FactorsInﬂuencingContractorPrequaliﬁcationProcesses ...construction industry. TheEconomy Watch (2010) stated that the construction industry is an important sector and that it is

International Journal of Architecture, Engineering and ConstructionVol 4, No 4, December 2015, 232-245

Factors Influencing Contractor Prequalification Processes

in Developing Countries

Mohammad M. Molla∗ and Eric Asa

Department of Civil and Environmental Engineering, North Dakota State University

Fargo, North Dakota, 58108-6050, United States

Abstract: There are numerous risk factors associated with contractor prequalification practices that may turnthe construction business into a hardship for the cost-oriented investors. It is necessary to address suitable riskfactors that need to be considered before final awarding any contract. Therefore, this paper aimed to identifythe factors should be considered during the contractors’ bid-prequalification process. Therefore, this studyconduct a thorough review of the literature about the contractors’ bid prequalification to identify the factorsthat are currently being practiced by the construction industry, research, and practitioner. This researchutilized a literature-review approach to achieve the research goal. Results showed that, from 1985 to 2012,a total of 18 major factors, containing a total of 163 minor factors, were used during the contractors’ bid-prequalification process. This study indicates a wide range of decision criteria that should be considered incontractor prequalification process. The outcomes of this research will contribute to the literature gaps and willhelp the construction industry to identify competent, successful, qualified, and quality contractor.

Keywords: Contractor prequalification, bid evaluation, tender, contractor selection, construction contracting

DOI: 10.7492/IJAEC.2015.024

1 INTRODUCTION

Prequalification could be used in early stages of thebidding process in order to select a group of potentialcontractors. The prequalification process could be usedfor various projects, goods, or services. Enshassi andNayrab (2010) stated that bidding decisions can affectbusiness success, meaning that the resulting output isbased on decision inputs at the contractor-solicitationlevel. Elyamany (2010) stated that large contractorswith more experience are competing against small con-tractors and that small contractors could bid lowerprices. Hatush and Skitmore (1997) explained the ne-cessity of contractor selection. They indicated that thecontractor prequalification, evaluation, and selectionprocess, as well as the criteria used, are elementaryeven though the project complexity and client require-ments have increased during the last two decades. Bub-shait and Al-Gobali (1996) stated that bid evaluationis one of the most vital functions for project manage-ment. Proper contractor selection affects the project’ssuccess or failure. Bubshait and Al-Gobali stated that

the owner and contractor benefit from an effective bid-evaluation process. With a proper bid-evaluation sys-tem, the owner for a given work, good, or service wouldbe able to select competent, financially capable, andexperienced contractors. Contractors would be able todecide whether they should bid on a project. Russell(1996) stated that the best prices with a higher-qualitycontractor could be obtained by practicing appropriatecontractor-evaluation techniques.

A project’s procurement risk is a basic problemfor construction firms (Kanoglu and Gulen 2013).They developed a model and tool covering both theconceptual and practical dimensions for managingthe construction firms’ contractual risks. Ye (2013)presented mixed development strategies for infrastruc-ture project. He reported that both traditional andconcession procurement approaches have limitations.Ye’s mixed-development strategy suggested that deci-sion makers should consider the project characteris-tics, the conditions of the construction market, andthe project participants.

*Corresponding Author. Email: [email protected]

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http://dx.doi.org/10.7492/IJAEC.2015.024

mailto:[email protected]

Molla and Asa/International Journal of Architecture, Engineering and Construction 4 (2015) 232-245

According to the report of the World Economic Fo-rum (2008), the world economic recession changedthe business environment into a zero-investment game.As their demands increased, cost-oriented owners whowork internationally created hardships for engineeringand construction companies. A 2006 CEO survey indi-cated that the engineering and construction businessenvironments are changing dramatically. Currently,this sector operates and searches for long-term goalsand multi-stakeholdership. In order to respond to cus-tomers’ demands, these industries have been proactive-ly preparing long-term plans even though a majority ofthe risks are unknown. The 2006 CEO survey showedthat, for the first time, more than 50% of the world’spopulation lives in urban areas.Infrastructure development mainly depends on the

community’s population and economic growth. Ear-lier studies by the report of the World Economic Fo-rum (2008) suggest that, in developing countries, 71%of the population will live in urban areas by the year2020, creating increased demand for engineering andconstruction industry. The Economy Watch (2010)stated that the construction industry is an importantsector and that it is one of the biggest industries inthe world economy. The construction industry con-tributes approximately 10% to the global GDP andapproximately 7% of the total employed population.The United Nations (2012) stated that the construc-tion sector is experiencing strong economic growth indeveloping countries. The previously mentioned stud-ies showed that the engineering and construction in-dustries have a major influence on the world economyand are contributing significantly to economic growth.By using a bid-prequalification process for contrac-

tors, project owners could benefit in several ways.Owners may be able to identify competent, success-ful, qualified, and quality contractors before awardingany contract. Owners could create an efficient sys-tem to reduce the bid-processing time and cost, in-cluding the elimination of bias. If the bid specifica-tions for a contract only require the selection of thelowest-cost bidder, project performance and qualitycould be jeopardized. Contractor prequalification isa multivariate decision-making process which could beused to pre-select contractors who are then asked tosubmit bids for projects, works, goods, and servicesin the construction industry. Construction projectsare risky, and there are always uncertainties presentwith each project. The contractor prequalification pro-cess decision-support system requires inputs from var-ied qualitative and quantitative perspectives. It is evi-dent that a systematic contractor-prequalification pro-cess would reduce the risks and uncertainties.Therefore, this paper aims to identify the factor(s)

that should be considered during the contractors’ bid-prequalification process in developing countries. Toidentify the factors that should be considered, a reviewof the current contractor-evaluation methods, the ex-

isting research about prequalification among organiza-tions and countries, and the work cited most frequent-ly about contractor prequalification will be analyzedto accomplish the objective. A rigorous Literature Re-view is utilized to search for the globally recognizedfactors that have been considered for the contractorprequalification process. This research presents litera-ture that is available from the American Society of Civ-il Engineers (ASCE), Science Direct, Web of Science,and Google Scholar. Finally, a tabulation method isemployed to analyze the Literature Review’s findingsand to present data in the Results and Discussion sec-tion.

