{"title":"Impact of regional artificial intelligence development on corporate environmental information","authors":"Yulin Wu , Jiahui Zhang , Xinyu Cai","doi":"10.1016/j.frl.2025.107413","DOIUrl":null,"url":null,"abstract":"<div><div>Using data from Shanghai and Shenzhen A-share listed companies between 2008 and 2022, this study investigates the impact of regional artificial intelligence (AI) development on the quality of corporate environmental information disclosure (EID). The findings indicate that regional AI development significantly enhances the quality of corporate EID. A series of robustness checks, such as replacing core explanatory and dependent variables and incorporating additional control variables, further support this conclusion. Additionally, heterogeneity analysis reveals that the positive influence of AI development on EID quality is more pronounced in Eastern regions and among firms in nonheavily-polluting industries. These results highlight AI's critical role in improving corporate information transparency and enhancing environmental governance, with notable regional and industry-specific differences.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"80 ","pages":"Article 107413"},"PeriodicalIF":7.4000,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Finance Research Letters","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1544612325006737","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
Using data from Shanghai and Shenzhen A-share listed companies between 2008 and 2022, this study investigates the impact of regional artificial intelligence (AI) development on the quality of corporate environmental information disclosure (EID). The findings indicate that regional AI development significantly enhances the quality of corporate EID. A series of robustness checks, such as replacing core explanatory and dependent variables and incorporating additional control variables, further support this conclusion. Additionally, heterogeneity analysis reveals that the positive influence of AI development on EID quality is more pronounced in Eastern regions and among firms in nonheavily-polluting industries. These results highlight AI's critical role in improving corporate information transparency and enhancing environmental governance, with notable regional and industry-specific differences.
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