Best-Value Model based on Project Specific Characteristics
Best-value becomes a well known procurement practice in many states in the country. The objective of this transformation from the old practice of lowest bid to best-value is to increase the value added to the project for each dollar added. This paper discusses a new concept of best-value modeling that is unique and tailored to each project. The model uses records of past projects to obtain specific evaluation criteria, from which a best-value score is determined for each contractor. Primary parameters that impact contractor selection are identified and analyzed based on which best-value model is designed. Data are collected from groups of experts in the Minnesota Department of Transportation. Two application methods are used to assess the best-value: (1) the weighted average method; and (2) the analytic hierarchy process. Although the paper is written to assist government agencies in selecting the best contractor(s), the research results shared in this paper are relevant to both academics and practitioners. The paper provides practitioners with a tool for ranking contractors based on best-value and provides academics with selection parameters, a model to evaluate this best-value, and a methodology of quantifying the qualitative effect of subjective factors.
M. Abdelrahman et al., "Best-Value Model based on Project Specific Characteristics," Journal of Construction Engineering and Management, vol. 134, no. 3, pp. 179 - 188, American Society of Civil Engineers (ASCE), Mar 2008.
The definitive version is available at https://doi.org/10.1061/(ASCE)0733-9364(2008)134:3(179)
Civil, Architectural and Environmental Engineering
Keywords and Phrases
Bids; Contractors; Highway Construction; Parameters; Project Management
International Standard Serial Number (ISSN)
Article - Journal
© 2008 American Society of Civil Engineers (ASCE), All rights reserved.
01 Mar 2008
The writers would like to gratefully acknowledge the Minnesota Department of Transportation (MnDOT) for their support in funding this research and selecting model parameters.