2 LITERATURE REVIEW

The literature indicates a wide range of decision crite-ria that are being used to evaluate contractors’ overallsuitability. A thorough review of the literature may re-veal the existence of various criteria, different informa-tion types, and different assessment methods. In orderto conduct the research investigation, it is necessary tostudy the global practices for the bid-prequalificationprocess that are frequently being used by the indus-try, researchers, and practitioners. Selected literatureis discussed in the following paragraphs.

The U.S. National Research Council (1994) statedthat, by the middle of the nineteenth century, U.S.government officials authorized the practice of prequal-ifying contractors during the bidding process in orderto protect public funds, to eliminate corruption andbias, to develop an efficient system, and to prevent mis-management. The study showed that the majority ofstates use either prequalification or post qualificationfor contractors during the bidding process. The at-tributes used to evaluate a prospective contractor arefinancial capability (financial strength of the contrac-tor at the time of qualification, the ability to obtaina bid, performance, and payment bonds for a specificproject), managerial and technical abilities, past ex-perience (ownership of equipment, the ability to rentor lease the equipment needed to perform the project,managerial ability to provide the required labor or ma-terials, the experience of key supervisory personnel,technical ability to perform, skills, and overall experi-ence), performance evaluation (attitude, cooperation,and performance on state department of transporta-tion projects, quality performance, and the ability tofinish projects on time), and business practices in orderto ensure that the contractor or the company has notbeen involved with previous wrongdoings or infractionsof agency policy. The U.S. National Research Councilmentioned that more than 75% of state departments oftransportation are at least evaluating the financial andmanagerial strength of prospective contractors, whichalso includes checking the debarment list that is main-tained by the Federal Highway Administration.

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On the other hand, the American Association ofState Highway Officials, the Associated General Con-tractors (AGC), and the Bureau of Public Roads arefollowing standard practices when selecting contractors(National Research Council 1994). Assaf and Jannadi(1994) used financial stability, experience, references,past performance, current workload, staff availability,manpower resources, company organization, office lo-cation, experience in a geographic location, quality per-formance, historical failure, procurement experience,safety consciousness, and claim attitude for their multi-criteria decision model in Saudi Arabia.Bubshait and Al-Gobali (1996) identified the cri-

teria for bid prequalification and ranked the criteriathat should be considered for semi-public and privateprojects in Saudi Arabia. The result indicated thatthe criteria used to evaluate the process include thecontractor’s experience, financial stability, past perfor-mance, quality performance, project-management ca-pabilities, historical failure, staff availability, and thecontractor’s capacity. The results were compared withthe United States and found to be similar. Sixteenfactors were identified, and then grouped and rankedbased on a relative importance index. The QueenslandDepartment of Public Works (2011) used a methodcalled the best value for the money. The idea wasthat the bidder who is most profitable and producesthe highest returns for the investment will probably beawarded the project. In some cases, such as a complexbid evaluation, the Queensland Department of PublicWorks utilized a warranted procurement commission-ing (Department of Public Works 2011).Hatush and Skitmore (1997) discussed the bidding

criteria that are being used by the United Kingdom’sconstruction industry. There, the contractors’ capabil-ities have to be justified and verified to see whether thecontractors are able to complete the work before award-ing any project. In the United Kingdom, the biddingprocess has three basic stages: 1) general information,2) prequalification, and 3) bid evaluation. General in-formation is the administrative information about acontractor company’s details, the scope of work, tech-nical resources, references, existing insurance, taxationdetails, financial information, subcontracting, race re-lations, plants and equipment, and health and safety(Hatush and Skitmore 1997).Russell and Skibniewski (1988) presented several fac-

tors, such as management, safety, location, perfor-mance, resources, finances, experience, failed perfor-mance, bonding, and the capacity for assuming anew project, when choosing a qualified contractor andavoiding construction failure. The Department of Trea-sury and Finance (1999) of Tasmania utilized a weight-ed bid-evaluation process rather than awarding the bidto the lowest bidder so that the department was able toutilize the money’s best value. Bid-evaluation guide-lines were developed using the weighted criteria, andthe most important evaluations were for the areas of

experience, past performance, technical skills, manage-ment skills and systems, resources, methodology, andcost.One of the critical success factors identified by Zhang

(2005) is related to concessionaire selection in public-private partnered (PPP) projects, that is, “reliable con-cessionaire consortium with strong technical strength”.In PPP projects, the concessionaire undertakes farmore commitments and assumes much broader anddeeper risks than a mere contractor. In addition to for-mulating a sound technical package, the concessionaireshould also have strong managerial capabilities suchas workable project organization structure, good re-lationship with host government authorities, partner-ing skills, rich experience in international PPP projectmanagement, and a strong project team.Shen et al. (2003) proposed a decision-support sys-

