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VOL 4, NO 6
DECISION MAKER’S PERCEPTIONS ON CONTRACTOR PREQUAIFICATION
CRITERIA
Ajayi, O.M. and Ogunsanmi, O.E.
Department of Building, University of Lagos, Akoka, Lagos, Nigeria.
Abstract
The process of selecting contractors for a proposed project is a major decision which may
influence the progress and success of any construction project. Selecting an inappropriate
contractor for a project could therefore lead to project behind schedule, price changes and
substandard work. The decision make by the client or his representative directly or indirectly
affect the success or otherwise of a project outcome. A descriptive research was used and the
population consists of client’s organization and consulting firms, it comprises of Quantity
Surveyors, Builders and Engineers. A random sampling method is used and a total of 50
questionnaires were distributed, but 17 were received from public client’s organization and 25
from consulting firms. Data collected were analyzed using descriptive and inferential statistic.
From the pilot study carried out, the most prominent prequalification criteria were identified. In
conclusion, clients and consulting firms will be aware of early warning sign of the contractors
who will not be able to perform.
Keywords: Contractor, Criteria, Decision Maker, Perception, Prequalification
1.0 Introduction
Decision making is a process of gathering information from which a decision is taken. It has
becomes mathematical science today (Figuera et al, 2005).It formalizes once thinking so that
the process of taking the decision is transparent. Decision making involves many criteria and
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subcriteria used to rank the alternatives of a decision and so decision maker’s have to be
objective whenever they are taking decision especially on selection of contractors (Saaty,
2008).Biases occur in all stages of decision process. They come in form of information
perception, information processing and in making selection from options. Decision making is
governed by certain heuristics﴾reasoning patterns﴿ and decision frames from which arise
deviations from rational and optimal decisions﴾Cardenas,Halman,Al-
Jibouri,2009.﴿Contractors are those involved in the construction stage of construction
projects and so any decision taken about their selection becomes cushion since it affect the
performance of the project. The process of selecting contractors for a proposed project is a
major decision which may influence the progress and success of any construction project.
Selecting an inappropriate contractor for a project could therefore lead to project behind
schedule, price changes and substandard work﴾.Banaitiene and Banaitis,2006﴿.It is due to
inappropriate criteria been selected when evaluating qualification of contractor, inappropriate
significance attributed to the criteria and inappropriate methodology applied for the
contractor evaluation and selection as identified by Banaitiene and Banaitis﴾2006﴿ in their
study on Lithuania selection and evaluation process. The complexity of contractor selection
is attributed to its uncertainty nature. It is due to fuzziness associated with contractor
performance, experience, prequalification criteria and qualitative judgment﴾Lam et al, 2001﴿.
The decision make by the client or his representative directly or indirectly affect the success
or otherwise of a project outcome (Holt, 1996). Thus, a wrong approach in selection could
lead to project failure. The client is faced with choosing between using competitive bidding
and negotiation to select contractor (Waara, 2006). Most public client organizations adopt a
selective approach for inviting tenderer for construction projects. This help to prevent
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contractor default and associated overhead costs of contractors. It enables the clients to assess
the liability, competency and capability of potential contractors to satisfactorily carry out the
contract. It also minimizes the potential risks involved in the project (Ng and Skitmore,
1999). Odeyinka and Yusuf (1997) opine wrong tendering practice is a major contribution to
inefficiency in Nigeria construction industry. However some contractor selection methods
currently in existence are criticized as incomplete and biased and lacking consideration in
terms of contractor’s performance (Fong and Choi, 2000). In addition, there have been steady
increase in the range of methods used for procurement of construction works in the last two
decades for instance in Nigeria we have “Due process which is meant for transparency and
accountability, but yet there have not be improvement in the success rate of construction
projects. Project management is faced with many problems and so a better means of
managing project delivery is therefore necessary for construction industry to continue to
survive. Therefore the method of ensuring that a contractor is able to execute the assigned
project in accordance to client’s objectives (time, cost and quality standard) is to assess the
contractor’s capabilities at the prequalification and tender evaluation stages (Hatush and
Skitmore, 1997).
Objectives of the study
1. To identify the prominent criteria used for contractor selection in client organization and
consulting firms at prequalification stage.
2. To find out the level importance of identified criteria for contractor selection at
prequalification.
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Hypotheses of the study
1.The most dominant criteria in clients’ organization and consulting firms at prequalification
stage are not financial criteria, experience, managerial capability, health and safety and
contractors reputation and image.
2. There is no significant difference between clients’ organization and consulting firms on the
level of importance of the prequalification criteria and tender evaluation.
