Evolutionary game analysis of ecological governance stakeholders in Caizihu national wetland park, China

The sustainability of national wetland parks is centered on coordinating game strategies among stakeholders. Considering China's Caizihu National Wetland Park, this study constructed a tripartite evolutionary game model of local governments, communities, and civil environmental protection organizations, and performed numerical simulation analysis using MATLAB software to further explore each stakeholder's strategic choices and key influencing factors. The results of the study showed that (1) among the eight possible strategy combinations, one stable equilibrium emerged wherein local governments adopt strict regulations, communities actively cooperate, and civil environmental organizations offer consistent support; (2) the reward and punishment mechanisms implemented by local governments play a decisive role in balancing stakeholder interests, significantly influencing the strategic behavior of both communities and civil organizations under strict regulatory conditions; and (3) factors such as high and low additional costs and loss of social reputation all have a significant impact on the ecological governance system of national wetland parks. Based on these findings, the study suggests that local governments should optimize the design of the reward and punishment system, communities should establish a sound participation mechanism, and civil environmental organizations should strengthen their reputation-management mechanisms. This study provides a theoretical basis and practical reference for sustainable development of national wetland parks.

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Publication Details

Journal
Scientific Reports
Published
2025-11-19
DOI
https://doi.org/10.1038/s41598-025-24817-8
Primary Topic
Evolutionary Game Theory and Cooperation
Type
article
Field-Weighted Citation Impact
0.00

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Evolutionary game analysis of ecological governance stakeholders in Caizihu national wetland park, China

Chunmei Mao, Qing Wang
Scientific Reports
Evolutionary Game Theory and Cooperation
article

Evolutionary game analysis of ecological governance stakeholders in Caizihu national wetland park, China

Chunmei Mao, Qing Wang
article en

Abstract

The sustainability of national wetland parks is centered on coordinating game strategies among stakeholders. Considering China's Caizihu National Wetland Park, this study constructed a tripartite evolutionary game model of local governments, communities, and civil environmental protection organizations, and performed numerical simulation analysis using MATLAB software to further explore each stakeholder's strategic choices and key influencing factors. The results of the study showed that (1) among the eight possible strategy combinations, one stable equilibrium emerged wherein local governments adopt strict regulations, communities actively cooperate, and civil environmental organizations offer consistent support; (2) the reward and punishment mechanisms implemented by local governments play a decisive role in balancing stakeholder interests, significantly influencing the strategic behavior of both communities and civil organizations under strict regulatory conditions; and (3) factors such as high and low additional costs and loss of social reputation all have a significant impact on the ecological governance system of national wetland parks. Based on these findings, the study suggests that local governments should optimize the design of the reward and punishment system, communities should establish a sound participation mechanism, and civil environmental organizations should strengthen their reputation-management mechanisms. This study provides a theoretical basis and practical reference for sustainable development of national wetland parks.

Scientific ReportsVol. 15(1)
Hohai University (CN)
Government of Jiangsu Province
Openalex Percentile: Top 55%
Evolutionary Game Theory and Cooperation
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Evolutionary game analysis of ecological governance stakeholders in Caizihu national wetland park, China — Chunmei Mao, Qing Wang · Scientific Reports (2025) | TGRS Research Map | TGRS