tem in order to select contractors for a competitivebid by using computer-aided applications. Utilizingcomputer-aided support systems allowed the owners tosort suitable bidders based strengths and weaknesses.Searching through the bidders’ weaknesses helped de-termine suitable contactors. Lai et al. (2004) includedsix main perspectives about bid evaluations: 1) degreesof responsiveness, 2) construction organization, 3) con-tractor reputation and competence, 4) prices of threematerials (steel, cement, and lumber), 5) the range forminimizing cost, and 6) thorough verification. Lamet al. (2005) reported that 17 factors should be con-sidered during the bid-evaluation process: 1) qualitystandard, 2) time, 3) construction scheme, 4) the qual-ity guarantee system, 5) safety, 6) plans for the laborforce, equipment, and material used, 7) the construc-tion schedule and guarantee measure, 8) the level ofqualification, 9) reputation, 10) the project manager’squalification level, 11) experience with similar projects,12) a qualified and excellent percentage of projects inthe last two years, 13) the percentage of on-time com-pletions, 14) bid prices, 15) amount of materials, 16) acost-minimization plan, and 17) points for a compre-hensive check and evaluation. Lam et al. (2005) statedthat the bid-evaluation process, using these 17 factors,was non-linear, uncertain, subjective, and complicated.Therefore, the study proposed a principal componentanalysis method to model it. Utilizing this method,a large number of interdependent variables, with theirco-linearity and dimensionality, could be reduced.Salama et al. (2006) surveyed the criteria for select-

ing contractors and bid evaluations in Egypt. Accord-ing to the authors, Egypt’s government projects areregulated through Act 89/1998, which recommends us-ing a point system to evaluate contractors based ontechnical and financial requirements. Salama et al.conducted research by providing Egypt’s project man-agers and professionals with recommendations aboutsuitable criteria for more accurate evaluations, bothtechnically and financially. The study revealed thatexperience with similar projects, resources, financial

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status, the firm’s structure and organization, the firm’scapacity, projects in progress, and the firm’s claim his-tory are most important. Again, for the technical eval-uation, Salama et al. used quality control/quality as-surance systems, adequacy of technical supervision, theavailability of equipment, method statements, schedul-ing, the experience of key personnel, and the per-centage of the subcontracted work. For the finan-cial evaluation, Salama et al. used bid price, bidprice/consultant or fair estimate, payment schedule,percentage of payments, financial stability, financialstatus, financial strength, credit history, and claim his-tory.El-Sawalhi et al. (2007) included both qual-

itative and quantitative information in the bid-prequalification process. The Genetic Neural Net-works (GNN) methodology was used to develop a state-of-the-art method for contractor bid prequalification.El-Sawalhi et al. suggested seven main prequalifica-tion criteria: 1) financial stability, 2) managementand technical ability, 3) experience, 4) historical non-performance, 5) resources, 6) quality, and 7) health andsafety. Abdelrahman et al. (2008) studied rational andflexible best-value procurement strategies for the Min-nesota Department of Transportation. Abdelrahmanet al. stated that the idea of best-value strategies wasbeing increasingly used by federal and state govern-mental agencies. Strategically, the best-value conceptcreated additional value for every dollar. Abdelrahmanet al. proved that quality performance is a better indi-cator of a suitable contractor, which eventually couldbe used to award a contract instead of utilizing thelowest price. They considered price, schedule, finan-cial and bonding requirements, past experience, safe-ty record/plan, key personnel and their qualifications,the utilization of small businesses, subcontractor plan,management/organization plan, quality management,design alternative, technical proposal responsiveness,and environmental considerations for the best-valueprocurement strategy (Abdelrahman et al. 2008).Turskis (2008) stated that it is important to be aware

of the bidder’s financial; technical; and general qualita-tive, quantitative, or verbal information before award-ing a project. By using the most preferable technique,feasible alternatives could be identified. This methodcould also be defined as the multi-variable contractor-ranking method. Although the lowest price is a vitalfactor when selecting the bidder, there are other non-price items which have an important role. The studyof Turskis (2008) focused on factors such as a histo-ry of reasonable bid-price submissions, work history,bid responsiveness, quality-control plans, the contrac-tor’s staffing plan, the subcontractor’s plan, coopera-tion with the team, scheduling, the environmental plan,safety concerns, warranty responsiveness, job-site man-agement, claims, workload, and manpower plan. Ple-bankiewicz (2009) stated that only competitive bidderscould be identified through the contractors’ prequalifi-

cation process. Plebankiewicz proposed a model usingthe fuzzy sets theory that has many criteria, such asfinancial standing, technical ability, management ca-pability, health and safety, and reputation. Lam et al.(2009) explained the necessity of using a prequalifica-tion process for both contractors and owners, especiallywith complex and large projects. The prequalificationprocess proactively serves as a safeguard for both par-ties. Considering the complexity of projects and theprequalification process, Lam et al. proposed a supportvector machine (SVM) method for best-value procure-ment. The attributes used in the SVM are financialstrength and resources, previous performance, past ex-perience, human resources, equipment resources, safe-ty and health aspects, environmental considerations,quality management, current workload, managementcapacity, and claims history.Padhi and Mohapatra (2010) researched the Indian

government’s bidding process which includes a three-step procedure before awarding a project. First, thebidders’ general information and claim histories wereevaluated. Second, agencies assessed and scored thebidders based on criteria related to past work perfor-mance, the availability of resources, and the bidders’ fi-nancial status. The three top bidders were selected forthe second step and were asked to submit bids for theproject, and the ultimate offer went to the lowest bid-der. The Minister of Finance (2012) for the DemocraticRepublic of Timor stated that, in order to do long-termbusiness, selecting contractors based only on bid priceswould be an inaccurate method. The government ofTimor considered technical capabilities or profession-al competence, commercial analysis, industry or localdevelopment, and financial analysis as the four ma-jor evaluation criteria. Lam and Yu (2011) developedan advanced multiple kernel learning (MKL) methodbased on subjectivity, non-linearity, and multi-variantbid prequalification with the goal of higher precision.Their MKL method performed better than the earliersupport vector machine method. The attributes of thesupport vector machine were financial strength, pastperformance, past experience, human resources, equip-ment resources, safety and health aspects, environmen-tal considerations, quality management, current work-load, management capacity, and claim history.The review of literature revealed that contractor pre-