2.0 Review of literature
From the design stage of construction project, the client is faced with numerous decisions which
may result to the success or failure of the entire project (Russell et al, 1992). The task of
selecting the appropriate bidders for a particular project is one of such decision. It is one of the
most challenging tasks performed by an owner or his representative. (Holt, 1996). Every
construction project faces adversity and uncertainty which must be overcome. No matter how
meticulous the development of the contract, poor selection of the contractor(s) to execute the
work will surely magnify the problems encountered on the project. In order to overcome these
problems, a competent contractor who will be able to complete the project within cost, time and
quality is required. It is achieved through prequalifying contractor prior to the bidding process
which is the first stage of selection and then through evaluation of tenders. Contractor
prequalification is a process of screening construction contractors by project owners or their
representatives according to a determined set of criteria deemed necessary for successful project
performance, in order to determine the contractor’s competence or ability to participate in the
project bid. It implies that there must be a set of principles (criteria) laid down upon which the
standard of acceptance and performance are to be measured even though such criteria varies in
emphasis according to the characteristics of the project﴾Moore,1985;Odusami,1998;Ng and
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Skitmore,1999;Ng,Skitmore and Smith,1999; Lam,Hu and Ng,2005﴿. Contractors generally
undergo a screening process before the project can be given to them. It enables unqualified
contractors to be eliminated at the early stage of the project and those who meet the required
criteria are qualified for the next stage. Contractors been classified into categories according to
factors such as experience, liquidity and patrimony. Then the prequalified contractors present
their offers. These offers are evaluated under an economic criterion and in some projects, a
technical criterion. After evaluation, the contract is awarded according to the final score (Alarcon
and Mourgues, 2000). According to Lam, Hu, Ng, Skitmore and Cheung (2001) contractor’s
prequalification can be regarded as a complicated two – group non – linear classification
problem. It involves a variety of subjective and certain information extracted from various
parties such as contractors, prequalifies and project teams. Non-linearity, uncertainty, and
subjectivity are the three predominant characteristics of contractor prequalification. This makes
the process more of an art than a scientific evaluation. Efforts have been made to cope with the
non-linearity existing between contractor attributes and the corresponding prequalification
decisions made by the owner (client) this efforts include the development of a range of
nonlinearity models such as programmed evaluation review technique (PERT) (Hatush and
Skitmore, 1997), the artificial neural network model (Lam et al, 2001, 2002; Khorsrowshah,
1999), the analytical hierarchy process (AHP) (Fong and Choi,2000; Al-Harbi, 2001) and the
multi – attribute utility model (Diekmann,1981). In an attempt to reduce the subjectivity and
uncertainty involved in the process of contractor prequalification, a number of techniques have
been investigated, involving varying degree of complexity. Nguyen (1985) in Lameta (2005)
applied fuzzy set theory to the evaluation and selection of bidders based on cost, the presentation
of bid information and past experience. While Russell et al (1990) develop a prototype
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knowledge based expert system that aids construction owners in performing contractor
prequalification. It provides an automated contractor evaluation process through which rational
and consistent prequalification decisions could be made. Ng (1996) in Lam et al (2005)
developed a case – based reasoning system and found that it could capture and reuse
experimental knowledge pertinent to contractor prequalification decisions, and thus help decision
makers to produce more reliable and expeditious decisions for contractor prequalification.
According to Khosrowshahi(1999) the ability to optimize the short listing from a large number of
potential contractors is as important to the final selection of the right bidder. This is because the
quality of the final bidder is as good as those shortlisted.Holt (1998) developed artificial
intelligence(AI).It helps to provide assistance with decisions relating to contractors
prequalification. It is suitable where the problem cannot be expressed totally in algorithmic form.
The most appropriate artificial intelligence (AI) is the artificial neural networks (ANN)
developed by Khosrowshahi (1999). It aids the public client to make rational decision on
contractors prequalification. The screening of contractors is usually based on a set of
prequalification criteria. These prequalification criteria are financial, experience, managerial
capability, health and safety and contractors’ reputation and image.
3.0 Research Methods
For this study the possible observations who made up the population for this study are clients and
consultants. For the purpose of this study public clients are the focus, since most of the projects
carried out by the public clients are owned by the government where accountability is required
and so such projects must go through “due process” and they are always in competition.
The consultants are the construction professionals involve in construction projects. They include
architects, quantity surveyors, engineers and builders. The list of the practicing professionals for
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the study was obtained from their respective professional bodies and they are randomly selected
which implies they all have equal chance of been selected. A descriptive research survey is used
for the study. Data for the research are generated using opinion-based questionnaire survey,
which will serve as the primary data. A closed ended questionnaire design is used for this study
because it helps in obtaining quantitative data which could be used to test the study hypotheses.
The tool for the analyses of the data collected depends on the type of data, the nature of analysis
and the hypotheses to be tested. Descriptive statistical tools such as frequency distribution
percentages and mean were used in analyzing the descriptive data of the respondents’ profile.
Ranking was based on the use of mean to test the level of importance of prequalification. T-test
and analysis of variance was used to test the difference between clients’ organization and
consulting firms.
4.0 Results and Discussions
The analysis of the data collected from the questionnaires administered and the checklist are
presented as follows.
General Information about Respondents.
Table 1 shows the demographic variable of respondents from client’s and consultant
organisation.From both client and consulting organisation,majority of the respondent are
Quantity surveyors﴾70.6%,96%﴿.It is followed by Architect﴾5.9 %﴿,civil Engineer﴾5.9% ﴿and
Builder﴾5.9%﴿ under client organisation.While under consulting organization there were no
respondents from Architecture, Civil Engineering and Building.47.1% of the respondents had
spend 11-20years in the construction industry in the client organisation and 41.7% in the
consulting organisation.It is follow by 23.5% of respondents have spend less than 10years and
21-30years respectively under client organisation.For consultants organisation,29.2% have spend
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less than 10years and 12.5% have spend 12.5%.Respondents that have spend more than 30years
for both client and consultant organisation are 5.9% and 16.6% respectively. The level of
experience of these respondents shows that the data collected are reliable. The highest academic
qualification of respondents for both client and consulting organization is M.Sc.﴾50%, 37.5%﴿.It
shows that all the respondents are knowledgeable and competent to provide the information
required for this study. The highest total value of project executed by client’s organisation is
29.4% of worth 101-500million and 501-1billion naira. It is follow by a project value of over
1billion of 23.5%.For consultant organisation, the highest total value of project executed is
52.2% of worth over 1billion naira. It is follow by project of worth 501-1billion naira﴾30.2%﴿.
