Utilising machine learning for corporate social responsibility (CSR) and environmental, social, and governance (ESG) evaluation: Transitioning from committees to climate
Ravichandran K. Subramaniam , Shyamala Dhoraisingam Samuel , Manjeevan Seera , Nafis Alam
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引用次数: 0
Abstract
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.
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.