qualification is a significant problem for the industry,and it is a continuous, demanding topic. The reviewof literature discussed several methodologies and fac-tor that was considered in each method. The chrono-logical development of contractor evaluation methodswas then summarized and presented in Table 1. Table1 includes the current methodologies for bidder selec-tion for the years from 1985 to 2012. El-Sawalhi et al.(2007), Padhi and Mohapatra (2010), and Hatush andSkitmore (1997) presented a detailed list of histori-cal development for the contractor-prequalification andbid-evaluation methodologies. The significant contri-

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Table 1. Current practices for bidder-selection methodologiesAuthor Country Modeling approachNguyen (1985) Australia Fuzzy set prequalificationRussell and Skibniewski (1990) USA Dimensional weighting aggregationRussell et al. (1990) USA Knowledge based systemEllis Jr and Herbsman (1990) USA Time/Cost approachHerbsman and Ellis (1992) USA Multi-parameter bidding systemHolt et al. (1994) UK Multi-attribute analysisTaha (1994) USA Artificial neural networksTransportation Research Board (1994) USA Scoring systemsMunaif (1995) Saudi Arabia Analytical hierarchy processKumaraswamy (1996) Hong-Kong Performance-based scoringHatush and Skitmore (1997) UK PERT model for contractor prequalificationHatush and Skitmore (1997) UK Point scoring systemHolt (1998) UK Cluster analysisHatush and Skitmore (1998) UK Multi-attribute utility theoryDeng (1999) Australia Fuzzy-analytic hierarchy processDepartment of Treasury and Finance (1999) Tasmania Weighted criteria methodKhosrowshahi (1999) UK Artificial neural networksCollins et al. (1999) USA MAGNET system/simulated annealingLam et al. (2000) Hong Kong Artificial neural networksAl-Harbi (2001) UAE Analytic hierarchy processSeydel and Olson (2001) USA Hybrid multi-criteria methodNg (2001) Hong Kong Case-based reasoningMahdi et al. (2002) Kuwait Analytical hierarchy processSkitmore (2002) Australia Outliers and goodness-of-fitTopcu (2004) Turkey Analytic hierarchy processLai et al. (2004) China Multi-attribute analysisMissbauer and Hauber (2006) Austria Integer programmingWang et al. (2006) Taiwan Unit-price basedLambropoulos (2007) Greece Multi-attribute utility theoryEl-Sawalhi et al. (2007) UK Hybrid model: combining AHP, neural network, genetic

algorithmConti and Naldi (2008) Italy Average bid criteria or bid distribution modelPadhi and Mohapatra (2009) India Fuzzy-analytic hierarchy process-SMARTZhang (2009) Hong-Kong Fuzzy logic systemElyamany (2010) USA Rational approachDepartment of Public Works (2011) Australia Weighted criteria and best value of moneyMinister of Finance (2012) Timor Leste Two envelope tendering system (scoring and best value of

money)

butions and findings from the literature are presentedin Table 1.

Table 1 included the year, author name(s), coun-try, and modeling-approach information. The keypapers from 1985 to 2012 revealed that there are aplethora of methods in different countries around theworld. Some approaches are fuzzy set, dimensionalweighting aggregations (DWA), knowledge-based sys-tems (KBS), time/cost approaches, multi-parameterbidding systems, multi-attribute analysis (MAA), ar-tificial neural networks (ANN), scoring systems, ana-lytical hierarchy processes (AHP), performance-basedscoring (PERT) models, cluster analysis, multi-agentcontract negotiation (MAGNET), hybrid models, bid-distribution models, simulated annealing, case-basedreasoning (CBR), outliers and goodness of fit tests,unit-price methods, integer programming, analytic hi-erarchy process and simple multi-attribute rankingtechnique (AHP-SMART), rational approaches, weigh-ing criteria, and best-value approach.

Selected factors, such as uncertainty, bid price, con-struction time, the quality of previous work, organi-zation and management structure, work experience, fi-nancial capability, technical ability, technology offered,

a similar type of project experience, quality assurance,workload, local knowledge, safety performance, reputa-tion, references, resources, methodologies, mark-up ra-tio, historical non-performance, and warranty, are usedfor the varied modeling approach. A majority of themodels, except fuzzy logic and the hybrid mutli-criteriamodel, only utilize a few factors.

3 METHODOLOGY

To identify the factors that should be considered dur-ing contractor prequalification, a review of the cur-rent contractor-evaluation methods, existing researchon prequalification practices among organizations anddifferent nations, and the work cited most frequent-ly about contractor prequalification was performed. Areview-of-literature approach for the published litera-ture regarding contractor prequalification, bid evalu-ation, contractor selection, bid assessment, etc. wasused. The literature used with this research was fromthe American Society of Civil Engineering, Science Di-rect, Web of Science, and Google Scholar. The refer-ences from the most frequently cited papers were alsoreviewed. A literature study covering the period from

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1985 to 2012 was conducted. In order to achieve theresearch objectives, the factors were analyzed using atabulated process and presented in the Results and Dis-cussion section.

