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.
Authors
- Nafis Alam (ORCID: https://orcid.org/0000-0002-7096-3692)
- Manjeevan Seera (ORCID: https://orcid.org/0000-0002-2797-3668)
- Shyamala Dhoraisingam Samuel (ORCID: https://orcid.org/0000-0001-5202-5355)
- Ravichandran K. Subramaniam (ORCID: https://orcid.org/0000-0001-9165-0196)
Institutions
- Monash University Malaysia (MY)
- Cancer Research Malaysia (MY)
- Subang Jaya Medical Centre (MY)
Publication Details
- Journal
- Sustainable Futures
- Published
- 2024-10-05
- DOI
- https://doi.org/10.1016/j.sftr.2024.100329
- Citations
- 12
- Primary Topic
- Corporate Social Responsibility Reporting
- Type
- article
- Field-Weighted Citation Impact
- 6.66
Funders
- Monash University Malaysia