An Evolutionary Game and Simulation Study of Work Safety Governance and Its Impact on Long-Term Sustainability Under the Supervisory System

Wu Hu, Fujun Ma and Tianjv Li ()
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Wu Hu: School of Public Administration, Southwestern University of Finance and Economics, Chengdu 610074, China
Fujun Ma: School of Public Administration, Southwestern University of Finance and Economics, Chengdu 610074, China
Tianjv Li: School of Public Administration, Southwestern University of Finance and Economics, Chengdu 610074, China

Sustainability, 2025, vol. 17, issue 2, 1-28

Abstract: Work safety governance is a critical component of corporate ESG (Environmental, Social, and Governance) performance, particularly in high-risk industries. Effective safety supervision systems not only protect workers’ wellbeing, a key social metric in ESG frameworks, but also enhance corporate governance through improved risk management and regulatory compliance. The supervisory system represents a major institutional innovation in China’s approach to addressing increasingly complex work safety governance challenges. This study constructs an evolutionary game model involving the central government, local government, and high-risk enterprises to analyze the evolutionary characteristics of stakeholder behaviors. Through system simulation, we examine how key parameter changes affect the stability of system equilibrium points. Our findings reveal that (1) the current supervisory system effectively incentivizes both local governments to conduct safety supervision and high-risk enterprises to comply with safety investment requirements. (2) While government penalty levels do not affect strategy combinations, both insufficient and excessive penalties slow the system’s evolution toward optimal states. (3) Local governments tend to choose non-regulatory strategies when transfer payments and enterprise subsidies are inadequate. (4) Insufficient supervision intensity from the central government leads to local government non-regulation, and although this can be addressed by increasing supervision intensity, excessive supervision reduces the system’s evolution speed toward ideal states. Based on these findings, we propose policy recommendations for rational supervision intensity control, scientific reward–punishment mechanisms, and enhanced safety information transparency. This framework provides insights into the relationship between governance mechanisms and corporate long-term sustainability, which has been shown to improve ESG standards.

Keywords: Environmental, Social, and Governance Management; work safety governance; tripartite evolutionary game; supervisory system; evolutionary simulation; long-term sustainability; risk management (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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