Detecting Red-Flag Bidding Patterns in Low-Bid Procurement for Highway Projects with Pattern Mining

Abstract

Competitive bidding is a popular technique State Highway Agencies use for selecting contractors for public construction work. It intends to ensure that construction projects are awarded at the lowest price. However, public owners may award contracts at high prices due to collusive bid arrangements among bidders. The current practices and state-of-the-art methods of bid collusion detection are ineffective because they greatly rely on engineers’ estimates, which can be inaccurate, and the similarity in the cost structure of the bids, which experienced collusive bidders can manipulate. This study contributes to the body of knowledge with a novel data-driven collusion red-flag detection framework (CRFD) that utilizes pattern mining techniques and statistical tests for detecting contractors with a red-flag pattern, which refers to a significant difference in the winning rates of a contractor with and without the co-occurrence of other particular contractors. A mechanism is also proposed to incorporate potential, influential factors into the CRFD to increase the detection power or examine possible collusion between different scenarios. The proposed method is expected to assist project owners in detecting early signs of bid collusion and eventually help them significantly enhance their award decision-making.