The best-value procurement strategy is gaining the interest of federal and state agencies. The strategy increases the value added to a project for each dollar added. A new concept of best value, that is, a rational and flexible model based on expected performance, is presented. The model's flexibility is obvious in the selection of parameters to be included in the contractor selection process and in the determination of their weights. The model's rationality will be achieved through relating all awarded scores to the agency's expected performance. The establishment of the best-value model relies on the past record of the contractor's work for the agency as an indicator of qualification trend. This research incorporates prequalification as a first-level screening technique in selecting top contractor bids in the best-value procurement and then applies a rational scoring system in the final selection. Selection of the most appropriate contractor with the best qualifications for a given project will be based on contractor best value. Data are collected from groups of experts in the Minnesota Department of Transportation and processed through the analytic hierarchy process to establish the parameter weights. Although this research assists departments of transportation in selecting the best contractor, the results 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 the best value, and a methodology for quantifying the qualitative effect of subjective factors.
M. Abdelrahman et al., "Rational Best-Value Model based on Expected Performance," Transportation Research Record, no. 2081, pp. 46-55, National Research Council (U.S.), Jan 2008.
The definitive version is available at https://doi.org/10.3141/2081-05
Civil, Architectural and Environmental Engineering
Keywords and Phrases
Decision Theory; Hierarchical Systems
International Standard Serial Number (ISSN)
Article - Journal
© 2008 National Research Council (U.S.), All rights reserved.
01 Jan 2008