Table 4.1 Background Information
Background clients’ consultant
Information organization organization
Frequency % frequency %
Professional Discipline
Architecture 1 5.9 - -
Civil engineering 1 5.9 - -
Building 1 5.9 - -
Quantity surveying 12 70.6 24 96
others 2 11.8 1 4
Total 17 100 25 100
Years in construction industry
Less than 10years 4 23.5 7 29.2
11-20years 8 47.1 10 41.7
21-30years 4 23.5 3 12.5
More than 30years 1 5.9 4 16.6
Total 17 100 24 100
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Table 4.1 continued.: Background Information
Background clients’ consultant
Information organization organization
Frequency % frequency %
Highest Academic Qualification
HND 2 12.5 7 29.2
B.SC 4 25 6 25
M.SC 8 50 9 37.5
MBA - - 2 8.3
PGD 2 12.5 - -
Total 16 100 24 100
Total value of project executed﴾#﴿
51-100million 3 17.6 - -
101-500million 5 29.4 4 17.4
501-1billion 5 29.4 7 30.4
Over 1billion 4 23.5 12 52.2
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Frequency of used prequalification criteria
From table 4.2 the frequently used prequalification criteria are
Table 4.2 Level of frequency of used and not used prequalification criteria by consulting
firms respondents
Consultant prequalification criteria frequency used (%) frequency not used (%)
A1. Financial criteria
Current fixed asset 18(78) 5(22)
Liquidity 13(57) 10(43)
Annual turnover 17(74) 6(26)
A2 Credit rating
Subcontractors 17(74) 6(26)
Supplier 12(57) 9(43)
A3 Banking arrangement and bonuses
Short term borrowing 11(48) 12(52)
Long term borrowing 9(41) 13(59)
Medium term borrowing 9(41) 13(59)
Bonus 6(30) 14(70)
A4 Financial status
Balance sheet statement 19(83) 4(17)
Income statement 17(74) 6(26)
B Technical Ability
B1 Experience criteria
Type of past projects completed 24(100) -
Size of past projects completed 24(100) -
National or local catchments 16(70) 7(30)
Level of technology 18(78) 5(22)
Technical skills 23(100) -
B2 Personal
Availability of supervisors 17(71) 7(29)
Availability of skilled craftsmen 18(82) 4(18)
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Skills including professional 23(100) -
B3 Plant and equipment
Availability of owned construction 23(100) -
B4 Ability
Ability to handle the project 24(100) -
Ability to perform on site 23(100) -
Ability to control and organize contract 23(100) -
Ability to efficiently integrate labour resources 21(91) 2(9)
Ability to meet target dates 21(91) 2(9)
C.Managerial capability
C1 Past performance and quality of work
Past performance 24(100) -
Quality control programme 24(100) -
Possession of quality assurance certificate 14(61) 9(39)
Quality of workmanship 22(92) 2(8)
Confidence in design and flexibility 14(64) 8(36)
D. Health and Safety
Experience in noise control 11(50) 11(50)
Accident book 10(48) 11(52)
Level of adherence to health and safety regulation 23(100) -
Provision of health and safety regulation 20(83) 4(17)
Safety record available 18(82) 4(18)
Company safety policy 20(87) 3(13)
E.Contractors’ reputation and image
Past and present experience 19(83) 4(17)
Financial penalties 21(100) -
Litigation tendency 19(87) 3(13)
E2.Length of time in business
Amount of projects 22(100) -
Capacity of work handled 23(100) -
Permanent place of residence 12(55) 9(45)
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Table 5.17 level of frequency of used and not used prequalification criteria by clients’
organisation respondents
Clients’ prequalification criteria frequency used (%) frequency not used (%)
A1. Financial criteria
Current fixed asset 13(87) 2(13)
Liquidity 13(87) 2(13)
Annual turnover 13(77) 4(23)
A2 Credit rating
Subcontractors 9(64.3) 5(35.7)
Supplier 8(53.3) 7(46.7)
A3 Banking arrangement and bonuses
Short term borrowing 8(40) 9(60)
Long term borrowing 3(20) 12(80)
Medium term borrowing 5(35.7) 9(64.3)
Bonus 1(9) 10(91)
A4 Financial status
Balance sheet statement 9(60) 6(40)
Income statement 9(64.3) 5(35.7)
B Technical Ability
B1 Experience criteria
Type of past projects completed 17(100) -
Size of past projects completed 16(100) -
National or local catchments 10(58.8) 7(41.2)
Level of technology 17(100) -
Technical skills 17(100) -
B2 Personal
Availability of supervisors 15(88.2) 2(11.8)
Availability of skilled craftsmen 14(100) -
Skills including professional technical expertise 16(100) -
B3 Plant and equipment
Availability of owned construction equipment
For quality assurance 16(94.1) 1(5.9)
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B4 Ability
Ability to handle the project 17(100) -
Ability to perform on site 15(93.8) 1(6.2)
Ability to control and organize contract 15(93.8) 1(6.2)
Ability to efficiently integrate labour resources 15(93.8) 1(6.2)
Ability to meet target dates 15(100) -
C.Managerial capability
C1 Past performance and quality of work
Past performance 15(100) -
Quality control programmes and quality of
Works on past project 17(100) -
Possession of quality assurance certificate 11(68.8) 5(31.2)
Quality of workmanship 17(100) -
Confidence in design and flexibility in
Accommodating design input by client 10(62.5) 6(37.5)
D. Health and Safety
Experience in noise control 5(33.3) 10(66.7)
Accident book 5(33.3) 10(66.7)
Level of adherence to health and safety regulation 14(87.5) 2(12.5)
Provision of health and safety regulation 15(88.2) 2(11.8)
Safety record available 9(60) 6(40)
Company safety policy 14(87.5) 2(12.5)
E.Contractors’ reputation and image
