Factors Affecting Performance of Contractors

The Construction, Building and Real Estate Research Conference of the Royal Institution of Chartered Surveyors Held at Dauphine Université, Paris, 2-3 September 2010
ISBN 978-1-84219-619-9 © RICS 12 Great George Street London SW1P 3AD United Kingdom www.rics.org/cobra September 2010

The RICS COBRA Conference is held annually. The aim of COBRA is to provide a platform for the dissemination of original research and new developments within the specific disciplines, sub-disciplines or field of study of:

Management of the construction process
• • • • • • • •

Cost and value management Building technology Legal aspects of construction and procurement Public private partnerships Health and safety Procurement Risk management Project management

The built asset
• • • • • • • • • • • • • •

Property investment theory and practice Indirect property investment Property market forecasting Property pricing and appraisal Law of property, housing and land use planning Urban development Planning and property markets Financial analysis of the property market and property assets The dynamics of residential property markets Global comparative analysis of property markets Building occupation Sustainability and real estate Sustainability and environmental law Building performance

The property industry
• • • • •

Information technology Innovation in education and training Human and organisational aspects of the industry Alternative dispute resolution and conflict management Professional education and training

Peer review process All papers submitted to COBRA were subjected to a double-blind (peer review) refereeing process. Referees were drawn from an expert panel, representing respected academics from the construction and building research community. The conference organisers wish to extend their appreciation to the following members of the panel for their work, which is invaluable to the success of COBRA.

Rifat Akbiyikli Rafid Al Khaddar Ahmed Al Shamma’a Tony Auchterlounie Kwasi Gyau Baffour Awuah Kabir Bala Juerg Bernet John Boon Douw Boshoff Richard Burt Judith Callanan Kate Carter Keith Cattell Antoinette Charles Fiona Cheung Sai On Cheung Samuel Chikafalimani Ifte Choudhury Chris Cloete Alan Coday Michael Coffey Nigel Craig Ayirebi Dansoh Peter Davis Peter Defoe Grace Ding Hemanta Doloi John Dye Peter Edwards Charles Egbu Ola Fagbenle Ben Farrow Peter Fenn Peter Fewings

Sakarya University, Turkey Liverpool John Moores University, UK Liverpool John Moores University, UK University of Bolton, UK University of Wolverhampton, UK Ahmadu Bello University, Nigeria Danube University Krems, Austria UNITEC, New Zealand University of Pretoria, South Africa Auburn University, USA RMIT University, Australia Heriot-Watt University, UK University of Cape Town, South Africa Glasgow Caledonian University, UK Queensland University of Technology, Australia City University of Hong Kong University of Pretoria, South Africa Texas A and M University, USA University of Pretoria, South Africa Anglia Ruskin University, UK Anglia Ruskin University, UK Glasgow Caledonian University, UK KNUST, Ghana Curtin University, Australia Calford Seaden, UK University of Technology Sydney, Australia University of Melbourne, Australia TPS Consult, UK RMIT, Australia University of Salford, UK Covenant University, Nigeria Auburn University, USA University of Manchester, UK University of the West of England, UK

Peter Fisher Chris Fortune Valerie Francis Rod Gameson Abdulkadir Ganah Seung Hon Han Anthony Hatfield Theo Haupt Dries Hauptfleisch Paul Holley Danie Hoffman Keith Hogg Alan Hore Bon-Gang Hwang Joseph Igwe Adi Irfan Javier Irizarry Usman Isah David Jenkins Godfaurd John Keith Jones Dean Kashiwagi Nthatisi Khatleli Mohammed Kishk Andrew Knight Scott Kramer Esra Kurul Richard Laing Terence Lam Veerasak Likhitruangsilp John Littlewood Junshan Liu Champika Liyanage Greg Lloyd S M Lo Mok Ken Loong Martin Loosemore David Manase Donny Mangitung Patrick Manu Tinus Maritz Hendrik Marx Ludwig Martin Wilfred Matipa Steven McCabe Annie McCartney Andrew McCoy Enda McKenna Kathy Michell Roy Morledge

