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Bashford, H H, Walsh, K D and Sawhney, A (2005) Production System Loading–Cycle Time Relationship in Residential Construction. Journal of Construction Engineering and Management, 131(01), 15–22.

Chen, Z, Li, H and Wong, C T C (2005) {[}EnvironalPlanning{]}: Analytic Network Process Model for Environmentally Conscious Construction Planning. Journal of Construction Engineering and Management, 131(01), 92–101.

Chester, M and Hendrickson, C (2005) Cost Impacts, Scheduling Impacts, and the Claims Process during Construction. Journal of Construction Engineering and Management, 131(01), 102–7.

Dzeng, R J, Tserng, H P and Wang, W C (2005) Automating Schedule Review for Expressway Construction. Journal of Construction Engineering and Management, 131(01), 127–36.

Elazouni, A M, Ali, A E and Abdel-Razek, R H (2005) Estimating the Acceptability of New Formwork Systems Using Neural Networks. Journal of Construction Engineering and Management, 131(01), 33–41.

Horman, M J and Kenley, R (2005) Quantifying Levels of Wasted Time in Construction with Meta-Analysis. Journal of Construction Engineering and Management, 131(01), 52–61.

Kaiser, M J, Pulsipher, A G and Byrd, R C (2005) Cost of Abrasive Cutting in Decommissioning Operations in the Gulf of Mexico. Journal of Construction Engineering and Management, 131(01), 137–48.

Kaiser, M J, Pulsipher, A G and Martin, J (2005) Cost of Site Clearance and Verification Operations in the Gulf of Mexico. Journal of Construction Engineering and Management, 131(01), 117–26.

Oliveros, A V O and Fayek, A R (2005) Fuzzy Logic Approach for Activity Delay Analysis and Schedule Updating. Journal of Construction Engineering and Management, 131(01), 42–51.

Singh, D and Tiong, R L K (2005) A Fuzzy Decision Framework for Contractor Selection. Journal of Construction Engineering and Management, 131(01), 62–70.

  • Type: Journal Article
  • Keywords: Contractors; Fuzzy sets; Evaluation; Decision making; Construction industry;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2005)131:1(62)
  • Abstract:
    Contractor selection is the process of selecting the most appropriate contractor to deliver the project as specified so that the achievement of the best value for money is ensured. Construction clients are becoming more aware of the fact that selection of a contractor based on tender price alone is quite risky and may lead to the failure of the project in terms of time delay and poor quality standards. Evaluation of contractors based on multiple criteria is, therefore, becoming more popular. Contractor selection in a multicriteria environment is, in essence, largely dependent on the uncertainty inherent in the nature of construction projects and subjective judgment of decision makers (DMs). This paper presents a systematic procedure based on fuzzy set theory to evaluate the capability of a contractor to deliver the project as per the owner’s requirements. The notion of Shapley value is used to determine the global value or relative importance of each criterion in accomplishing the overall objective of the decision-making process. The research reported upon forms part of a larger study that aims to develop a fuzzy decision model for construction contractor selection involving investigating multiple criteria selection tendencies of construction clients, relationship among decision criteria, and construction clients’ preferences of criteria in the contractor selection process. An illustration with a bid evaluation exercise is presented to demonstrate the data requirements and the application of the method in selecting the most appropriate contractor for the project under uncertainty. The proposed model is not intended to supplant the work of decision-making teams in the contractor selection process, but rather to help them make quality evaluations of the available candidate contractors. One major advantage of the proposed method is that it makes the selection process more systematic and realistic as the use of fuzzy set theory allows the DMs to express their assessment of contractors’ performance on decision criteria in linguistic terms rather than as crisp values.

Tatum, C B (2005) Building Better: Technical Support for Construction. Journal of Construction Engineering and Management, 131(01), 23–32.

Yiu, C Y, Ho, H K, Lo, S M and Hu, B Q (2005) Performance Evaluation for Cost Estimators by Reliability Interval Method. Journal of Construction Engineering and Management, 131(01), 108–16.

Zhang, X (2005) Critical Success Factors for Public–Private Partnerships in Infrastructure Development. Journal of Construction Engineering and Management, 131(01), 3–14.

Zhang, X (2005) Paving the Way for Public–Private Partnerships in Infrastructure Development. Journal of Construction Engineering and Management, 131(01), 71–80.

Zheng, D X M, Ng, S T and Kumaraswamy, M M (2005) Applying Pareto Ranking and Niche Formation to Genetic Algorithm-Based Multiobjective Time–Cost Optimization. Journal of Construction Engineering and Management, 131(01), 81–91.