Past and present experience in regard to legal claim 8(53.3) 7(46.7)
Financial penalties previously
Levied in respect 8(53.3) 7(46. 7)
Litigation tendency 9(69.2) 4(30.8)
E2.Length of time in business
Amount of projects handled in the past 5years 15(93.8) 1(6.2)
Capacity of work handled presently 17(100) -
Permanent place of residence 10(71.4) 4(28.6)
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Table 5.18 level of importance of prequalification criteria of clients’ organization and
consulting firms
Prequalification consulting firms clients’ organization importance overall
criteria Importance index rank importance index rank index ranking
Ability to handle the project 0.928 1 0.96 1 4.71 1
Type of past projects 0.92 2 0.92 6 4.60 3
Skills including professional 0.917 3 0.86 15 4.37 8
Past performance 0.912 4 0.94 4 4.61 2
Technical skills 0.904 5 0.95 2 4.50 4
Ability to perform on site 0.904 5 0.94 4 4.44 6
Size of past project
Completed 0.896 7 0.88 13 4.45 5
Complexity of work
executed 0.883 8 0.88 13 4.29 11
Ability to control and organize
contract 0.883 8 0.90 9 4.34 9
Ability to efficiently
integrate 0.87 10 0.83 16 4.15 17
Ability to meet target dates 0.87 10 0.95 2 4.39 7
Quality of workmanship 0.87 10 0.91 7 4.32 10
Availability of skilled
Craftsmen 0.858 12 0.89 11 4.24 13
Quality control programme 0.85 13 0.90 9 4.24 13
Availability of owned
construction 0.843 14 0.88 13 4.20 15
Level of technology 0.842 15 0.91 7 4.24 13
Amount of projects handled 0.842 15 0.88 13 4.17 16
Availability of supervisors 0.84 17 0.88 13 4.29 12
Current fixed asset 0.792 18 0.71 20 3.71 18
Company safety policy 0.775 19 0.77 19 3.68 19
Liquidity 0.73 20 0.8 18 3.59 22
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Annual turnover 0.725 21 0.71 23 3.50 24
Experience in noise control 0.717 22 0.60 33 2.79 36
Possession of quality
Assurance 0.717 22 0.81 17 3.68 19
Level of adherence to health 0.712 24 0.73 22 3.60 21
Provision of health and safety
regulation 0.692 25 0.69 29 3.37 26
Confidence in design 0.692 25 0.76 20 3.51 23
Safety record available 0.683 27 0.61 32 3.17 30
Past and present experience 0.648 28 0.68 28 3.31 27
Litigation tendency 0.643 29 0.70 25 3.15 32
Balance sheet statement 0.642 30 0.66 29 3.17 30
National or local catchments 0.617 31 0.69 26 3.31 27
Subcontractors 0.616 32 0.63 30 3.10 33
Accident book 0.611 33 0.54 35 2.43 40
Permanent place of residence 0.609 34 0.61 31 2.90 35
Medium term borrowing 0.591 35 0.50 37 2.59 38
Supplier 0.576 36 0.60 33 2.93 34
Long term borrowing 0.564 37 0.53 36 2.54 39
Short term borrowing 0.522 38 0.63 30 2.68 37
Income statement 0.525 39 0.71 23 3.40 25
Bonus 0.5 40 0.43 38 1.92 41
Capacity of work handled - - 0.89 11 4.27 13
Financial penalties - - 0.63 30 3.25 29
Hypothesis
5.2.20 Perception of clients’ organization, consulting firms and contracting organization on
prequalification and tender evaluation for contractors’ selection
Table 5.28 shows the result of the perception of the respondents of clients’ organization,
consulting firms and contracting organization. Analysis of variance was used to show their
perception. It was realized that Ftab was greater than Fcal, thus there is a significant between their
perceptions and so the alternate hypothesis (H1) is accepted.
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Table 5.27 Descriptive data results of level of importance of prequalification criteria of
clients’ organization, consulting firms and contracting organization
Respondents N mean standard deviation standard error minimum maximum
Contractor 23 172.83 21.27 4.43 132.00 213.00
Consultant 22 153.46 28.14 6.00 54.00 193.00
Client 13 152.31 27.58 7.65 76.00 181.00
Total 58 160.88 26.87 3.53 54.00 213.00
Table 5.28 Anova result of level of importance of prequalification criteria of clients’
organization, consulting firms and contracting organization
Sum of mean
Square DF squares Fcal Ftab sig. pvalue decision
Between
Groups 5450.627 2 2725.314 41.98 724.98 0.02 0.00 HI accepted
Within
Groups 35703.528 55 649.155
Total 41154.155 57
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References
Banaitiene,N.and Banaitis,A.﴾2006﴿.Analysis of criteria for contractors’ qualification
evaluation.Technological and Economic Development of Economy,12﴾4﴿,276-282.
Figuera, J. Greco, S. and Ehrogott, M. (2005).Multiple criteria analysis. State of the Art surveys.
New York, Springer.
Fong, P.S. and Choi, S.K. (2000).Final contractor selection using analytical hierarchy process.
Construction management and economics, 18,547-557.
Hatush, Z. and Skitmore, M. (1997).Assessment and evaluation of contractor data against client
goals using PERT approach. Construction management and economics, 15,327-340.
Holt, G.D. (1998).Which contractor selection methodology? International journal of project
management, 16(3), 153-164.
Khosrowshahi,F.(2001).Neural Network Model for contractors’ prequalification for local
authority projects. Building and Environment, 6(3), 315-328.
Lam, K.C., Hu, T.S., Ng, S.T., Skitmore, M. and Cheung, S.O.﴾2001﴿.A fuzzy neutral network
approach for contractor prequalification. Construction management and economics,19﴾2﴿175-
188.
Ng, S.T., Skitmore, R.M. and Smith, N.J.﴾1999﴿.Decision-makers’ perceptions in the formulation
of prequalification criteria. Engineering Construction and ArchitecturalManagement,6﴾2﴿155-
165.
