a preference map on the perceptual map.

Insights from the preference map The preference analysis utilizes paired comparisons to infer relative ideal vectors for each individual radiating from the origin of the map. These ideal vectors are then overlaid on the perceptual map to get a sense of the ideal benefit profile given the tradeoffs that have to be made when choosing among products (or in our case regions or countries). The overlaid perceptual map is called a preference map. The preference map in Figure 2 shows the average ideal vector for the sample as a whole and spaces in the map where large numbers of individual level ideal vectors are located. Note that the average ideal vector from the total sample splits the upper right hand quadrant. Also note that Coastal China is located very close to the end of the vector indicating, not surprisingly, that Coastal China is a preferred sourcing location on average. The three triangular regions on the map show areas where large numbers of ideal vectors end. Thus, 43.21 percent of respondents show ideal vectors in the upper part of the upper right hand quadrant. These companies are focused on cost and reliability but more focused on cost. As such they are likely to see Coastal China, Inland China, and less developed Asia as desirable sourcing locations. Another 23.46 percent of respondents are in the lower part of the upper right hand quadrant. These companies are also focused on cost and reliability but more focused on reliability. Thus, they are more likely to see Coastal China as a strong sourcing candidate. Finally, we have another group of respondents who have ideal vectors located in the upper part of the of the lower right hand quadrant. These companies are focused on reliability and the protection of intellectual property (though more focused on reliability). They may very well begin their search for new sources with urban India.

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Low Cost Inland China 43.21% LD Asia Low Reliability 23.46% High Reliability Coastal China Avg. Ideal Vector

Rural India Russia Eastern Europe 23.46% Urban India

South America Mexico

Intellectual Property Protection

Figure 2. Preference map

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Perceptions versus reality The question arises as to the accuracy of stereotypical perceptions. Do regional cultural stereotypes impact the accuracy of managers’ perceptions? There is empirical evidence that this does indeed occur. For example, comparing the managers’ perceptions of labor cost with empirical data compiled by the Bureau of Labor Statistics (BLS) reveals a lack of correlation between perception and reality. As the North American purchasing managers perceive and rate Mexico as having the most unfavorable labor cost relative to the other regions, BLS (2007) data provides a contrarian factual example. Coastal China, rated by the respondents as very favorable, is in fact on a par with Mexico labor costs. A similar lack of correlation between perceived and factual measures exists upon examining the attribute evaluations of transportation reliability and transportation cost. While Mexico is rated by respondents as being one of the highest rated regions on a par with Coastal China, in fact, Mexico is rated factually as being far below China on performance for these two attributes in a recent comprehensive survey of logistics capabilities (Arvis et al., 2007). Finally, a measure of government corruption provided by “Corruption perception index” (Transparency International, 2007) is also not consistent with our managers’ perceptual attribute evaluations. In our data, Central India and Africa are ranked as the best and the worst in terms of government corruption. But CPI shows that Central India and Africa are at the same level in terms of government corruption. Obviously bias exists here. Thus, we could see that H3 is also supported. Managers’ perceptions of location-related characteristics are biased by regional stereotypes. However, it is not so simple to say that managers’ perceptions of attribute values are wrong. For some regions they are factually incorrect and in other cases more accurate. But the idea that perceptions are impacted by regional stereotypes has face validity and supported factually by empirical comparisons. Key findings and implications This research should provide several prescriptive benefits for practicing procurement managers and foster several streams of future research for academicians. From these perspectives, the analysis has provided insights on several issues. . Where there are cross-functional members of a sourcing or buying team, the perceptual map gives everyone on the sourcing team a sense of how the various countries/regions are viewed. This helps foster discussions of how to leverage overall spend by sourcing multiple items and services from the same region or country. . The perceptual map serves as a screening mechanism for sourcing strategy. If managers are charged with sourcing based on low cost, for example, the map gives them an easy way to compare regions along the cost axis while simultaneously being able to gauge service or other considerations. . The map is a fine communication device to non-procurement executives from the rest of the company, or even the supply chain. When a non-procurement executive asks about the how and why of global sourcing, it is easy to superimpose key

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supplier locations on top of the overall map to see what the most attractive strategy might be. Comparing managers’ perceptions with objective data of location attributes clearly demonstrates that perception is biased by cultural stereotypes. This is consistent with assertions made in the extant literature. Finally, the map can serve to communicate with suppliers and authorities in the political structure of the geographies. Presently, most low cost geographies are actively seeking investment and economic development. Perceptual maps can show these areas where they must improve to equal or better the competition, and equally, where they should not slip since it might give the competition a significant advantage.