University of Northumbria, UK University of Salford, UK University of Melbourne, Australia University of Wolverhampton, UK University of Central Lancashire, UK Yonsei University, South Korea University of Wolverhampton, UK Cape Peninsula University of Technology, South Africa University of the Free State, South Africa Auburn University, USA University of Pretoria, South Africa University of Northumbria, UK Construction IT Alliance, Ireland National University of Singapore University of Lagos, Nigeria Universiti Kebangsaan Malaysia, Malaysia Georgia Institute of Technology, USA University of Manchester, UK University of Glamorgan, UK University of Central Lancashire, UK University of Greenwich, UK Arizona State University, USA University of Cape Town, South Africa Robert Gordon’s University, UK Nottingham Trent University, UK Auburn University, USA Oxford Brookes University, UK Robert Gordon’s University, UK Anglia Ruskin University, UK Chulalongkorn University, Thailand University of Wales Institute, Cardiff, UK Auburn University, USA University of Central Lancashire, UK University of Ulster, UK City University of Hong Kong Yonsei University, South Korea University of New South Wales, Australia Glasgow Caledonian University, UK Universitas Tadulako, Malaysia University of Wolverhampton, UK University of Pretoria, South Africa University of the Free State. South Africa Cape Peninsula University of Technology, South Africa Liverpool John Moores University, UK Birmingham City University, UK University of Glamorgan, UK Virginia Tech, USA Queen’s University Belfast, UK University of Cape Town, South Africa Nottingham Trent University, UK

Michael Murray Saka Najimu Stanley Njuangang Henry Odeyinka Ayodejo Ojo Michael Oladokun Alfred Olatunji Austin Otegbulu Beliz Ozorhon Obinna Ozumba Robert Pearl Srinath Perera Joanna Poon Keith Potts Elena de la Poza Plaza Matthijs Prins Hendrik Prinsloo Richard Reed Zhaomin Ren Herbert Robinson Kathryn Robson Simon Robson David Root Kathy Roper Steve Rowlinson Paul Royston Paul Ryall Amrit Sagoo Alfredo Serpell Winston Shakantu Yvonne Simpson John Smallwood Heather Smeaton-Webb Bruce Smith Melanie Smith Hedley Smyth John Spillane Suresh Subashini Kenneth Sullivan Joe Tah Derek Thomson Matthew Tucker Chika Udeaja Basie Verster Francois Viruly John Wall Sara Wilkinson Trefor Williams

University of Strathclyde, UK Glasgow Caledonian University, UK University of Central Lancashire, UK University of Ulster, UK Ministry of National Development, Seychelles University of Uyo, Nigeria Newcastle University, Australia Bogazici University, Turkey University of the Witwatersrand, South Africa University of KwaZulu, Natal, South Africa Northumbria University, UK Nottingham Trent University, UK University of Wolverhampton, UK Universidad Politécnica de Valencia, Spain Delft University of Technology, The Netherlands University of Pretoria, South Africa Deakin University, Australia University of Glamorgan, UK London South Bank University, UK RMIT, Australia University of Northumbria, UK University of Cape Town, South Africa Georgia Institute of Technology, USA University of Hong Kong, Hong Kong Nottingham Trent University, UK University of Glamorgan, UK Coventry University, UK Pontificia Universidad Católica de Chile, Chile Nelson Mandela Metropolitan University, South Africa University of Greenwich, UK Nelson Mandela Metropolitan University, South Africa MUJV Ltd. UK Auburn University, USA Leeds Metropolitan University, UK University College London, UK Queen’s University Belfast, UK University of Wolverhampton, UK Arizona State University, USA Oxford Brookes University, UK Heriot-Watt University, UK Liverpool John Moores University, UK Northumbria University, UK University of the Free State, South Africa University of the Witwatersrand, South Africa Waterford Institute of Technology, Ireland Deakin University, Australia University of Glamorgan, UK

