Abstract
The use of design/build (DB) contracting by transportation agencies has been steadily increasing as a project delivery system for large complex highway projects. However, moving to DB from traditional design-bid-build procurement can be a challenge. One significant barrier is gaining acceptance of a best-value selection process in which technical aspects of a proposal are considered separately and then combined with price to determine the winning proposal. These technical aspects mostly consist of qualitative criteria, thus making room for human errors or biases. Any perceived presence of bias or influence in the selection process can lead to public mistrust and protests by bidders. It is important that a rigorous quantitative mathematical analysis of the evaluation process be conducted to determine whether bias exists and to eliminate it. The paper discusses two potential sources of bias—evaluators and weighting model—in the DB selection process and presents mathematical models to detect and remove biases should they exist. A score normalization model deals with biases from the evaluators; then a graphical weight-space volume model and a Monte Carlo statistical sampling model are developed to remove biases from the weighting model. The models are then tested and demonstrated using results from the DB bridge replacement project for the collapsed Mississippi River bridge of Interstate 35W in Minneapolis.
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Acknowledgments
The writers wish to acknowledge the support and funding provided by the Construction and Materials Support Center (CMSC) at the University of Wisconsin-Madison in the preparation of this paper.
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Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 136 • Issue 8 • August 2010
Pages: 904 - 912
Copyright
© 2010 ASCE.
History
Received: Dec 12, 2008
Accepted: Jan 25, 2010
Published online: Jan 28, 2010
Published in print: Aug 2010
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