风险投资与社会责任行为:基于进化博弈的方法

IF 1.7 4区 工程技术 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Complexity Pub Date : 2025-05-11 DOI:10.1155/cplx/6661472
Yuzhong Lu, Guillermo A. Buitrago, Meng Li
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引用次数: 0

摘要

本文引入了一种基于进化博弈的新模型,探讨了风险投资机构与被投资企业在企业社会责任实践中的动态相互作用,并重点研究了政府监管的调节作用。随着企业社会责任在风投支持的公司生态系统中日益突出,了解这些动态至关重要。通过数值模拟验证,该模型考察了在有和没有政府监督的情况下的系统演化。主要发现如下:(1)当风险投资优先考虑长期投资策略时,风险投资支持的公司更有可能采取企业社会责任实践,而以股东价值为中心的短期战略阻碍了企业社会责任的努力;(2)风险投资股权比例、企业社会责任成本、企业社会责任收益等因素显著影响企业社会责任采纳;(3)政府激励可以促进企业社会责任,加速向理想结果趋同,但影响有限。本研究促进了对风险投资与企业社会责任关系的理解,为促进负责任的投资和商业实践提供了理论见解和实践建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Venture Capital and Social Responsibility Behavior: An Evolutionary Game-Based Approach

Venture Capital and Social Responsibility Behavior: An Evolutionary Game-Based Approach

This study introduces a novel evolutionary game-based model to explore the dynamic interplay between venture capital (VC) institutions and their invested firms in adopting corporate social responsibility (CSR) practices, with a focus on the moderating role of government supervision. With CSR gaining prominence in VC-backed firm ecosystems, understanding these dynamics is critical. Verified through numerical simulations, the model examines system evolution under scenarios with and without government supervision. Key findings include the following: (1) VC-backed firms are more likely to adopt CSR practices when VCs prioritize long-term investment strategies, whereas short-term strategies centered on shareholder value hinder CSR efforts; (2) factors such as VC equity share, CSR costs, and benefits significantly influence CSR adoption; and (3) government incentives can promote CSR and accelerate convergence toward ideal outcomes, though with limited impact. This research advances the understanding of the VC-CSR relationship, offering theoretical insights and practical recommendations to foster responsible investment and business practices.

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来源期刊
Complexity
Complexity 综合性期刊-数学跨学科应用
CiteScore
5.80
自引率
4.30%
发文量
595
审稿时长
>12 weeks
期刊介绍: Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.
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