Bimbo Windapo Francis Wong Ing Liang Wong Andrew Wright Peter Wyatt Junli Yang Wan Zahari Wan Yusoff George Zillante Benita Zulch Sam Zulu

University of Cape Town, South Africa Hong Kong Polytechnic University Glasgow Caledonian University, UK De Montfort University, UK University of Reading, UK University of Westminster, UK Universiti Tun Hussein Onn Malaysia, Malaysia University of South Australia University of the Free State, South Africa Leeds Metropolitan University, UK

In addition to this, the following specialist panel of peer-review experts assessed papers for the COBRA session arranged by CIB W113 John Adriaanse Julie Adshead Alison Ahearn Rachelle Alterman Deniz Artan Ilter Jane Ball Luke Bennett Michael Brand Penny Brooker Alice Christudason Paul Chynoweth Sai On Cheung Julie Cross Melissa Daigneault Steve Donohoe Ari Ekroos Tilak Ginige Martin Green David Greenwood Asanga Gunawansa Jan-Bertram Hillig Rob Home Peter Kennedy Anthony Lavers Wayne Lord Sarah Lupton Tim McLernon Frits Meijer Jim Mason Brodie McAdam Tinus Maritz London South Bank University, UK University of Salford, UK Imperial College London, UK Technion, Israel Istanbul Technical University, Turkey University of Sheffield, UK Sheffield Hallam University, UK University of New South Wales, Australia University of Wolverhampton, UK National University of Singapore University of Salford, UK City University of Hong Kong University of Salford, UK Texas A&M University, USA University of Plymouth, UK University of Helsinki, Finland Bournemouth University, UK Leeds Metropolitan University, UK Northumbria University, UK National University of Singapore University of Reading, UK Anglia Ruskin University, UK Glasgow Caledonian University, UK Keating Chambers, UK Loughborough University, UK Cardiff University University of Ulster, UK TU Delft, The Netherlands University of the West of England, UK University of Salford, UK University of Pretoria, South Africa

Francis Moor Issaka Ndekugri John Pointing Razani Abdul Rahim Linda Thomas-Mobley Paul Tracey Yvonne Scannell Cathy Sherry Julian Sidoli del Ceno Keren Tweeddale Henk Visscher Peter Ward

University of Salford, UK University of Wolverhampton, UK Kingston University, UK Universiti Technologi, Malaysia Georgia Tech, USA University of Salford, UK Trinity College Dublin, Ireland University of New South Wales, Australia Birmingham City University, UK London South Bank University, UK TU Delft, The Netherlands University of Newcastle, Australia

Factors Affecting Performance of Contractors on Construction Projects in Lagos State, Nigeria
Ajayi,O.M. University of Lagos,Department of building,Akoka-Yaba, Lagos state. [email protected] Ogunsanmi,O.E. University of Lagos,Department of building,Akoka-Yaba, Lagos state. bode-ogunsanmi2004.co.uk Ajayi,K.A. Hadejaz Nigeria Limited. [email protected] Ofili,C.M. University of Lagos,Department of building,Akoka-Yaba, Lagos state. Abstract The study is set out to highlight the factors affecting the performance of contractors on construction projects within Lagos State. This will assist clients in the choice of the right contractors to select for realising their projects. A descriptive research survey was used and simple random sampling technique was adopted for the study. Fifty questionnaires were designed and administered to indigenous main contractors in order to elicit information regarding the study. Forty questionnaires were returned from which one was treated as invalid due to missing responses. From the results obtained, it was found that the most suitable performance yardsticks to ascertain whether a contractor has performed adequately are the quality of work, the delivery of the project on time, the productivity rate of the contractor and project completion within the estimated budget. It was discovered that significant factors affecting performance as categorised into ten groups are site conditions, 1

