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Best Value Contractor Selection in Road Construction Projects: ANP-Based Decision Support System

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Abstract

Based on the limitations of traditional procurement, this study uses analytical network process (ANP) for contractor selection. Using extensive literature review, best value (BV) contributing factors are identified. Experts are involved to get their feedback for shortlisting the identified factors. An ANP-based decision support system has been developed using data collected through a detailed questionnaire survey in the local construction industry for evaluating the selection process. Further, five case studies of completed road construction projects have been used to validate the decision support system. The findings indicate that in almost all the cases, the traditional procurement system, owing to its stringent prequalification measures, subliminally took into consideration the overall value proposition, and only one case study showed anomalies for which detailed reasoning is deliberated. This highlights the tendency of practitioners to overweigh the cost-based criteria, despite an established significance of other factors, treating the intangible value factors of quality, health and safety, environmental impact, etc. as less important. It reflects that the local construction industry attaches marginal value to qualitative factors. The construction industry will benefit from implementation of BV procurement system and a prolonged exposure may help improve its value system to realize the contribution of non-cost-based factors.

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Authors and Affiliations

  1. Department of Construction Engineering & Management (CE&M), NIT-SCEE, National University of Sciences & Technology (NUST), H-12, Islamabad, Pakistan

    Muhammad Hasnain, Muhammad Jamaluddin Thaheem & Fahim Ullah

Authors
  1. Muhammad Hasnain
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  2. Muhammad Jamaluddin Thaheem
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  3. Fahim Ullah
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Correspondence to Muhammad Jamaluddin Thaheem.

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Hasnain, M., Thaheem, M.J. & Ullah, F. Best Value Contractor Selection in Road Construction Projects: ANP-Based Decision Support System. Int J Civ Eng 16, 695–714 (2018). https://doi.org/10.1007/s40999-017-0199-2

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  • DOI: https://doi.org/10.1007/s40999-017-0199-2

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