Odusami, K.T. (2001).Criteria for measuring project performance by construction professionals
in the Nigerian construction industry. Journal of financial management of property and
construction, 8(1), 39-47.
ijcrb.webs.com
INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS
COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 191
OCTOBER 2012
VOL 4, NO 6
Saaty, T.L. (2008).Decision making with the analytical hierarchy process. International journal
services sciences, 1(1), 83-98.
References
Aibinu, A.A. and Jagboro, G.O. (2002).The effects of construction delays on project delivery in
Nigerian construction industry. International journal of project management, 20(8), 593-599.
Ajayi, O.M., Ogunsanmi, O.E., Ajayi, K.A. and Ofili, C.M. (2010).Factors affecting r
performance of contractors on construction projects in Lagos state,Nigeria. The international
construction research conference of the Royal Institution of chartered surveyors held at Dauphine
Universite, Paris,2nd
-3th
September, 2010,1-25.
Aje, I.O.﴾2008﴿.Contractor prequalification and award criteria as determinant of construction
project performance. In Lagos and Abuja, Nigeria.Unpublished Ph.D thesis, in Federal
University of Technology, Akure, Nigeria.
Alarcon, L.F. and Mourgues, C. (2002).Performance modeling for contractor selection. Journal
of management in engineering, 52-60.
AI-Tabtabai,H.M. and Thomas,V.P.(2004).Negotiation and resolution of conflict using AHP:an
application of project management. Engineering construction and Architectural management,
11(2), 90-100.
Amu,O.O.,Adeoye,O.A. and Faluyi,S.O.(2005).Effects of incidence factors on the completion
time of projects in selected Nigeria cities.Journal of Applied Sciences,5(1),144-146.
Anagnostopoulos,K.P. and Vavatsikos,A.P.(2006).An AHP Model for Construction Contractor
Prequalification.Operational Research:An international Journal,6(3),33-346.
Aniekwu,A.N. and Osedeme,W.A.(2002).Interim project financing in the Nigerian construction
industry.Journal of civil engineering,JKUAT,8,pp 47-59.
ijcrb.webs.com
INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS
COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 192
OCTOBER 2012
VOL 4, NO 6
Ayeni, J.O. (1997).Principle of tendering and estimating. Builder’s magazine limited, Lagos.
Bee-Hua, C. (2000).Evaluating the performance of combining neural networks and genetic
algorithms to forecast construction demand: the case of the Singapore residential sector.
Construction management and economics, 18(2), 209-217.
Beynon, M., Curry, B. and Morgan,P.(2000).The Dempster-Shafer theory of evidence: an
alternative approach to multicriteria decision modelling.OMEGA-Internation Journal of
Management Science,28,37-50.
Bubshit, A. and Al-Gobali, K.H. (1996).Contractor prequalification in Saudi Arabia. Journal of
management in Engineering, 12(2), 50-54.
Cheung, S., Lam, T., Leung, M. and Wan, Y. (2004).An analytical hierarchy process based
procurement selection method. Construction management and Economics, 24(6), 588-604.
Cheung, S.O., Wong, P.S.P., Fung, A.Y.S.and Coffey, W.V. (2008).Examing the use of bid
information in predicting the contractor’s performance. Journal of Financial Management of
Property and Construction, 13(2) 111-122.
Dada, M.O. (2004).Teambuilding procurement method, selection and project performance in
some states in Nigeria. Unpublished Ph.D.thesis in University of Lagos, Lagos state.
Darvish,M.,Yasaei,M. and Saeedi,A.(2009).Application of the graph theory and matrix methods
to contractor ranking.International journal of project management,27,610-619.
Davey, M. and Olson, D.L. (1997).Multi-attribute utility methods in group decision making: past
applications and potential for inclusion in GDSS.Omega, 25(6), 691-706.
Dey, P.K. (2004).Analytic hierarchy process helps evaluate project in Indian oil pipelines
industry. International journal of operations and production management, 24(6), 588-604.
ijcrb.webs.com
INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS
COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 193
OCTOBER 2012
VOL 4, NO 6
Doloi,H.(2009).Analysis of pre-qualification criteria in contractor selection and their impacts on
project success. Construction Management and Economics, 27(12) 1245-1263.
Drew, D.S., Ho, L.C.Y. and Skitmore, M. (2001).Analysis of consultant’s competitiveness in
two-envelope fee tendering. Construction management and economics, 19(5), 503-510.
Elinwa,A.U.,Joshua,M.(2001).Time-overrun factors in Nigeria construction industry.Journal of
construction Engineering and Management,127(5)419-425.
El-Sawalhi, N., Eaton, D. and Rustom, R. (2007).Forecasting contractor performance using a
neutral network and genetic algorithm in a pre-qualification model. Construction innovation,
8(4), 280-298.
Fong, P.S. and Choi, S.K. (2000).Final contractor selection using analytical hierarchy process.
Construction management and economics, 18,547-557.
Forman,E.H. and Selly, M.A.(2002).Decision by objectives. World scientific publications.
Gilleard, J.D. and Yat-Lung, P.W. (2004).Benching facility management: applying analytic
hierarchy process.Facilities, 22(1/2), 19-25.
Graham, G. and Hardaker, G. (2001).Contractor evaluation in the Aerospace industry using the
evidential reasoning approach. Journal of research in marketing and entrepreneurship, 3(3),
162-173.
Hatush, Z. and Skitmore, M. (1997).Assessment and evaluation of contractor data against client
goals using PERT approach. Construction management and economics, 15,327-340.
Hatush, Z. and Skitmore, M. (1998).Contractor selection using multicriteria utility theory: an
additive model. Building and Environment, 33(2-3), 105-115.
ijcrb.webs.com
INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS
COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 194
OCTOBER 2012
VOL 4, NO 6
Holt, G.D., Olomolaiye, P.O. and Harris, F.C. (1994).Factors influencing U.K. construction
clients’ choice of contractor. Building and Environment, 29(2), 241-248.