complexity of project, subcontractors experience, collaboration of project participants, experience of workers, quality control of materials amongst others. Excellent contractor performance would lead to reduced construction cost, improved quality of work and reduction in waste among others. Keywords:Contractors,Performance,Construction, projects, 1.0 Introduction Nigeria has an estimated population of 150M and it is located in the sub-saharan region of Africa.Its land area is 924770km2 ,and it is made up of 36states.The country has a significant role in the socioeconomic and political arena of the African continent(Mansfield,Ugwu and Doran,1994).The construction industry contribute greatly to the gross domestic product.In Nigeria,construction investment accounts for over 60% of the gross fixed capital formation(GFCF) i.e the total national investment(Dlakwa and Culpin,1990).Problems in construction projects in Nigeria therefore hold back planned economic developments.Current construction projects are complex efforts requiring the support of the design and construction profession(Ogunsemi and Jagboro,2006).Therefore,a realistic time for execution of project will reduce the possibility of disputes between state agency and the contractors(Almomani,2000)It also reflect the contractor’s ability to organize and control site operations,to optimally allocate resources and to manage the flow of information to and from the design team and among contractors(Xiao and Proverbs,2002).The correct choice of construction contractor(s) is a critical function of either the client or the client’s consultant\project manager.It usually has a significant impact on the success or failure of a project.Attempting to predict contractor performance with regard to a forthcoming project requires appraisal of current workload and residual resource capacities as well as investigation of performance on recent project(Kuwaraswamy,1996).One of the most difficult decisions taken by the client in the construction industry is selecting the contractor.Every construction project faces adversity

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and uncertainty and an inappropriate contractor increases the chances of delays,cost overrruns,substandard work,disputes or bankruptcy(Elinwa and Joshua,2001).Nigerian contractors are faced with the problems of lack of technical education,managerial skill and finance when compared with their counterparts in the developed countries. The performance of a project will definitely correlate with the performance of a contractor. The evaluation of performance has been a challenge for the construction industry for decades. Several models and procedures have been proposed for the evaluation and measurement of project performance. However, most of these procedures limit their analysis to selected measures such as cost, schedule, or labour productivity (Alarcon, 1994). The increasing competitiveness of the Construction Industry (CI) motivates companies to assess performance and implement efficiency improvement strategies in order to obtain competitive advantage. Therefore, focus is to be directed towards the site constructors which are the contractors. To raise the levels of competitiveness, contractors need to increase the use of performance assessment tools as a means of supporting performance improvement programmes. contractor performance is defined to embrace construction cost, construction time, construction quality and sustainable development, the philosophy being that the achievement of one aspect of performance should not be at the expense of another (Hong and Proverbs, 2003). From the standpoint of Poon (2003), the major indicator of the contractor’s performance is the client’s satisfaction. poor contractor performance, as characterized by poor work quality and low productivity, is common in the industry.Furthermore, other problems associated with poor performance are cost over-runs, rework, late completion, unacceptably high accident rate, insensitivity to environmental considerations, poor work practices and adversarial relationships (Allens, 1994; Henry, 1994; Lobelo, 1996;Alwi, Hampson and Mohammed, 2002). It is against this background that the study seeks to determine the factors affecting the performance of contractors on construction projects. The

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identification of these factors, the causes of poor performance, and a measurement of their severity, would provide useful information that would allow management to act to reduce their negative effect in advance.Therefore,considering the state of project execution in Nigeria and the level of injury inflicted to various parties in the project execution process,it becomes imperative to critically analyse the factors affecting the performance of the contractors.

