Research on the Game Strategy of Mutual Safety Risk Prevention and Control of Industrial Park Enterprises under Blockchain Technology

Systematic management of corporate safety risks in industrial parks has become a hot topic. And risk prevention and control mutual aid is a brand-new model in the risk and emergency management of the park. In the context of blockchain, how to incentivize enterprises to actively invest in safety risk prevention and control mutual aid has become a series of key issues facing government regulators. This paper innovatively combines Prospect Theory, Mental Accounting, and Evolutionary Game Theory to create a hypothetical model of limited rationality for the behavior of key stakeholders (core enterprises, supporting enterprises, and government regulatory departments) in mutual aid for safety risk prevention and control. Under the static prize punishment mechanism and dynamic punishment mechanism, the evolutionary stabilization strategy of stakeholders was analyzed, and numerical simulation analysis was performed through examples. The results show: (1) Mutual aid for risk prevention and control among park enterprises is influenced by various factors, including external and subjective elements, and evolves through complex evolutionary paths (e.g., reference points, value perception). (2) Government departments are increasingly implementing dynamic reward and punishment measures to address the shortcomings of static mechanisms. Government departments should dynamically adjust reward and punishment strategies, determine clearly the highest standards for rewards and punishments, and the combination of various incentives and penalties can significantly improve the effectiveness of investment decisions in mutual aid for safety risk prevention and control. (3) Continuously optimizing the design of reward and punishment mechanisms, integrating blockchain technology with management strategies to motivate enterprise participation, and leveraging participant feedback are strategies and recommendations that provide new insights for promoting active enterprise investment in mutual aid for safety risk prevention and control. The marginal contribution of this paper is to reveal the evolutionary pattern of mutual safety risk prevention and control behaviors of enterprises in chemical parks in the context of blockchain.