Holt, G.D., Olomolaiye, P.O. and Harris, F.C. (1994).Applying multi-attribute analysis to
contractor selection decisions. European journal of purchasing and supply management, 1(3),
139-148.
Holt, G.D., Olomolaiye, P.O. and Harris, F.C. (1995).A review of contractor selection practice in
the U.K. construction industry. Building and Environment, 30(4), 553-561.
Holt, G.D. (1996) Applying cluster analysis to construction contractor classification. Building
and Environment, 11(6), 557-567.
Holt, G.D. (1998).Which contractor selection methodology? International journal of project
management, 16(3), 153-164.
Jennings, P. and Holt, G. (1998).Prequalification and Multi-criteria selection: a measure of
contractors’ opinion. Construction management and economics, 16,651-660.
Kaming,P.F., Olomolaiye,P.O., Holt,G.D. and Harris,F.C.(1997).Factors influencing
construction time and cost overruns on high-rise projects in Indonesia. Construction
Management and Economics, 15, 83-94.
Kashiwagi,D. and Byfield,R.E.(2002).State of Utah performance information procurement
system tests. Journal of Construction Engineering and Management, 128 (4) 338-347.
Khosrowshahi,F.(2001).Neural Network Model for contractors’ prequalification for local
authority projects. Building and Environment, 6(3), 315-328.
Koushi, P.A., Al-Rashidi, K. and Kartam, N. (2005).Delays and cost increases in the
construction of private residential projects in Kuwait. Construction management and Economics,
23,285-294.
ijcrb.webs.com
INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS
COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 195
OCTOBER 2012
VOL 4, NO 6
Kumaraswamy, M.M. (1996).Contractor evaluation selection: a Hong Kong perspective.
Building and Environment, 31(3), 273-277.
Kumaraswamy, M.M. and Walker, D.H.T.(1999).Multiple performance criteria for evaluating
construction contractors, procurement system-A guide to best practice in construction.London:E
and FN spon.
Kuprenas, J.A. and Nasi, E.B. (2007).Cost performance comparison of two public sector project.
Procurement Techniques. Journal of management in engineering, 23(3), 114-120.
Lai, K.K., Liu, S.L. and Wang, S.Y. (2004).A method used for evaluating bids in the Chinese
construction industry. International journal of project management, 32,193-201.
Lam, K.C., Ng, S.T., Hu, T., Skitmore, R.M.and Cheung, S.O. (2000).Decision support system
for contractor pre-qualification artificial neural network model. Engineering construction and
architectural management, 7(3), 251-266.
Lam, K.C., Hu, T.S. and NG, S.T. (2005).Using the principal component analysis method as a
tool in contractor prequalification. Construction management and economics, 23,673-681.
Lin,C-T and Chen,Y-T(2004).Bid/no-bid decision-making-a fuzzy linguistic approach.
International Journal of project Management,22,585-593.
Ling, F.Y.Y. (2004).Key determinants of performance of design-bid-build projects in Singapore.
Building Research and Information, 32(2),128-139.
Mahdi, I.M., Riley, M.J., Fereig, S.M. and Alex, A.P. (2002).A multi-criteria approach to
contractor selection. Engineering construction and Architectural management, 9(1), 29-37.
ijcrb.webs.com
INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS
COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 196
OCTOBER 2012
VOL 4, NO 6
Mangitung, D.M. and Emsley, M.W. (2002).Decision criteria for periodic prequalification in the
UK construction industry. Proceedings of the RICS foundation construction and building
research conference, Nottingham Trent University,5th
-6th
sept.,1-13.
Mangitung,D.M.(2004).Typical contractor prequalification characteristics of public procurement
practices in Indonesia. The international construction research conference of the Royal
Institution of chartered surveyors held at Headingley cricket clud,Leeds Metropolitan
University,Uk.7th
-8th
September,2004,1-19.
Manoharan,R.A/L.(2005).Subcontractor selection method using Analytical Hierarchy
Process.Unpublished M.Sc.(construction management) dissertation faculty of civil
Engineering,Universiti of Teknologi,Malaysia.
Marzouk, M.(2008).A Superiority and Inferiority ranking model for contractor selection.
Construction innovation: information, process, management, 8(4), 250-268.
McCabe, B., Tran, V. and Ramani, J. (2005).Construction prequalification using data
envelopments analysis. Canadian journal of civil engineering, 32,183-193.
McCarthy, J.L. (1973).The Nigerian contractor. An unpolished lecture delivered to the
Engineering Society of Ahmadu Bello University Zaria in March, 40-45.
Meland,O.H.,Robertsen,K. and Hannas,G.(2011).Selection criteria and tender evaluation:The
Equivalent Tender Price Model(ETPM).Management and innovation for sustainable built
environment.20th
-23rd
June,2011,Amsterdam,The Nertherlands.
Min,H.(1994).International supplier selection: A multi-attribute utility approach. International
journal of physical distribution and logistics management, 24(5),24-33
Nabeel, A.N. (2011).Development of multi-criteria decision analysis models for bidding and
contractor selection. http://researchrepository.napier.ac.uk/id/eprint3746
ijcrb.webs.com
INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS
COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 197
OCTOBER 2012
VOL 4, NO 6
Nassar,K.(2004).Defining contractor performance levels.The international construction research
conference of the Royal Institution of chartered surveyors held at Headingley cricket clud,Leeds
Metropolitan University,Uk.7th
-8th
September,2004,1-9.
Newcombe, R., Langford, D. and Fellows, R. (1990).Construction management: organization
systems, London: Mitchell publishing co. Ltd.
Ng, S.T. and Skitmore, R.M. (1998).Contractor financial capability assessment. Australian
institute of building papers, 3rd Sept., 1-32.
