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ESG-washing detection in corporate sustainability reports

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  • Lagasio, Valentina

Abstract

This study introduces the ESG-washing Severity Index (ESGSI) for quantitatively assessing discrepancies between portrayed and actual sustainability practices in corporate disclosures. Using advanced Natural Language Processing (NLP) techniques, we analyze sustainability reports from 749 listed companies, integrating sentiment analysis with the frequency of sustainability terms to calculate the ESGSI. Our findings reveal significant variation in ESG-washing practices across industries and geographical regions. The ESGSI serves as a critical tool for stakeholders and policymakers, highlighting the need for stricter sustainability reporting standards and more effective regulatory frameworks to combat ESG-washing. This study contributes to the growing body of literature on corporate sustainability and provides practical implications for investors, corporate managers, and policymakers in evaluating and improving ESG practices and disclosures.

Suggested Citation

  • Lagasio, Valentina, 2024. "ESG-washing detection in corporate sustainability reports," International Review of Financial Analysis, Elsevier, vol. 96(PB).
    • Handle: RePEc:eee:finana:v:96:y:2024:i:pb:s1057521924006744
    DOI: 10.1016/j.irfa.2024.103742
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