利用机器学习进行企业社会责任 (CSR) 和环境、社会及治理 (ESG) 评估:从委员会过渡到气候

IF 3.3 2区 社会学 Q2 ENVIRONMENTAL SCIENCES
Ravichandran K. Subramaniam , Shyamala Dhoraisingam Samuel , Manjeevan Seera , Nafis Alam
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引用次数: 0

摘要

透明度和问责制是企业可持续发展的重要组成部分。本研究利用机器学习和实证分析来研究企业社会责任(CSR)委员会以及环境、社会和治理(ESG)倡议对企业可持续发展的影响。利用 2017-2021 年彭博终端数据,我们调查了财富 500 强企业的环境足迹、信息披露实践、风险概况和 ESG 基金承诺。主要研究结果表明,企业社会责任委员会对环境绩效有积极影响,随着时间的推移,环境责任也在增加。政策影响强调了在审计行业内合作优先考虑环境可持续性和解决气候风险披露审计问题的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Utilising machine learning for corporate social responsibility (CSR) and environmental, social, and governance (ESG) evaluation: Transitioning from committees to climate
Transparency and accountability are critical components of corporate sustainability. This study uses machine learning and empirical analysis to examine the influence of corporate social responsibility (CSR) committees and environmental, social, and governance (ESG) initiatives on corporate sustainability. Using 2017–2021 Bloomberg Terminal data, we investigated the environmental footprints, disclosure practices, risk profiles, and ESG fund commitments of Fortune 500 companies. Key findings indicate that CSR committees positively impact environmental performance, with an increase in environmental responsibility over time. Policy implications highlight the necessity for collaboration to prioritize environmental sustainability and address climate risk disclosure auditing within the audit profession.
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来源期刊
Sustainable Futures
Sustainable Futures Social Sciences-Sociology and Political Science
CiteScore
9.30
自引率
1.80%
发文量
34
审稿时长
71 days
期刊介绍: Sustainable Futures: is a journal focused on the intersection of sustainability, environment and technology from various disciplines in social sciences, and their larger implications for corporation, government, education institutions, regions and society both at present and in the future. It provides an advanced platform for studies related to sustainability and sustainable development in society, economics, environment, and culture. The scope of the journal is broad and encourages interdisciplinary research, as well as welcoming theoretical and practical research from all methodological approaches.
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