Ng, S.T. and Skitmore, R.M. (1999).Client and consultant perspective of prequalification
criteria. Building and Environment, 34,607-621.
Ng, S.T., Skitmore, M. and Smith, N.J. (1999).Decision-makers’ perceptions in the formulation
of prequalification criteria. Engineering construction and architectural management, 6(2), 155-
165.
Ngai,S.C.,Drew,D.S.,Lo,H.P. and Skitmore,R.M.(2002).A theoretical framework for determining
the minimum number of bidders in construction bidding competitions.Construction management
and economics,20(6),473-482.
Nguyen,V.U.(1985).Tender evaluation by fuzzy sets. Journal of construction Engineering and
Management,111, 231-243.
Obiegbu,M.E. (2005).Due Process and the procurement methods in construction industry.
Proceedings of the 35th
annual general meeting/conference of Nigeria Institute of
Building﴾NIOB﴿ AT Abia state,10th
-14th
August,2005.
ijcrb.webs.com
INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS
COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 198
OCTOBER 2012
VOL 4, NO 6
Odusami, K.T. (2001).Criteria for measuring project performance by construction professionals
in the Nigerian construction industry. Journal of financial management of property and
construction, 8(1), 39-47.
Odusami.K.T.,Onukwube,H.N.,Ekwoanya,C.C. and Achi,F.O.(2007).An evaluation of factors
affecting the selection of building contractors: the case of Nigeria.5th
international conference on
construction project management/2nd
international conference on construction engineering and
management(ICCPM/ICCEM),1-7.
Ogunlana, S.O. (2002).Training for construction industry development: best practices. In
S.O.Ogunlana(Ed).Training for construction industry development, CIB publication no 282(1-
6).Thailand: Department of civil engineering, Asian institute of Technology.
Ogunsanmi, O.E. and Bamisile, A. (1999).Selection of main contractor in Nigeria. Construction
in Nigeria, 12(1), 2-12.
Ogunsanmi, O.E., Iyagba, R.O.A. and Omirin, M.M. (2001).Modeling procurement performance
in housing projects in Nigeria. The Lagos journal of Environmental Studies, 3(1), 16-35.
Ogunsemi, D.R. and Ojo, I.O. (2005).A model for contractors’ selection in Nigeria. Journal of
Nigerian Institute of Quantity surveyors, 50(1), 1-8.
Ogunsemi,D.R.and Jagboro,G.O.(2006).Time-cost model for building projects in
Nigeria.Construction Management and Economic,24,253-258.
Ogunsemi, D.R. and Aje, I.O.(2006).A model for contractors’ selection in Nigeria. Journal of
financial management of property and construction, 3(1), 33-44.
Oladapo,A.A.(2005).An evaluation of the maintenance management of the staff housing Estates
of selected first generation universities in southwestern,Nigeria.Unpublished thesis submitted to
ijcrb.webs.com
INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS
COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 199
OCTOBER 2012
VOL 4, NO 6
the department of building, faculty of Environmental design and management,ObafemiAwolowo
University,Ile-Ife,Osun state.
Olatunji, O.A. (2008).A comparative analysis of tender sums and final costs of public
construction and supply projects in Nigeria. Journal of financial Management of Property and
Construction, 13 (1), 60-79.
Oyediran, O.S. (1995).Comparative analysis of criteria for the award of contract in public and
private sectors of the Nigeria construction industry. Federation of building and civil engineering
contractors in Nigeria, 10(9), 14-23.
Palaneeswaran,E.,Kumaraswamy,M.M. and Tam,P.W.M.(1999).Comparing approaches to
contractor selection for design and build.CIB W55 and W65 Joint Triennial Symposium,
Customer satisfaction: A focus for research and practice, Cape Town:5th
-10th
sept.,1-10.edited
by Bown,P. and Hindle,R.
Palaneeswaran, E., Kumaraswamy, M. and Ng, T. (2003).Targeting optimum value in public
sector projects through “best value”-focused contractor selection. Engineering construction and
management, 11(6), 418-431.
Palaneeswaran, E. and Kumaraswamy, M.M. (2009).Contractor selection for Design/Build
projects. Journal of Construction Engineering and Management, 126(5), 331-339.
Peters, L.A.and Hommers, J.L. (1997).It’s not time, cost or quality that ensure project success:
Learn project fundamentals and core processes which are keys to project success. Paper
presented at project management institute 28th
annual seminars and symposium, Chicago,
Illinois.
ijcrb.webs.com
INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS
COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 200
OCTOBER 2012
VOL 4, NO 6
Pinto, J.K. and Slevin, D.P. (1988).Project success: definition and measurement techniques.
Project management journal, 19(1), 67-71.
Plebankiewiez, E. (2009).Contractor prequalification model using fuzzy sets. Journal of civil
engineering and management, 15(4), 377-385.
Polat, G. and Donmez, U. (2009).ANP-based marketing activity selection model for construction
companies. Construction innovation, 10(1), 89-111.
Pongpeng, J. and Liston, J. (2003).TenSeM:a multicriteria and multidecison-makers’ model in
tender evaluation. Construction management and economics, 21, 21-30.
Pongpeng, J. and Liston, J. (2003).Contractor ability criteria: a view from the Thai construction
industry. Construction management and economics, 21,267-282.
Puthitha,P.(2011).Contractor prequalification criteria, Tendering criteria and Tendering
procedure in Cambodia building and housing construction projects.http://www.set.ait.ac.th/ceim/
retrieved 7/2/2011.
Rahman,M.A. and Chileshe,N.(2012).Attitudes,Perceptions and Practices of contractors towards
quality related risks inSouth Australia.18th
Annual Pacific-rim Real Estate Society Conference
Adelaide,Australia,15th
-18th
January.,1-12.
