Dual-layer coordination framework for urban mining: Integration of social network analysis and multi-agent systems

Urban mining recovery and reuse involve a complex system of multiple agents with independent interests across different stages. This study examines the dual-layer coordination among four key agents—supplying, recycling and sorting, reuse, and regulatory—using multi-period game theory and a heterogeneous social network model. By integrating these models with a multi-agent based simulation (MABS), we achieve bidirectional feedback and dynamic interactions. Our analysis under various policy scenarios reveals that non-cooperative strategies often dominate, but adjusting price schemes can effectively stimulate cooperative strategies among recycling and sorting agents with limited impact on other agents. Policy effects also vary based on agent personality matches. A gradual subsidy phase-out mechanism enhances the stability of collaborative evolution among recycling and sorting agents, while technical threshold subsidies promote technological learning, driving refined processing by reuse agents. Enhancing network effects through adjusting interaction willingness and market entry and exit rules increases network link probabilities but may counteract collaborative behaviors, whereas small groups within a certain range show better coordination and stability. In this study, a solid basis is laid for future research and implementation of effective multi-agent behaviors in urban mining, offering a valuable reference for stakeholders in urban resource management and policy-making.