How to Improve the Cooperation Mechanism of Emergency Rescue and Optimize the Cooperation Strategy in China: A Tripartite Evolutionary Game Model

Evolutionary game analysis for multi-level collaborative governance under public crisis in China: From a value perception perspective

In a risk society, the survival and development of humans are facing threats of complex and severe public crisis events. Public participation in collaborative governance (CG) of public crisis events is increasingly recognized as an important direction for the reform of the current and future emergency management system. Previous studies of CG have mainly focused on the macro level and ignored to address micro-level discussions of the behavioral strategy evolution of stakeholders. From a fresh value perception perspective, this study constructs an evolutionary game model to clarify the evolution mechanism of multi-level emergency CG. First, the value perception model is built based on Prospect Theory and Mental Accounting to optimize the traditional game matrix. Second, the evolutionary stability is analyzed to solve the system evolution law. Finally, numerical simulation is conducted in the case of Heilongjiang province, a main region of food and energy supply in China. Results showed that (1) the CG game system has a complex evolutionary path; (2) the behavior of game players is affected by perceived incomes and perceived costs; (3) compared with the reference value and the risk aversion coefficient of income accounts, game players are more sensitive to that of cost accounts; (4) enhancing the perceived value of public psychological satisfaction and government reputation is helpful for the long-term construction of CG. Overall, this study aims to highlight the potential utility of value perception in promoting effective implementations of CG and to provide new insights for the development of CG in China and other countries.

Allocation strategy of medical supplies during a public health emergency: a tripartite evolutionary game perspective

Ensuring the rational and orderly circulation of medical supplies during a public health emergency is crucial to quickly containing the further spread of the epidemic and restoring the order of rescue and treatment. However, due to the shortage of medical supplies, there are challenges to rationalizing the allocation of critical medical supplies among multiple parties with conflicting interests. In this paper, a tripartite evolutionary game model is constructed to study the allocation of medical supplies in the rescue environment of public health emergencies under conditions of incomplete information. The game's players include Government-owned Nonprofit Organizations (GNPOs), hospitals, and the government. By analyzing the equilibrium of the tripartite evolutionary game, this paper makes an in-depth study on the optimal allocation strategy of medical supplies. The findings indicate that: (1) the hospital should reasonably increase its willingness to accept the allocation plan of medical supplies, which can help medical supplies allocate more scientifically. (2) The government should design a reasonable reward and punishment mechanism to ensure the rational and orderly circulation of medical supplies, which can reduce the interference of GNPOs and hospitals in the allocation process of medical supplies. (3) Higher authorities should strengthen the supervision of the government and the accountability for loose supervision. The findings of this research can guide the government in promoting better circulation of medical supplies during public health emergencies by formulating more reasonable allocation schemes of emergency medical supplies, as well as incentives and penalties. At the same time, for GNPOs with limited emergency medical supplies, the equal allocation of emergency supplies is not the optimal solution to improve the efficiency of emergency relief, and it is simpler to achieve the goal of maximizing social benefits by allocating limited emergency resources to the demand points that match the degree of urgency. For example, in Corona Virus Disease 2019, emergency medical supplies should be prioritized for allocation to government-designated fever hospitals that are have a greater need for medical supplies and greater treatment capacity.

Multiobjective Emergency Resource Allocation under the Natural Disaster Chain with Path Planning

Public safety and health cannot be secured without the comprehensive recognition of characteristics and reliable emergency response schemes under the disaster chain. Distinct from emergency resource allocation that focuses primarily on a single disaster, dynamic response, periodic supply, and assisted decision-making are necessary. Therefore, we propose a multiobjective emergency resource allocation model considering uncertainty under the natural disaster chain. Resource allocation was creatively combined with path planning through the proposed multiobjective cellular genetic algorithm (MOCGA) and the improved A* algorithm with avoidance of unexpected road elements. Furthermore, timeliness, efficiency, and fairness in actual rescue were optimized by MOCGA. The visualization of emergency trips and intelligent avoidance of risk areas were achieved by the improved A* algorithm. The effects of logistics performance, coupling of disaster factors, and government regulation on emergency resource allocation were discussed based on different disaster chain scenarios. The results show that disruption in infrastructure support, cascading effect of disasters, and time urgency are additional environmental challenges. The proposed model and algorithm work in obtaining the optimal solution for potential regional coordination and resilient supply, with a 22.2% increase in the total supply rate. Cooperative allocation complemented by political regulation can be a positive action for successfully responding to disaster chains.