基于第三方担保的ESG企业混合风险分散机制

IF 2.7 3区经济学 Q2 ECONOMICS

Managerial and Decision Economics Pub Date : 2025-07-21 DOI:10.1002/mde.70001

Jiaxin Zhuang, Yinglin Wang, Shengxu Shi

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引用次数: 0

摘要

为了减轻支持ESG披露的财务负担，本研究引入了第三方机构，并提出了两种替代模式：GFSL（先担保，后补贴）和SFGL（先补贴，后担保）。利用进化博弈论，分析战略决策，并通过数值模拟比较模型。结果表明，补贴上限和保费水平必须谨慎平衡。SFGL适用于外部影响最小的情况，而具有动态激励的FGS适用于强烈响应者。对于有机会的企业，优先考虑SFGL。本研究为优化ESG补贴策略，推进可持续金融发展提供了理论见解和实践指导。

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ESG Enterprise Hybrid Risk Diversification Mechanism Based on Third-Party Guarantee

To alleviate the financial burden of supporting ESG disclosures, this study introduces third-party institutions and proposes two alternative models: GFSL (Guarantee First, Subsidy Later) and SFGL (Subsidy First, Guarantee Later). Using evolutionary game theory, it analyzes strategic decisions and compares models through numerical simulations. Results show that subsidy caps and premium levels must be balanced carefully. SFGL suits cases with minimal external influence, while FGS with dynamic incentives fits strong responders. For opportunistic enterprises, SFGL is preferred. This study offers theoretical insights and practical guidance for optimizing ESG subsidy strategies and advancing sustainable finance.

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来源期刊

Managerial and Decision Economics Multiple-

CiteScore

1.40

自引率

18.20%

发文量

242

期刊介绍： Managerial and Decision Economics will publish articles applying economic reasoning to managerial decision-making and management strategy.Management strategy concerns practical decisions that managers face about how to compete, how to succeed, and how to organize to achieve their goals. Economic thinking and analysis provides a critical foundation for strategic decision-making across a variety of dimensions. For example, economic insights may help in determining which activities to outsource and which to perfom internally. They can help unravel questions regarding what drives performance differences among firms and what allows these differences to persist. They can contribute to an appreciation of how industries, organizations, and capabilities evolve.