Identifying greenwashing in corporate‐social responsibility reports using natural‐language processing

Nina Gorovaia, Michalis Makrominas
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Abstract

A textual analysis of corporate‐social responsibility (CSR) reports reveals that companies engaged in environmental violations report differently from firms with a clean record. The violators issue longer, more positive and more frequent reports to relay environmental content that is more copious but less readable. The violator firms appear to modify their reporting practices right after committing a violation. The findings suggest that culpable firms exploit the current unregulated–unaudited state of CSR reporting as a means of greenwashing and call for institutional change. Our results are robust to a number of industry‐firm characteristics, including board composition, ownership dispersion and international presence.
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利用自然语言处理技术识别企业社会责任报告中的 "洗绿 "行为
对企业社会责任(CSR)报告的文本分析表明,有环境违法行为的公司与无不良记录的公司的报告方式不同。违规企业发布的报告篇幅更长、内容更积极、频率更高,传达的环境内容更丰富,但可读性更低。违规企业似乎会在违规后立即修改其报告做法。研究结果表明,应受处罚的企业利用企业社会责任报告目前不受监管和审计的现状,将其作为一种 "洗绿 "手段,并呼吁进行制度变革。我们的研究结果对一些行业-企业特征具有稳健性,包括董事会构成、所有权分散性和国际存在。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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