Mobilizing social emergency forces to participate in urban flood response: an evolutionary game on dynamic rewards and punishments

Global climate change has exacerbated the frequency and severity of flooding in China. Because of its limited resources, the government requires the assistance of social emergency forces to provide rescue to affected areas. Existing research primarily focuses on static policy analysis, and there is a scarcity of examinations of dynamic incentive mechanisms for increasing social force involvement. An evolutionary game model was constructed between local government and social emergency forces in rescue collaboration, comparing the model stability under static and three dynamic reward and punishment mechanisms. Through numerical simulations, the strategy evolution process between both actors was studied under different conditions, including the effects of initial cooperative willingness, collaboration efficiency, maximum reward, and maximum punishment. The results show that the dynamic government intervention enhances the evolutionary stability, and optimizes for the limitations of the static mechanism effects. However, over-reliance on rewards decreases the likelihood of local government opting positive linkage strategy. In addition, the collaboration capability coefficient is more significant. Higher collaboration capability makes actors tend to choose positive strategies, which increases the enthusiasm of social forces to participate in urban flood rescue. On this basis, it is suggested that the emergency management system reform should strengthen the dynamic mechanism adjustment and establish a long-term collaboration system between the government and social emergency forces.