Low cost countries and geographies 239

Limitations and the need for further research Although our results have significant “face validity,” more work is required to understand the value of this approach as well as the usefulness of the specific findings. The sample used is relatively small and spread across a multitude of industries, although other research suggests that sourcing needs may vary by industry and items to be outsourced (Global Competitiveness Studies, 2006). Furthermore, it would be extremely useful to construct perceptual maps by buying region to test if, for example, Asian buyers have different perceptions of intra-Asian differences vs North American and European procurement managers. Global sourcing is no longer of interest only to manufacturers and retailers in the advanced economies. As China, Korea, and others experience increases in labor costs and living standards, companies in those areas will be increasingly looking to reduce their own costs through advanced sourcing strategies. The authors believe that visual representations of alternative sourcing options have great potential to improve the efficiency of cross-disciplinary and multi-company teams that are increasingly responsible for global sourcing strategies. The authors have also demonstrated that managers’ perceptions are biased by regional stereotypes. Thus, managers should be cautious in solely relying on their subjective perceptions in making sourcing location decisions. Finally, this research is only a first step in what we hope will be another approach to advancing the theory and practice of global sourcing and outsourcing decisions.
Notes 1. Perceptual mapping can be done using multiple discriminant analysis, composite vector analysis, or composite ideal point analysis. Composite vector analysis was used in this research because it has the advantage of easily combining perceptual and preference data which discriminant approaches do not, and because the attributes we use in this research are of the “more is better” type. Vector approaches are superior to ideal point approaches for these kinds of attributes as they more clearly differentiate between the various countries/regions we included in the study. 2. A complete table of all means for all regions and attributes is available by request from the authors. 3. The t-test for transportation cost differences between Coastal China and Mexico produced a confidence interval which just barely included 0, as did the t-test for differences between Mexico and Urban India on border clearance.

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4. The two dimensions account for 51.38 percent of the variance in the overall map. This suggests that while these dimensions are useful there are still significant factors that are not accounted for in the analysis. The authors looked at adding a third dimension to the map but chose not to do so because it accounted for only 9.03 percent of the variance. The convention is to typically not include a third dimension unless it accounts for over 10 percent of the variance because it greatly complicates interpreting the analysis. In addition, the analysis provides an indication of the extent to which the estimated ideal vectors are successful in accounting for individual preferences. Respondents should prefer to source products closest to their estimated ideal vectors. The authors also measured the distance between that respondent’s perception of each sources product as a point in the space and the location of his/her estimated ideal vector in the same space. If the preferred product is farther from the ideal vector than the non-preferred product, we score a “miss.” The percentage of order violations ¼ 17.697. When one should expect an error rate of 50 percent due to random chance, the perceptual model provides a pretty significant improvement. References Armstrong, J. and Overton, T. (1977), “Estimating nonresponse bias in mail surveys”, Journal of Marketing Research, Vol. 14 No. 3, pp. 396-402. Arvis, J. et al. (2007), “Connecting to compete: trade logistics in the global economy”, The International Bank for Reconstruction and Development/The World Bank, available at: www.worldbank.org/lpi Bala, V. and Long, N.V. (2004), “International trade and cultural diversity: a model of preference selection”, CESifo Working Papers No. 1242: Category 7, Trade policy, CES, Munich. Blair, I.V. (2002), “The malleability of automatic stereotypes and prejudice”, Personality and Social Psychology Review, Vol. 6 No. 3, pp. 242-61. BLS (2007), “Hourly compensation costs for production workers in manufacturing, 33 countries or areas, 22 manufacturing industries, 1992-2005”, United States Bureau of Labor Statistics, available at: www.bls.gov/fls/home.htm Butta, K.S. and Huq, F. (1992), “The supplier selection problem: a comparison of the total cost of ownership and analytic hierarchy processes”, Supply Chain Management, Vol. 7 Nos 3/4, pp. 126-35. Carter, J.R. and Narasimhan, R. (1996), “A comparison of North American and European future purchasing trends”, International Journal of Purchasing & Materials Management, Vol. 32 No. 2, pp. 12-22. Carter, J.R. et al. (2005), Outsourcing Strategically for Sustainable Competitive Advantage, Research Monograph, Center for Advanced Purchasing Studies (CAPS Research), Tempe, AZ, available at: www.capsresearch.org Chen, Z., Tsui, A. and Farh, J. (2007), “Loyalty to Supervisor Vs. Organizational Commitment: Relationships to Employee Performance in China”, Hong Kong University of Science & Technology Business School Research Paper, available at: ssrn.com/abstract=1007388 Choi, T.Y. and Hartley, J.L. (1996), “An exploration of supplier selection practices across the supply chain”, Journal of Operations Management, Vol. 14 No. 4, pp. 333-43. Crnic, F., Kleeman, U. and Seider, C. (2006), Low Cost Country Sourcing can Benefit a Company’s Bottom Line, IBM Global Business Services, Supply Chain Management, Armonk, NY, available at: www.Ibm.com/bcs/supplychain Czinkota, M.R. and Ronkainen, I.K. (1997), “International business and trade in the next decade: results from a Delphi study”, Journal of International Business Studies, Vol. 28 No. 4, pp. 827-44.