2.0

Performance Measurement

Measuring performance is a complex problem (Ofori and Chan, 2001as cited in Alwi et al., 2002). This is because every contractor is unique in terms of the manner in which he follows design specifications, method of delivery, administration, and composition of team members. Evaluation of performance has been a challenge for the construction industry for decades. According to Neely (1995), performance measurement is the set of metrics used to quantify both the efficiency and effectiveness of actions. In the manufacturing and construction industries, performance measurement is used as a systematic way of judging project performance by evaluating the inputs, outputs and the final project outcomes. However, very few companies systematically measure their performance in a holistic way. Moreover, the existing systems tend to focus more on product and less on process and design. This can lead to the sub-optimal quality of the performance measurement system, the misjudging or relative performance, and to complacency and the denying of appropriate rewards to the deserving. Performance measurement is the regular collecting and reporting of information about the inputs, efficiency and effectiveness of construction projects. It is used to judge project performances, both in terms of the financial and non-financial aspects and to compare and contrast the performance with others, in order to improve programme efficiency and effectiveness in their organizations (Takim et al., 2003).

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Moreover, according to Steven et al. (1996), measurements are needed to track, forecast, and ultimately control those variables that are important to the success of a project, and this has been agreed by many researchers and practitioners (Sinclair and Zairi, 1995; Mbugua et al., 1999; Love et al., 2000 and Chan, 2001). More specifically, Kelada (1999) suggests that the performance measurements used apply not only to product or service quality and to business performance, but should also be extended to quality management, customer satisfaction, needs, wants and expectations. Performance measurement provides necessary information for process control, and makes it possible to establish challenging and feasible goals. It is also necessary to support the implementation of business strategies. Despite the importance of performance measurement, it has not been widely implemented in construction companies and information on the performance of the construction industry as a whole is also scarce (Dayana et al., 2005).However contractor performance is critical to the success of any construction project which is the determinant of cost,time and quality standard because the contractor convert the design into practical reality(Xiao and

Proverbs,2003).Untimely completion of construction projects has been found to be a major setback in the construction industries in Nigeria(Amu,Adeoye and Faluyi,2005).And according to Odusami and Olusanya(2000) projects executed in Lagos metropolis experienced an average delay of 51% of planned duration for most projects.Construction cost in Nigeria is 40% expensive when compared with Kenya,Brazil(35%) and

Britain(30%).Therefore an improved contractor performance can leads to increased client satisfaction,improvement in reputation and competitiveness in the market(Ogunsemi and Jagboro,2006).

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3.0 Reseach methods To achieve the objective of this study, a structured questionnaire was designed to serve as the instrument for the collection of data; the designed questionnaire was administered on 50 randomly selected indigeous contractors in Lagos State. Out of the 50 questionnaires sent out, only 40 were retrieved representing a response rate of 80% although one of the questionnaire was treated as invalid due to missing response.Data collected were analyzed using Statistical Package for social Sciences (SPSS) to generate the descriptive statistics and the mean deviation were calculated.The mean deviation is a measure of the spread of a distribution from the mean, or average value. If there are n observations with a mean of m, the mean deviation is the sum of the absolute values of the differences of the observation values from m, divided by n. Mean Response Analysis is where the mean item score is determined for each of the variables.The data collected on the identified factors were analysed using relative importance index (i.e. the mean item score). The mean item score (MIS) was computed using the formula:

where: i =response category index = 1, 2, 3, 4, and 5 for nil, low, average, high and very high respectively. Wi = the weight assigned to the ith response = 1, 2, 3, 4, 5 respectively. Xi = frequency of the ith response given as percentage of the total responses for each cause (Odeh and Battaineh, 2002).

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4.0 Results and Analysis 4.1 Background information Most of the professionals are civil engieer(56.4%),Builder(25.6%) and

Architect(2.6%) as shown in table 4.1.Table 4.2 shows the highest eduational qualification with B.sc. rank as the highest(61.5%).Table 4.3 shows that the respondents experience in the construction industry is between 0-5years(56.4%).
Table 4.1: Respondents Profession distribution Respondent's profession Civil Engineer Builder Architect Quantity Surveyor Estate Surveyor Total Quality Control Total Frequency 22 10 1 3 2 38 1 39 Percent (%) 56.4 25.6 2.6 7.7 5.1 97.4 2.6 100

Table 4.2: Respondents Highest Educational Qualification Respondent's highest educational qualification N.D H.N.D. B.Sc M.Sc Total

