Research on Optimal Logistics Configuration Based on Game Model

The concept of dynamic logistics alliances has emerged as an effective approach for enhancing the competitiveness of logistics enterprises, improving service efficiency, optimizing resource allocation, and facilitating the sharing of logistics resources. However, real-world outcomes of these alliances have often fallen short, leading to a consistently high failure rate. In response, an evolutionary game model was developed to address the interactive dynamics between functional logistics providers and resource logistics providers. This model analyzed the behavioral decision evolution paths and strategies for functional logistics providers, resource logistics providers, and the relationship between them. The analysis and discussion focused on key factors influencing alliance stability, revealing a positive correlation between collaboration benefits, penalty costs, trust coefficient, and alliance stability. Conversely, a negative relationship was observed with the cost conversion coefficient and learning absorption capacity. Additionally, the distribution coefficient was found to have a non-linear relationship with alliance stability, with an optimal distribution coefficient promoting the highest stability. Finally, the rationality of the evolutionary game relationships in dynamic logistics alliances was verified through numerical simulations and the case study of the Zhongtong Logistics Shengsu Express Alliance.