Network Theory–Based Approach to Data-Driven Assessment of Bidding Competition in Highway Construction

Abstract

Competitive bidding in design-bid-build contracts holds the potential to lower bid prices, maximize project outcomes, and promote growth in the construction industry. However, these potential benefits of competitive bidding are contingent upon adequate competition among bidders. State highway agencies (SHAs) traditionally evaluate competition levels predominantly based on the number of bidders, neglecting other key elements such as bidders’ competitiveness. Moreover, little research focuses on addressing this limitation. This study proposes a novel data-driven network theory approach to measure competition from the owners’ perspective. Specifically, competition is modeled as a bidirected network of connected bidders using their past winning and losing records. We propose different measures of contractors to provide unique insights into the competitiveness of the bidders. These centrality measures are further correlated with the bidding performance using Spearman’s rank correlation coefficient. Our findings demonstrate that these proposed centrality measures bear stronger correlations with bidding performance than the number of bidders. By employing this novel approach, SHAs can better understand contractor competitiveness and competition levels during the project-letting phase.