Frequency Percent (%) 1 2.6 9 23.1 24 61.5 5 12.8 39 100

Table 4.3: Distribution of respondent’s years of experience Respondent's years of experience 0-5 years 6-10 years 11-15years 16-20 years Total Frequency Percent 2 5.1 22 56.4 10 25.6 3 7.7 2 5.1 39 100.0

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4.2 Factors Affecting Performance of Contractors on Site Factors affecting performance of contractors as categorised into ten related factors have been ranked by the respondents as shown in Table 4.4 below which gives the mean item score of the factors as well as their ranking in decreasing level of influence on a contractor’s performance. The three most significant project-characteristic factors are site conditions, complexity of project and its duration. The financial capability of the client, delay in approvals and delay of progress payment to contractors are the three highest ranked client related factors. The three highest ranked subcontractors’s related factors are Sub-contractors commitment to meet cost, time and quality targets, Sub-contractors Experience and Literacy of subcontractors workmen. The most significant project management related factors are Collaboration of project participants, Quality, health and safety program and Technical skill of the project manager. The five most significant consultant related factors affecting project performance are consultant’s commitment to ensure construction work according to specification, consultant cooperation to solve problems, adequacy of design and specifications, design team experience and consultants involvement to monitor the project progress. Also, the five most important resource related factors are experience of workers, skill of workers, supply of material, quality control of material and working capital. The four most important external environmental factors in decreasing order include community issues, weather conditions, economic situation (boom or meltdown) and government policy.
Table 4.4: Ranking of Factors affecting performance Project-Characteristics related factors Site conditions Complexity of project Duration of Project Type & Nature of project Size of project Location of Project Number of floors/Vertical height of the project Constructability of project design MIS 3.82 3.67 3.56 3.51 3.51 3.51 3.44 3.43 Category Ranking 1 2 3 5 5 5 8 9

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Client’s related factors Financial capability of Client Delay in approvals Delay of progress payment to contractors Client's experience whether he is a sophisticated or specialized client. Client's interference during construction Client's erratic changes Client's ability to make decision Client's emphasis on quick construction instead of quality Client's emphasis on low construction cost Client's ability to brief the project objective Size of client's organization Subcontractors related factors Sub-contractors commitment to meet cost, time and quality targets Sub-contractors Experience Literacy of subcontractors workmen Contractors Control over subcontractors works. Timely payment to sub-contractors Sub-contractors leaders working relationship with one another Skill/Training of the Sub-contractors labour force Lingua Franca of subcontractors workmen Project Management related factors Collaboration of project participants Quality, health and safety program Technical skill of the project manager Project manager early and continuous involvement in the project. Organizing skill of the project manager Integration of design and construction process Project manager adaptability to changes in the project plan Budget progress monitoring Implementation of an effective quality assurance program Presence of an Organizational structure Speed of information dissemination Formal dispute resolution process Consultant related factors Consultants commitment to ensure construction work according to specification Consultant cooperation to solve problems Adequacy of design and specifications Design team experience Consultants involvement to monitor the project progress Adequacy of specifications and drawings Delay in production of design documents Changes to Original design during construction 4.26 4.10 4.08 4.05 4.05 3.97 3.90 3.70 1 2 3 4.5 4.5 6 7 8 4.13 4.08 4.05 4.05 3.87 3.81 3.79 3.77 3.70 3.70 3.46 3.15 1 2 3.5 3.5 5 6 7 8 9.5 9.5 11 12 4.09 3.77 3.76 3.70 3.70 3.57 3.51 2.97 1 2 3 4.5 4.5 6 7 8 3.77 3.69 3.67 3.67 3.62 3.59 3.54 3.54 3.36 3.26 2.74 1 2 3.5 3.5 5 6 7.5 7.5 9 10 11

