Statistical Modeling of Number of Bidders in Highway Resurfacing and Widening Construction Projects

Lack of competition is a major challenge for transportation agencies in construction projects. As market conditions are volatile and less predictive, public highway agencies encounter a difficulty in obtaining the certain number of bidders for their projects. It is argued in the literature that the degree of competition for highway construction projects might be influenced by several factors, such as project types, geographic locations of projects, prices of resources, and construction volume. However, there has not been a comprehensive empirical study to explore the relationship between the number of bidders on highway projects and construction and economic market conditions. The objective of this study is to analyze the effects of the construction market and economic conditions on the degree of competition for highway projects. This research uses historical bid data of highway projects let in the State of Georgia, the United States, between 2005 and 2015. To achieve this objective, this paper conducts statistical regression modeling for identifying significant factors contributing to the degree of competition/number of bidders on resurfacing and widening projects. The findings of this study indicated that total contract price, number of pay item, duration, the annual total value of projects, architecture billings index, annual total number of projects, asphalt cement price index, and number of bids are significant factors that contribute to the degree of competition/number of bidders. The results of this research help public highway agencies establish bidding strategies for letting projects with an improved understanding of factors affecting the degree of competition for highway construction projects.


  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 670-679
  • Monograph Title: Construction Research Congress 2018: Infrastructure and Facility Management

Subject/Index Terms

Filing Info

  • Accession Number: 01683707
  • Record Type: Publication
  • ISBN: 9780784481295
  • Files: TRIS, ASCE
  • Created Date: Oct 4 2018 4:49PM