TY - JOUR
T1 - Natural disaster emergency response from a public policy perspective
T2 - a four-party evolutionary game among government, international organizations, healthcare institutions, and enterprises
AU - Wu, Baoling
AU - Zhang, Tao
AU - Wang, Xi
AU - Liang, Jiakai
AU - Liu, Mingke
AU - Zheng, Yifan
AU - Liang, Jiarui
AU - Chen, Zhengyu
N1 - Publisher Copyright:
Copyright © 2025 Wu, Zhang, Wang, Liang, Liu, Zheng, Liang and Chen.
PY - 2025
Y1 - 2025
N2 - Objective: This study utilizes evolutionary game theory to analyze the collaborative evolutionary mechanisms among governments, international organizations, healthcare institutions, and enterprises in natural disaster emergency response, aiming to explore how public policy can optimize the behavior of each stakeholder. Methods: A four-party evolutionary game model was constructed to examine strategy interactions and cooperative mechanisms among all parties. Numerical simulations were conducted to verify how key parameters affect the evolutionary outcomes. Results: The results indicate that government regulatory intensity, intervention strategies of international organizations, the philanthropic orientation of healthcare institutions, and the sense of corporate social responsibility among enterprises significantly influence the efficiency of emergency response. Numerical simulations further show that increasing government penalties, reducing international organizations’ dependency losses, improving the resource utilization efficiency of healthcare institutions, and raising both the cost of non-compliance and the market trust benefits for enterprises can encourage stakeholders to adopt more cooperative strategies that serve the public interest. Conclusion: This study reveals the “double-edged sword effect” of government regulation, the “time window effect” of international organizational intervention, the “multiplier effect” of resource efficiency in healthcare institutions, and the “trust-benefit mechanism” of corporate social responsibility, offering new insights for optimizing public policy.
AB - Objective: This study utilizes evolutionary game theory to analyze the collaborative evolutionary mechanisms among governments, international organizations, healthcare institutions, and enterprises in natural disaster emergency response, aiming to explore how public policy can optimize the behavior of each stakeholder. Methods: A four-party evolutionary game model was constructed to examine strategy interactions and cooperative mechanisms among all parties. Numerical simulations were conducted to verify how key parameters affect the evolutionary outcomes. Results: The results indicate that government regulatory intensity, intervention strategies of international organizations, the philanthropic orientation of healthcare institutions, and the sense of corporate social responsibility among enterprises significantly influence the efficiency of emergency response. Numerical simulations further show that increasing government penalties, reducing international organizations’ dependency losses, improving the resource utilization efficiency of healthcare institutions, and raising both the cost of non-compliance and the market trust benefits for enterprises can encourage stakeholders to adopt more cooperative strategies that serve the public interest. Conclusion: This study reveals the “double-edged sword effect” of government regulation, the “time window effect” of international organizational intervention, the “multiplier effect” of resource efficiency in healthcare institutions, and the “trust-benefit mechanism” of corporate social responsibility, offering new insights for optimizing public policy.
KW - emergency response
KW - evolutionary game
KW - multi-party collaboration
KW - natural disasters
KW - public policy
UR - https://www.scopus.com/pages/publications/105022118435
U2 - 10.3389/fpubh.2025.1595034
DO - 10.3389/fpubh.2025.1595034
M3 - Article
C2 - 41268415
AN - SCOPUS:105022118435
SN - 2296-2565
VL - 13
JO - Frontiers in Public Health
JF - Frontiers in Public Health
M1 - 1595034
ER -