Evolutionary game theory-based system dynamics modeling for community solid waste classification in China

To increase the utilization rate of renewable resources, China will widely implement solid waste classification in the next few years. However, waste classification in many communities has been placed on hold. This study establishes a multi-player evolutionary game among the government, community, and residents to explore the real reasons for the implementation difficulties. The evolutionary game is simulated by adopting system dynamics to analyze the effectiveness of various strategies on the game process and game equilibrium to provide references for the government to formulate macro policies. We show that fluctuations in a static penalty scheme make formulating effective strategies difficult for the government. By contrast, a dynamic penalty scheme can effectively eliminate fluctuations. Furthermore, the optimal dynamic penalty-subsidy scheme features an ideal evolutionarily stable strategy where the optimal strategy for a community and its residents is to implement the waste classification system and obey the rules, respectively. • Process of implementing the community garbage classification system in China. • Multi-player evolutionary game among the government, community, and residents. • System dynamics simulates the changes and interactions of stakeholders' strategies. • Fluctuations make it difficult for the government to formulate effective strategies. • Eliminate the fluctuations, stabilize the game and features an ideal evolutionarily stable strategy in the proposed scheme.