4 RESULTS AND DISCUSSION

Initially, 228 factors were identified. There were a lotof factors that had different terminology, but the samefunctionality, used for the various publications and lo-cations. The bid-prequalification factors with differentterminology but the same meaning were redundant.Thus, based on the tabulation method, the 228 fac-tors were reduced to the 163 factors that are presentedin Table 1. The Table 1 presents 36 articles that werecategorized by Science Direct, Web of Science, and AS-CE. The Table 1 includes factors that were being usedby the industry, researcher, and practitioner from 1985to 2012. Under the 18 major factors listed, a totalof 163 minor factors were counted and ranked basedon the Mann-Whitney ranking procedure. Appendix 1presented all 163 factors. The last two columns of Ap-pendix 1 represent the count and rank for each minorfactor. The count represents how many times each mi-nor factor was observed in the 36 articles. At the end

of the table, the number of factors that each authorused is presented in the last row.

The major factors are 1) general information andregistration detail, 2) experience, 3) project specific,4) references, 5) management and organization, 6) re-sources, 7) finances, 8) methodology, 9) working sched-ule, 10) quality, 11) safety, 12) communication, 13)claim history, 14) capability, 15) subcontracting, 16)estimation, 17) strategic business, and 18) bid spe-cific. Twenty-four prequalification systems and bid-evaluation procedures were used globally (available re-search on prequalification among organizations andcountries, and the work cited most frequently aboutcontractor prequalification).

Based on Appendix 1, the top-10 ranked factors arepresented in Tables 2 and 3. Table 3 has the sup-plementary notation for Table 2. Table 2 shows thatthere are 15 minor factors that are ranked as the top10. Table 2 reveals that the highest number of respons-es was 26 for health and safety performance and plan,which was ranked as the first criterion. The top-15criteria with the highest rankings were 1) health andsafety plan; 2) quality assurance and quality controlplan; 3) financial stability and soundness; 4) manage-ment and technical skills capability; 5) key managerial,

Table 2. Top ten ranked factors

Author Factors1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

1 Nguyen (1985) X X X X X X X X X X2 Russell and Skibniewski (1990) X X X X X X X X X X X X X3 Russell (1990) X X4 Herbsman and Ellis (1992) X X X5 Assaf and Jannadi (1994) X X X X X X X X X X X6 Potter and Sanvido (1994) X X X X X X X X X X X7 Kumaraswamy (1996) X X X8 Bubshait and Al-Gobali (1996) X X X X X X X X X X X9 Russell (1996) X X X X X X X X X10 Hatush and Skitmore (1997) X X X X X X X11 Hatush and Skitmore (1998) X X X X X X X X X X X12 Al-Harbi (2001) X X X X X X X X X13 Sönmez et al. (2002) X X X X X X X14 Shen et al. (2003) X X X X15 Lai et al. (2004) X X X16 Palaneeswaran and Kumaraswamy

(2005)X X X X X X X

17 Singh and Tiong (2006) X X X X X X X X18 Salama et al. (2006) X X X X X X X X X19 El-Sawalhi et al. (2007) X X X X X X X X X X20 Lam et al. (2007) X X X X X X X X X21 Abudayyeh et al. (2007) X X X X22 Li et al. (2007) X X X X X X X23 Turskis (2008) X X X X X X X X24 Lu et al. (2008) X X X X X X25 Plebankiewicz (2009) X X X X X X X X X26 Lam et al. (2009) X X27 Padhi and Mohapatra (2010) X X X X X28 Abdelrahman et al. (2008) X X X X X29 Marsh and Fayek (2010) X X X X X X X X30 Lam and Yu (2011) X X X X X X X X X X31 Nieto-Morote and Ruz-Vila (2012) X X X X X X X X X X X X32 Alzahrani and Emsley (2012) X X X X X X X X X X X

Count 26 24 22 18 18 17 17 16 13 13 12 12 12 11 10Rank 1 2 3 4 4 5 5 6 7 7 8 8 8 9 10

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Table 3. Notation for table 2

Serial Factors1 Health and safety performance and plan2 Quality management, control, and assurance system3 Financial stability and soundness4 Management and technical skills and capability5 Key managerial, supervisory and operational personnel experience and availability6 Equipment resources and availability7 Contractor’s failure to complete a project8 Past and current performance9 Workforce resources and availability10 Claim history11 Length of time in business12 Contractor’s organization and plan13 Current workload14 Experience in the project’s geographic location15 Credit rating and history

supervisory, and operational personnel experience andavailability; 6) equipment resources and availability;7) contractor’s failure to complete a project; 8) pastand current performance; 9) workforce resources andavailability; 10) claim history; 11) length of time inbusiness; 12) contractor’s organization and plan; 13)current workload; 14) experience in the project’s geo-graphic location; and 15) credit rating and history.

Each factor was also counted based on the total num-ber of authors who listed the factor as important. Thequartile analysis of the counts shown in Table 4 showshow the identified factors revealed that 75% of the fac-tors were below a count of 3 and that 25% of the fac-tors were above a count of 3. Therefore, 50% of thefactors were above the count of 1. Using the normal-distribution confidence interval theory, not a single fac-tor could be eliminated because all the lower-rankingfactors were within the 95% confidence interval bound-aries. It can be concluded that the count distributionwas not normally distributed. The pareto plot in Fig-ure 1 indicates that the distribution pattern for eachauthor’s factor responses is positively skewed.

A total of 87 factors received just one author’s opin-ion, which was ranked as the least-responded criterion.According to the goodness-of-fit test for 162 degreesof freedom, the observed chi-square value was 1036.42,and the P-Value was less than 0.005. Therefore, it canbe inferred that, for the 99.995% significance level, allfactors did not have the same significance.