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Sarkis, J. and Talluri, S. (2002), “A model for strategic supplier selection”, The Journal of Supply Chain Management, Vol. 38 No. 1, pp. 18-28. Schmitz, H. and Knorringa, P. (2002), “Learning from global buyers”, The Journal of Development Studies, Vol. 37 No. 2, pp. 177-205. Sharland, A. (2003), “The impact of cycle time on supplier selection and subsequent performance outcomes”, Journal of Supply Chain Management, Vol. 39 No. 3, pp. 4-12. Sitkin, S. and Weingart, L. (1995), “Determinants of risky decision-making behavior: a test of the mediating role of risk perceptions and propensity”, The Academy of Management Journal, Vol. 38 No. 6, pp. 1573-92. Slovic, P., Finucane, M.L., Peters, E. and MacGregor, D.G. (2007), “The affect heuristic”, European Journal of Operational Research, Vol. 177 No. 3, pp. 1333-52. Stalk, G. Jr (2006), “Surviving the China riptide”, Supply Chain Management Review, Vol. 10 No. 1, pp. 18-26. Sterman, J. (1989), “Modeling managerial behavior: misperceptions of feedback in a dynamic decision making experiment”, Management Science, Vol. 35 No. 3, pp. 321-39. Teng, S.G. and Jaramillo, H. (2005), “A model for evaluation and selection of suppliers in global textile and apparel supply chains”, International Journal of Physical Distribution & Logistics Management, Vol. 35 Nos 7/8, pp. 503-23. Timmermans, K. (2005), “The secrets of successful low-cost country sourcing”, Outlook, Accenture.com, No. 2, pp. 62-72. Transparency International (2007), “Corruption perceptions index”, available at: www. transparency.org/policy_research/surveys_indices US Department of Commerce (2007), Quick Stats, US Department of Commerce, Washington, DC. Verma, R. and Pullman, M. (1998), “An analysis of the supplier selection process”, Omega, Vol. 26 No. 6, pp. 739-50. Vonderembse, M.A. and Tracey, M. (1999), “The impact of supplier selection criteria and supplier involvement on manufacturing performance”, Journal of Supply Chain Management, Vol. 35 No. 3, pp. 33-9. Weber, C.A., Current, J.R. and Benton, W.C. (1991), “Vendor selection criteria and methods”, European Journal of Operations Research, No. 50, pp. 2-18. Webster, F.E. Jr and Wind, Y. (1972), Organizational Buying Behaviors, Prentice-Hall, Englewood Cliffs, NJ. White, P.D. (1979), “Attitudes of US purchasing managers towards industrial products manufactured in selected western European nations”, Journal of International Business Studies, No. 10, p. 8190. Wilson, E.J. (1994), “The relative importance of supplier selection criteria: a review and update”, International Journal of Purchasing & Materials Management, Summer, pp. 35-41.

Further reading Hirakubo, N. and Kublin, M. (1998), “The relative importance of supplier selection criteria: the case of electronic components procurement in Japan”, International Journal of Purchasing & Materials Management, Vol. 34 No. 2, pp. 19-27. Narasimhan, R., Talluri, S. and Mahapatra, S. (2006), “Multiproduct, multicriteria model for supplier selection with product life-cycle considerations”, Decision Sciences, Vol. 37 No. 4, p. 577.

Nydick, R.L. and Hill, R.P. (1992), “Using the analytic hierarchy process to structure the supplier selection procedure”, International Journal of Purchasing & Materials Management, Vol. 28 No. 2, p. 31. About the authors Joseph R. Carter is a Professor of Supply Chain Management, the Avnet Professor in the W.P. Carey School of Business and was founding Chair of the Supply Chain Management Department at Arizona State University. Of the 60 refereed journal articles and research monographs either published or under review for Professor Carter, all address issues of relevance within the field of purchasing and supply management. Professor Carter’s research contribution encompasses three major content areas: buyer and supplier communication processes and information exchange systems, international sourcing and supply management issues, and strategic procurement. Joseph R. Carter is the corresponding author and can be contacted at: [email protected] Arnold Maltz is an Associate Professor of Supply Chain Management in the W.P. Carey School of Business at Arizona State University. Professor Maltz has done nationally recognized work on logistics outsourcing and decision analysis models for procurement. His current research focus is on border issues, and supply chains that include less-developed countries. Tingting Yan is a doctoral student in the Department of Supply Chain Management, W.P. Carey School of Business in Arizona State University. Her research interests include: timing issues in multi-stage inventory management, game theory applications in supply chain coordination, integration of financial derivatives in supply contracts, internet and service supply chain, and supply risk management from a real option perspective. Elliot Maltz is a Professor of Marketing in the Atkinson Graduate School of Management at Willamette University, Salem, Oregon. Professor Maltz’ research interest areas include marketing management and strategy with particular emphasis on acquisition and dissemination of market information for strategic decision making.

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