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Variations to work Resource Related Factors Experience of workers Skill of workers Supply of material Quality Control of material Working capital Suitability of equipment Availability of credit facilities Availability of Incentives for workforce Contractual relationship related factors Control mechanism of the project activities Communication system among project participants Overall managerial actions Feedback capabilities between project participants Contract modifications External Environment Factors Community Issues Weather conditions Economic situation (Boom or Meltdown) Government policy Technological advancement of project location Political condition Civil Unrest Physical environment Bureaucracy in government agencies Industrial relations environment Professional ethics of government officials Social environment Cultural beliefs Procurement related factors Conditions of Contract Procurement method Tendering method Contractor related factors Management skill of Site Managers Contractors Experience Size of labour force Construction method adopted Leadership style of workforce Supervision of workmen Planning of site activities Cashflow of the contractor

3.46

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4.28 4.23 4.21 4.21 4.13 4.05 3.97 3.67

1 2 3.5 3.5 5 6 7 8

4.05 3.82 3.74 3.43 3.38

1 2 3 4 5

3.97 3.78 3.66 3.62 3.49 3.21 3.18 3.10 3.08 3.08 3.03 2.92 2.51

1 2 3 4 5 6 7 8 9.5 9.5 11 12 13

3.56 3.33 3.21

1 2 3

4.24 4.18 4.15 3.97 3.95 3.90 3.82 3.79

1 2 3 4 5 6 7 8

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Skill of Mechanical Equipment operators Site Housekeeping Literacy of Workmen Lingua Franca/Vernacular of Workmen/workforce

3.72 3.46 3.44 3.16

9 10 11 12

4.3 Effects of Adequate Contractor’s Performance on the Construction Project Results of respondent’s agreement with the tabulated effects of contractors performance on a construction project is shown in Table 4.5 below. The table shows that the majority of respondents agree to a large extent that (in decreasing order of significance) improved quality work, minimal construction errors and mistakes, absence or minimal accidents on site and reduced construction cost are the four most significant effects of good contractor’s performance with positive response ratings of 91.9%, 87.2%, 82.1% and 78.4% respectively.
Table 4.5: level of agreement of effects of contractor’s performance Effects Reduced Construction Cost Improved quality of work Reduced construction time Absence of defects and need for rectification Absence or minimal accidents on site Absence or reduced need for rework Minimal construction errors and mistakes Reduced client’s complaints Minimal dispute construction team Reduction in Waste among Response Agree Disagree Agree Disagree Agree Disagree Agree Disagree Agree Disagree Agree Disagree Agree Disagree Agree Disagree Agree Disagree Agree Disagree Frequency Percent (%) 29 78.4 8 21.6 34 91.9 3 8.1 25 64.1 14 35.9 24 64.9 13 35.1 32 82.1 7 17.9 29 78.4 8 21.6 34 87.2 5 12.8 25 64.1 14 35.9 24 64.9 13 35.1 30 81.1 7 18.9

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4.4 Causes of poor contractor performance on construction project The significant causes that have a mean item score equal to or above 2.00 in decreasing order of significance are inadequate planning, mismanagement of funds, delay in making decisions and approvals by the owner, affection for the use of low quality materials, poor communication and communication, late deliveries, contractors lack of experience, discrepancies between architectural, structural and mechanical drawings, inadequate and unclear drawings, bad weather conditions and lack of mobilization fee. Causes which were ranked low as insignificant causes of poor performance are size of contractor’s firm, inadequate subcontractors, greed, difficulties in obtaining work permit and diversity of the construction team. This implies that a smaller workforce of the contractor does not necessarily mean that the performance would be adversely affected. Neither does the diversity of the workforce in terms of cultural background, tribe or business objectives tend to result in poor performance of the contractor.