Figure 1. Pareto plot of the identified factors

5 CONCLUSION

This paper conducted a rigorous and extensive Liter-ature Review about the contractor’s prequalificationpractices. This study presented a comprehensive listof contractor prequalification factors. Prequalificationfactors and criteria were compiled and analyzed by re-viewing the 24 prequalification systems and literaturereview. This study indicates a wide range of decisioncriteria that are being used to evaluate contractors’overall suitability. A thorough review of the literaturemay reveal the existence of various criteria, differentinformation types, and different assessment methods.This paper discovered appropriate factors that need

to be addressed in order to find the best-qualified con-tractors to reduce the unknown risk for a construction

Table 4. Quartile analysis for the countsQuartile

No. Count Quartile PercentileFunction Count Description

0 1 Same as Minimum 0 11 1 1st Quartile 0.25 1 25% of the values are below the count of 1, and

75% of the values are above the count of 12 1 2nd Quartile

Same as Median0.5 1 50% of the values are above the count of 1

3 3 3rd Quartile 0.75 3 75% of the values are below the count of 3, and25% of the values are above the count of 3

4 26 Same as Maximum 1 26

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project. The outcomes of this research might be rec-ommended during the contractor’s bid prequalificationfor any projects, goods, or services, especially in devel-oping countries, including any international, lucrative,funded project. This research considered a literature-review approach to achieve the research goal. The com-plete set, with 163 factors, was very large, and it isexpensive to employ the entire list of factors. Thisstudy demonstrated that all 163 factors do not haveequal importance and significance. Therefore, a statis-tical investigation can be done in the future in orderto identify the most influential of these 163 factors.Again, a future survey can be utilized to identify thefactors. A better systematic framework can be devel-oped to reduce the risk before awarding any projects.Finally, the research results may be recommended

for the construction industry to utilize when identify-ing competent, successful, qualified, and quality con-tractors before awarding any contract. The outcomesof this research will contribute to the literature signif-icantly and help the construction industry.

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Molla and Asa/International Journal of Architecture, Engineering and Construction 4 (2015) 232-245A

ppen

dix

1.Prequ

alification

factorsin

currentpractices

MajorFactor

Minor

Factor/Year

Science

Direct

Web

ofScience

ASCE

Others

Organ

ization

Count

Rank

12

34

56

78

910

1112

1314

1516

1718

1920

2122

2324

2526

2728

2930

3132

3334

3536

Kumaraswamy

HatushandSkitmoreAl-HarbiLaietal.Nabiletal.PlebankiewiczLametal.PadhiandMohapatra

MoroteandVila

AlzahraniandEmsley

Assaf

Shenetal.

Lametal.

Zenonas

LamandYu

RussellandSkibniewski

Russell

HerbsmanandEllis

PotterandSanvidor

BubshaitandAl-Gobali

Sonmezetal.

PalaneeswaranandKumaraswamy

SinghandTiong

Abudayyehet.Al

Lietal.

Luelat.

ElyamanyandAbdelrahman

MarshandFayek

Nguyen

Russell

ZedanandSkitmore

Salama

Australia

Tasmania

NCHRP

Timor

199619982000200420072009200920102012

2012

1994

2003

2007

2008

2011

1990

1990

1992

1995

1996

2002

2005

2006

2007

2007

2008

2010

2010

1985

1996

1997

2006

2000

1999

1994

2007

GeneralInform-ationandRegi-strationDetails

Validityof

registration

details

XX

XX

X5

16Attitude,

coop

erationan

dperform

ance

XX

XX

X5

16Board

ofdirectors

X1

20Custom

erservice,

includingwholeof

life

servicingan

dmaintenan

ceX

X2

19Qualification

grad

eX

120

Fam

iliarity

withregu

latingau

thorities

X1

20Ownership

andsubstan

ceof

thebusiness

XX

X3

18Age

ofshareholders

X1

20

Experience

Lengthof

timein

business

XX

XX

XX

XX

XX

XX

129

Sizeof

business

XX

XX

417

Lengthof

timecompan

ycontrolledbycurrentman

agem

ent

X1

20Largest

project

perform

edin

past5years

XX

219

Pastan

dcurrentperform

ance

XX

XX

XX

XX

XX

XX

XX

XX

XX

XX

204

Qualified

andexcellentpercentage

ofproject

inrecent5years

XX

219

General

worksexperience

X1

20Specialist

workexperience

X1

20Partners/sub-con

tracts

experience

XX

219

Recentcompletedproject

X1

20Typeof

workwan

tto

door

did

XX

XX

XX

XX

813

Pastperform

ance

inow

ner’s

previousproject

X1

20Sizeof

project-experience

XX

XX

XX

615

Classes

ofworkperform

edin

each

project

X1

20Workperform

edwithow

nforces

X1

20Businesscoverage

X1

20

References

Number

ofprojects-experience

X1

20Expertise

insimilar

projects

XX

XX

XX

XX

813

Largest

similar

project

perform

edin

pastfive

years

X1

20Understan

dingof

objectives

andidentify

keyissues

X1

20Experience

ingeographic

location

ofproject

XX

XX

XX

XX

XX

X11

10Com

pan

yim

age-historicalnon

-perform

ance

X1

20Com

pan

yreputation

XX

XX

XX

615

Appreciationof

thetask

XX

XX

417

References

XX

XX

XX

XX

XX

1011

Goodrelation

ship

withstakeholders

XX

XX

X5

16Goodrelation

ship

withpas

projectsow

ners

X1

20Clientsatisfaction

-historicalnon

-perform

ance

XX

219

ManagementandOrganization

Man

agem

entan

dtechnical

skills

andcapab

ility

XX

XX

XX

XX

XX

XX

XX

XX

XX

XX

204

Qualityman

agem

entsystem

X1

20Leader’s

personalityan

dcapab

ility

X1

20Qualification

ofow

ners/contractor

XX

219

Designan

dconsultan

tman

agem

ent

XX

219

Environ

mentalsustainab

ility

XX

XX

XX

XX

813

Subcontractorman

agem

ent

XX

219

Waste

man

agem

ent

XX

X3

18Project

man

agem

ent

XX

XX

X5

16Project

control

procedures

XX

X3

18Plantman

agem

ent

X1

20Con

tractman

agem

ent

X1

20Substan

ceab

use

policy

XX

219

Siteman

agem

ent

XX

XX

XX

615

Standardof

subcontractors’worksin

pastprojects

X1

20Con

tractororganizationan

dplan

XX

XX

XX

XX

XX

XX

X13

8Logistican

dsupply

chainman

agem

ent

X1

20Purchasingexpertise,materialhan

dlingan

dcontrol

XX

219

242


Appen

dix

1.Prequ

alification

factorsin

currentpractices(con

tinu

ed)

