The cooperative behavioral game of urban waste reduction network considering environmental cost-sharing.

This study aims to identify key intervention points for urban solid waste reduction and assign corresponding environmental responsibilities. It further examines how enterprises engage in waste reduction and cooperate with one another in this process. The research integrates Material Flow Analysis (MFA) and Life Cycle Assessment (LCA) to locate critical nodes for waste reduction. An evolutionary game model is developed, where enterprises are modeled as nodes in a scale-free network and interact with neighboring nodes. MATLAB simulations are conducted to evaluate the effects of cost-sharing, benefit allocation, penalty mechanisms, and spillover effects on cooperative behavior in waste reduction. The results reveal that moderate penalty mechanisms and positive spillover effects promote multi-subjects cooperative waste reduction. While cost-sharing and benefit allocation mechanisms also enhance cooperation, their effectiveness depends on maintaining parameter values within reasonable ranges. Furthermore, the impact of these mechanisms varies across networks of different scales, suggesting that a one-size-fits-all approach may be ineffective. This study provides a novel integration of MFA, LCA, and evolutionary game theory within a network framework to explore enterprise-level cooperation in waste reduction. It offers actionable insights into designing differentiated incentive mechanisms based on network characteristics, contributing to more effective urban waste management strategies.