Evolutionary game analysis of collaborative strategies in fresh e-commerce and cold chain logistics: The role of incentive mechanisms and supervision policies

The sustainable development of fresh food e-commerce is highly dependent on the support of efficient cold chain logistics system, however, the obstacle of cooperation between fresh food e-commerce platforms and logistics enterprises is still one of the bottlenecks that need to be broken through globally. In this study, by constructing a three-party evolutionary game model including fresh food e-commerce platforms, logistics enterprises and regulators, we try to extend the traditional bilateral game model by invoking the regulatory dynamic mechanism, and design a payoff matrix incorporating corruption rate variables to accurately quantify the dynamic impact of commodity quality decay on the decision-making behaviors of multiple parties. Meanwhile, sensitivity analysis of 12 key parameters based on adaptive simulation algorithm reveals that the regulatory mechanism can effectively inhibit speculative behavior, and the system stability enhancement effect is especially prominent when the ratio of punishment to incentive exceeds 2.5:1; moderate economic incentives can optimize the stability of the cooperation, and its strength has an inverted U-shape relationship with the efficiency of the collaboration, while excessive incentives will have a negative impact; the evolutionary process of the convergence requires participants to have a reputation sensitivity threshold, i.e., the ability to effectively perceive and punish non-cooperative behaviors. This study provides a theoretical analysis tool for the collaborative governance of perishable commodity supply chains, and the related findings provide a reference basis for managers to optimize the design of regulatory strategies, the construction of incentive mechanisms, and the quality risk in the fresh food e-commerce ecosystem.