MajorFactor

Minor

Factor/Year

Science

Direct

Web

ofScience

ASCE

Others

Organ

ization

Count

Rank

12

34

56

78

910

1112

1314

1516

1718

1920

2122

2324

2526

2728

2930

3132

3334

3536

Kumaraswamy


MoroteandVila

AlzahraniandEmsley

Assaf

Shenetal.

Lametal.

Zenonas

LamandYu


Russell

HerbsmanandEllis

PotterandSanvidor


Sonmezetal.


SinghandTiong

Abudayyehet.Al

Lietal.

Luelat.


MarshandFayek

Nguyen

Russell

ZedanandSkitmore

Salama

Australia

Tasmania

NCHRP

Timor

199619982000200420072009200920102012

2012

1994

2003

2007

2008

2011

1990

1990

1992

1995

1996

2002

2005

2006

2007

2007

2008

2010

2010

1985

1996

1997

2006

2000

1999

1994

2007

Resources

Key

man

agerial,supervisoryan

dop

erational

personnel

experience

and

availability

XX

XX

XX

XX

XX

XX

XX

XX

XX

XX

204

Personnel

back-upstrategy

XX

X3

18Amou

ntof

workperform

edwithow

nforces

X1

20Techno-wareTechnologyavailability

X1

20Info-w

areTechnologyknow

ledge

andavailability

XX

XX

X5

16Org-w

areTechnologyavailability

X1

20Human

-wareTechnologyavailability

X1

20Ownership

ofequipmentor

theab

ilityto

rentor

leaseequipmentneeded

toperform

thejob

XX

219

Workforceresources

andavailability

XX

XX

XX

XX

XX

XX

XX

X15

7Equipmentresources

andavailability

XX

XX

XX

XX

XX

XX

XX

XX

XX

185

Equipmentop

erational

experience

X1

20Thequan

tities,capab

ilities,

andconditionof

thecontractor’sow

ned

orrentedequipment

XX

X3

18

Availab

ilityof

product

andprice

inform

ationof

labor,materials,plants,

andother

resources

X1

20

Availab

ilityof

testingequipmentas

qualityassurance

X1

20Equipmentrepairan

dmaintenan

ceX

XX

X4

17

Qua-lity

Qualityman

agem

ent,

control

andassurance

system

XX

XX

XX

XX

XX

XX

XX

XX

XX

XX

XX

XX

XX

XX

281

Achievementof

qualitylevel

X1

20Qualityperform

ance

XX

X3

18

Metho-dology

Statementof

methodology

XX

XX

X5

16Technical

proposal

respon

siveness

XX

219

Environ

mentalconsiderations.

XX

219

Specializedknow

ledge

ofparticularconstructionmethod

XX

219

Finance

Finan

cearrangement

XX

219

Qualityof

finan

cial

statem

ent

X1

20Con

structionexperience

ofaccountant

X1

20Accou

ntingmethod

X1

20Currentcommitments

X1

20Cap

ital

X1

20Currentan

dfixed

assets

X1

20Net

worth

X1

20Ran

geof

reducingcost

X1

20Finan

cial

stab

ilityan

dsoundness

XX

XX

XX

XX

XX

XX

XX

XX

XX

XX

XX

XX

243

Previousfinan

cial

penalties

XX

219

Currency

ofrecordsof

employees

X1

20Credit

ratingan

dhistory

XX

XX

XX

XX

XX

1011

Solvency

XX

X3

18Liquidity

XX

XX

XX

615

Turnover

history

XX

XX

XX

X7

14Overruns:

cost

XX

X3

17Ban

karrangement

XX

XX

XX

615

Debit

ratio

XX

XX

XX

615

Owned

finan

cial

funds

X1

20Previousclaimsan

dpastjudgm

ents

X1

20Paymentscore

X1

20Profitability

XX

XX

XX

XX

813

243


Appen

dix

1.Prequ

alification

factorsin


tinu

ed)

MajorFactor

Minor

Factor/Year

Science

Direct

Web

ofScience

ASCE

Others

Organ

ization

Count

Rank

12

34

56

78

910

1112

1314

1516

1718

1920

2122

2324

2526

2728

2930

3132

3334

3536

Kumaraswamy


MoroteandVila

AlzahraniandEmsley

Assaf

Shenetal.

Lametal.

Zenonas

LamandYu


Russell

HerbsmanandEllis

PotterandSanvidor


Sonmezetal.


SinghandTiong

Abudayyehet.Al

Lietal.

Luelat.


