Strategic dynamics of local governments in regional collaborative governance: An evolutionary game theory analysis of haze pollution response in the Fen-Wei Plain, China

Regional collaborative governance has become a key strategy for environmental protection, especially in reducing transboundary pollution transfer. This study, set against the backdrop of environmental governance in China's Fen-Wei Plain, employs evolutionary game theory to deeply analyze the strategic choices of local governments in managing haze pollution. We developed a model incorporating 14 key variables to systematically explore the emission reduction strategies of local governments under various policy environments. Through numerical simulations, we not only validate the effectiveness of the model but also focuses on how incentives and punishments from the central government influence the stability of local governments adopting a "strict enforcement" strategy. We find that appropriate incentives from the central government can significantly enhance the tendency of local governments to choose a "strict enforcement" strategy for emission reduction. Under certain conditions, whether adopting "strict enforcement" or "superficial enforcement," both can lead to an Evolutionarily Stable Strategy (ESS). Moreover, the intensity of rewards and penalties from the central government and the benefits of collaborative governance by local governments are key factors determining the stability of strategies. Our findings underscore the importance of establishing performance-oriented incentive mechanisms, refining reward and punishment measures, and focusing on sustainable and adaptable governance strategies. The strategic recommendations provided by this study offer important guidance for balancing incentives and punishments, thereby stimulating local government enthusiasm for governance, which supports high-quality environmental protection and sustainable development goals.