Study on the Dynamic Evolution of Transverse Collusive Bidding Behavior and Regulation Countermeasures Under the “Machine-Managed Bidding” System - Zongyuan Zhang; Jincan Liu; Zhitian Zhang; Bin Chen (Buildings)
The Machine-Managed Bidding (MMB) system is an innovative bidding mode implemented by the Chinese government to mitigate collusive bidding behavior. Prior studies have focused minimally on the bidding mechanism and the possible collusive bidding behavior under this mode. The objectives of this study are to analyze the bidding mechanism and the dynamic evolution of collusive bidding behavior under the MMB system and provide targeted regulation countermeasures. To this end, this study develops an evolutionary game model among collusion initiators, free bidders, and regulators, explores possible scenarios for evolutionarily stable strategies, and performs sensitivity analysis of critical parameters utilizing MATLAB software (Version R2024a) based on empirical data. Results indicate that: (1) The MMB model significantly mitigates vertical collusive bidding behavior but lacks measures for governing transverse collusive bidding; (2) The game model has five evolutionarily stable strategies, with the one where the collusion initiator adopting the “non-collude” strategy, the free bidder adopting the “bid” strategy, and the regulator adopting the “negative regulate” strategy being the optimal evolutionary stable strategy; (3) Decreasing the costs associated with preparing bid documents, enhancing supervision costs, increasing the technical complexity of collusive bidding, and expanding the total number of construction enterprises with high-credit and low-credit ratings can expedite the evolution of the three participants toward the optimal evolutionarily stable strategy. This study supplements current knowledge on the regulation of collusive bidding behavior and enriches the knowledge framework of the MMB model. This study also provides insights for policymakers to guarantee the smooth implementation of the MMB.