MarshandFayek

Nguyen

Russell

ZedanandSkitmore

Salama

Australia

Tasmania

NCHRP

Timor

199619982000200420072009200920102012

2012

1994

2003

2007

2008

2011

1990

1990

1992

1995

1996

2002

2005

2006

2007

2007

2008

2010

2010

1985

1996

1997

2006

2000

1999

1994

2007

Saf-ety

Healthan

dsafety

perform

ance

andplan

XX

XX

XX

XX

XX

XX

XX

XX

XX

XX

XX

XX

XX

X27

2Security

X1

20

Commu-nication

Com

munication

XX

X3

18Documentation

man

agem

ent

XX

X3

18Inad

equatelystaff

edreception

arrangements

fortelephon

emessage

atheadoffi

ceX

120

WorkingSchedule

Schedule

ofproject

XX

XX

XX

XX

X9

12Schedule

ofresources

XX

219

Con

structionschem

eX

120

Schedulingof

cost

control

XX

219

Overruns:

time

XX

X3

18Con

structionschedulinggu

aran

teemeasure

XX

219

Projectscompletedon

time

X1

20Project

completedon

budget

X1

20Percentage

ofkeepingtimepromise

X1

20

ClaimHistory

History

ofclaims

XX

XX

XX

XX

XX

XX

XX

X15

7Con

tractorfailure

tocomplete

aproject

XX

XX

XX

XX

XX

XX

XX

XX

X17

6Con

tractnot

renew

eddueto

failure

toperform

XX

219

Currentclaimsin

court

orarbitration

X1

20Prequalification

anddisqualification

history

withan

yagency

X1

20Litigationtendency

XX

X3

18Engagedin

frau

dulentactivity

X1

20Has

thecontractorever

beendebarredin

acertainjurisdiction

area

by

agovernmentalagency

XX

219

Claim

anddispute

resolvingskills

X1

20Know

ledge

andexpertise

onlaw

X1

20Declined

invitations,or

did

not

submitabid

onat

leastthreeoccasions

intheprevious12mon

ths

XX

219

Capability

Currentworkload

XX

XX

XX

XX

XX

XX

129

Unbon

ded

at-riskwork

X1

20Availab

lesurety

credit

X1

20Amou

ntof

currentuncompletedwork-on-han

dX

X2

19Largest

ofam

ountof

uncompletedwork-on-han

dX

120

Abilityto

obtain

abid,perform

ance,pay

mentbon

d;bon

dingcapacity

XX

XX

XX

XX

813

Cap

acityof

firm

sX

X2

19Amou

ntof

workperform

edearlier

X1

20Cap

acityto

addthis

project

XX

219

Availab

ilityof

liab

ilityan

dworkers’compensation

insurance

policies

X1

20Themax

imum

amou

ntof

workthat

canbeperform

edbythecontrac-

tor’sow

nworkforce

X1

20

Key

man

life

insurance

X1

20Risk

man

agem

ent(including

insurance,an

duse

ofau

thorized

sub-

contractors)

XX

XX

417

Sub-contracting

Percentage

subcontractedwork

X1

20Utilization

ofsm

allbusiness

X1

20Subcontractorprequalification

process

X1

20Man

agem

entof

subcontractors

X1

20Reputation

ofsubcontractors

tobeusedfortheproject

X1

20Subcontractorplan

XX

219

244


Appen

dix

1.Prequ

alification

factorsin


tinu

ed)

MajorFactor

Minor

Factor/Year

Science

Direct

Web

ofScience

ASCE

Others

Organ

ization

Count

Rank

12

34

56

78

910

1112

1314

1516

1718

1920

2122

2324

2526

2728

2930

3132

3334

3536

Kumaraswamy

HatushandSkitmore

Al-Harbi

Laietal.

Nabiletal.

Plebankiewicz

Lametal.PadhiandMohapatra

MoroteandVila

AlzahraniandEmsley

Assaf

Shenetal.

Lametal.

Zenonas

LamandYu


Russell

HerbsmanandEllis

PotterandSanvidor


Sonmezetal.

Palaneeswaranand

Kumaraswamy

SinghandTiong

Abudayyehet.Al

Lietal.

Luelat.

Elyamanyand

Abdelrahman

MarshandFayek

Nguyen

Russell

ZedanandSkitmore

Salama

Australia

Tasmania

NCHRP

Timor

1996

1998

2000

2004

2007

2009

200920102012

2012

1994

2003

2007

2008

2011

1990

1990

1992

1995

1996

2002

2005

2006

2007

2007

2008

2010

2010

1985

1996

1997

2006

2000

1999

1994

2007

Esti-

mation

Fairestimation

XX

219

Schedule

ofpay

ments

XX

219

Advance

pay

ment

XX

219

StrategicBusiness

Location

ofhom

eoffi

cean

dman

-pow

eraccommodation

XX

XX

XX

615

Trainingactivitiesor

program

ssupportedbythebidder

orsustainab

ledevelop

mentof

human

resources

XX

XX

417

Thecontractor’stimean

dcost

savingconsiderations

X1

20

Postbusinessattitude

X1

20

Innovatemethod

XX

XX

X5

16

Strategic

awarenessan

dperspective

X1

20

Matchingstrategy

toacompan

y’s

situation

X1

20

Strategyim

plementation

X1

20

Suitab

ilityof

organizationstructure

X1

20

Motivationan

djobsatisfaction

X1

20

Technological

innovationab

ility

X1

20

Sustainab

ledevelop

mentof

technologyan

dR&D

X1

20

Marketresearch

andplanning

X1

20

Bid

Specific

Biddingstrategy

X1

20

Experiencesin

bidding

X1

20

Biddingresources

X1

20

Businessplan

X1

20

Total

1318

1113

2113

13721

2714

119

2012

2411

518

2019

2134

1524

3712

2819

1316

1621

68

9

245

Documents

FactorsInﬂuencingContractorPrequaliﬁcationProcesses ...construction industry. TheEconomy Watch (2010) stated that the construction industry is an important sector and that it is