Russell, J.S.and Skibniewski, M.J. (1988).Decision criteria in contractor prequalification.
Journal of Management in Engineering, 4,1 48-164.
Russell, J.S. (1992).Decision models for analysis and evaluation of construction contractors.
Construction management and economics, 10,185-202.
Saaty,T.L.(1980). The Analytical Hierarchy Process. McGraw-Hill International, New York.
ijcrb.webs.com
INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS
COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 201
OCTOBER 2012
VOL 4, NO 6
Saaty, T.L. (1990).How to make a decision: The Analytical Hierarchy Process. European
Journal of Operational Research, 48, 9-26.
Saaty, T.L. (2008).Decision making with the analytical hierarchy process. International journal
services sciences, 1(1) 83-91.
Saxby,W.(2004).Is there a Prisoners’ Dilemma in construction procurement.The international
construction research conference of the Royal Institution of chartered surveyors held at
Headingley cricket clud,Leeds Metropolitan University,Uk.7th
-8th
September,2004,1-15.
Seydel, J. (2005).Supporting the paradigm shift in vendor selection: multicriteria methods for
sole-sourcing. Construction management and economics, 31(3), 49-66.
Shen, Q.Lo.K. and Wang.(1998).Priority setting in maintenance management: a modified multi-
attribute approach using analytic hierarchy process. Construction management and Economics,
16,693-702.
Shen, L.Y., Drew, D.S. and Zhang, Z.H. (1999).Optimal bid model for price-time biparameter
construction contractor. Journal of construction engineering and management, 125(3)204-209.
Sonmez, M., Holt, G.D., Yang, J.B. and Graham, G. (2002).Applying evidential reasoning to
prequalifying construction contractors. Journal of management in engineering, 8(3), 111-119.
Spear,J.E.(2005).Performance improving contractor. Spear Consulting LLC,1-.4.
Steven,J.D.(1996).Blueprint for measuring project quality.Journal of Management in
Engineering,ASCE,12(2) 34-39.
Takim,R.Akintoye,A. and Kelly,I.(2003).Performance measurement system in
construction.In:Greenwood,D.J.(Ed.) 19th
Annual ARCOM conference.3rd
-5th
Sept.,2003.University of Brighton Association of Researchers in Construction
Management,1,423-432.
ijcrb.webs.com
INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS
COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 202
OCTOBER 2012
VOL 4, NO 6
Tam, C.M. and Harris,F.(1996).Model for assessing building contractors’ project performance.
Engineering construction and architectural management, 3(3), 187-203.
Tam, K.C., Hu, T.S. and Ng, S.T. (2005).Using principal component analysis method as a tool in
contractor pre-qualification. Construction management and economics, 23,673-684.
Tamosaitiene, J., Turskis, Z. and Zavadskas, E.K.﴾2008﴿.Modeling of contractor selection taking
into account different risk level. The 25th
international symposium on automation and robotics in
construction﴾ISARC﴿,june 26th
-29th
,676-681.
Tan,Y.,Shen,L.,Lu,W. and Shen,Q .﴾2008﴿.Multiple-objective bidding strategy using goal
programming technique.Management Decision,46(4), 656-672.
Tarawneh, S.A. (2004).Evaluation of pre-qualification criteria: Client perspective; Jordan case
study. Journal of Applied Sciences, 4(3), 354-363.
Tan, Y. and Shen, L. (2009).A fuzzy competence requirement (FCR) model for competitive
bidding strategy. Construction innovation, 10(1), 75-88.
Topeu, Y.I. (2004).A decision model proposal for construction contractor selection in Turkey.
Building and Environment, 39,469-481.
Udensi,C.U.﴾2005﴿.Problems in the implementation of Due Process.Proceedings of the 35th
annual general meeting/conference of Nigeria Institute of Building﴾NIOB﴿ AT Abia state,10th
-
14th
August,2005.
Ulubeyli, S., and Kazaz A. (2009).A multiple criteria decision-making approach to the selection
of concrete pumps. Journal of civil engineering and management, 15(4), 369-376.
ijcrb.webs.com
INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS
COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 203
OCTOBER 2012
VOL 4, NO 6
Wong, C.H., Holt, G.D. and Cooper, P.A. (2000).Lowest price or value? Investigation of UK
construction clients’ tender selection process. Construction management and economics, 18(7),
767-774.
Wong, Y.and Chan, T.S.(2003).Application of analytic hierarchy process in construction
procurement. Proceeding of the CIB student chapters’ international symposium-innovation in
construction and real estate. The Hong Kong polytechnic university, Hong Kong.
Wong, C.H., Nicholas, J. and Holt, G.D. (2003).Using multivariate techniques for developing
contractor classification models. Engineering construction and architectural management, 10(2),
99-116.
Xiaohong,H.(2011).An analysis of the selection of project contractor in the construction
management process.International journal of business and management,6(3),184-189.
Zala,M.I.and Bhatt,R.B.(2011).An approach of contractor selection by Analytical Hieirarchy
Process.National Conference on Recent Trends in Engineering and Technology,13th
-14th
May,1-
6.
Zavadskas,E.K.;Kaklauskas,A.;Turskis,Z.and Tamosaitiene,J.﴾2008﴿.Contractor selection multi-
attribute model applying COPRAS method with grey interval numbers. International conference
20th
EURO mini conference “continuous optimization and knowledge-based
technologies﴾EurOPT-2008﴿ May 20th
-23yh Neringa, LITHUANIA 241-247.
Zhi, L. and Wei, W. (2007).Contractors selection based on the grey decision model. Wireless
communications, Networking and Mobil Computing, 2007, WICOM International conference
21st-25
th sept., at Shanghai, 5301-5304.