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Table

4.6: Ranking of the causes of poor contractor performance

S/N
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Causes
Inadequate or poor planning Mismanagement of Funds Delay in making decisions and approvals by owner Affection for the use of low quality materials Poor coordination and communication Late deliveries Contractor's lack of experience Discrepancies between Architectural, Structural, Mechanical drawings etc. Inadequate and unclear drawings Bad Weather Conditions Lack of mobilization fee/ Inadequate working capital Changes in the design and scope Late information Low skill level among the workers Poor estimation of quantity of work involved Inadequacy to make Claims and follow to a logical conclusion according to the Conditions of Contract Size of Contractor's firm/workforce Inadequate subcontractors Greed! even though quality is sacrificed Difficulties in obtaining work permit Diversity of the construction team (in terms of tribe, culture, business objectives)

MIS
2.41 2.32 2.27 2.27 2.22 2.18 2.16 2.13 2.11 2.00 2.00 1.97 1.92 1.90 1.83 1.81 1.76 1.74 1.71 1.66 1.32

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5.0 Conclusions To measure contractors performance on construction project the suitable yardsticks are the quality of the work, delivery of project on time, the rate at which the contractor performs the work, Project completion to budget and Degree/Level of Clients Satisfaction. The most significant factors affecting contractor performance under project characteristics are site conditions, complexity of project and duration of project. It can be inferred that the conditions of a site, whether swampy, water-logged, having a steep terrain would affect the performance of the contractor. Also, the technical complexities to be encountered during the construction process and the estimated time for project completion would also have significant effect on contractor’s performance. The three most significant of the client-related factors affecting contractors’ performance are the financial capability of client, delay in approvals and delay of progress payment to contractors. Where interim certificates are not paid on time or the financial capability of the client is not consistent or where the client delays approvals of materials and other items, these could adversely affect contractor’s performance. The three most significant subcontractor related factors affecting contractor performance are sub-contractors commitment to meet cost, time and quality targets, sub-contractors experience and literacy of subcontractors’ workmen. Where the contractor exhibits a lackadaisical attitude towards the work in terms of completing the work within the estimated budget, time and to the required quality, this adversely affects contractor’s performance as he may militate against the overall progress of the project. The three most significant project management related factors are collaboration of project participants, quality, health and safety program and technical skill of the project manager. An effective quality, health and safety program, excellent collaboration of project participants and adequate technical skill of the project manager all would ensure good contractor performance on any

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construction project. Significant contractor related factors are management skill of site managers, contractors experience and size of labour force. An optimum site labour force is required where the labour is adequate to carry out a particular work on site. The experience of the contractor also takes its toll on his performance. Well-experienced contractors would have acquired information about the do’s and dont’s of the construction process and this would therefore reflect in their performance.The major effects of performance of the contractor on construction projects are improved quality of work, minimal construction errors and mistakes, reduction in waste and reduced construction cost.The major causes of contractor’s poor performance are inadequate or poor planning, mismanagement of funds, delay in making decisions and approvals by owner and affection for the use of low quality materials. 6.0 References Alarcon, L.F. (1994). Tools for the Identification and Reduction Waste in Construction Projects. In Alarcon, Luis, (Ed.) Lean Construction, A.A.Balkema, Netherlands 1997. Allens, A.R. (1994). “Quality Management in the Construction Phase of the Traditional Procurement System in South Africa: The Case of the Western Cape”, University of Cape Town in Cape Town,Western Cape, South Africa. Al-Momani A.H. (2000). “Construction Delay: A Quantitative Analysis.” International Journal Of Project Management, 18(1):51-59. Amu,O.O.,Adeoye,O.A.and Faluyi,S.O.(2005).Effects of incidental factors on the completion time of projects in selected Nigeria cities.Journal of Applied Sciences,5(1),144-146. Chan, A. (2001). A Quest for Better Construction Quality in Hong Kong. Construction Paper 131, CIOB Construction Information Quarterly, 3(2): 9-16

Construction Industry Board (1998). Lean Construction. Adopted from Construction Industry Board Web Site: http://www.ciboard.org.uk/lean.

Dayana, B.C., Formoso, C.T., Kagioglou, M. and Alarcon (2005). Performance measurement systems for benchmarking in the construction industry.

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