“Good Citizen” or “Good Actor”: The Asymmetric Impact of Artificial Intelligence on Firms' Tactical Environmental Information Disclosure

ABSTRACT Sustainable development necessitates “good citizens” rather than “good actors” in environmental governance. This study employs data on Chinese A‐share listed companies spanning 2012 to 2023 and finds that artificial intelligence (AI) exerts a suppressive impact on corporate tactical environmental information disclosure (TEID). Specifically, AI exerts a linear suppressive effect on excessive tactical disclosure and greenwashing behaviors, whereas it exhibits an inverted U‐shaped relationship with brownwashing, initially promoting and then inhibiting such behaviors. The underlying mechanisms operate through three channels: enhancing internal control quality, alleviating financing constraints, and mitigating information asymmetry. Government regulation amplifies these suppressive effects, whereas public demands only reinforce the inhibition of excessive tactical disclosure and greenwashing. Heterogeneous analysis reveals that under strong regulatory regimes, the synergy between AI and regulation primarily enhances internal control quality and mitigates information asymmetry; under weak regulation, their interaction mainly alleviates financing constraints. The suppressive effects are more pronounced for high‐pollution, manufacturing, and technology‐intensive firms. This study contributes theoretical insights into AI's role in corporate environmental governance and offers targeted policy implications for governments when formulating environmental information disclosure regulations.

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Publication Details

Journal
Business Strategy and the Environment
Published
2025-12-03
DOI
https://doi.org/10.1002/bse.70433
Primary Topic
Corporate Social Responsibility Reporting
Type
article
Field-Weighted Citation Impact
0.00
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article

“Good Citizen” or “Good Actor”: The Asymmetric Impact of Artificial Intelligence on Firms' Tactical Environmental Information Disclosure

Majid Murad, Ximeng Jia, Xinxin Yu, Tao Wang et al.
Business Strategy and the Environment
Corporate Social Responsibility Reporting
article

“Good Citizen” or “Good Actor”: The Asymmetric Impact of Artificial Intelligence on Firms' Tactical Environmental Information Disclosure

Majid Murad, Ximeng Jia, Xinxin Yu, Tao Wang, Chen Chen
article en

Abstract

ABSTRACT Sustainable development necessitates “good citizens” rather than “good actors” in environmental governance. This study employs data on Chinese A‐share listed companies spanning 2012 to 2023 and finds that artificial intelligence (AI) exerts a suppressive impact on corporate tactical environmental information disclosure (TEID). Specifically, AI exerts a linear suppressive effect on excessive tactical disclosure and greenwashing behaviors, whereas it exhibits an inverted U‐shaped relationship with brownwashing, initially promoting and then inhibiting such behaviors. The underlying mechanisms operate through three channels: enhancing internal control quality, alleviating financing constraints, and mitigating information asymmetry. Government regulation amplifies these suppressive effects, whereas public demands only reinforce the inhibition of excessive tactical disclosure and greenwashing. Heterogeneous analysis reveals that under strong regulatory regimes, the synergy between AI and regulation primarily enhances internal control quality and mitigates information asymmetry; under weak regulation, their interaction mainly alleviates financing constraints. The suppressive effects are more pronounced for high‐pollution, manufacturing, and technology‐intensive firms. This study contributes theoretical insights into AI's role in corporate environmental governance and offers targeted policy implications for governments when formulating environmental information disclosure regulations.

Business Strategy and the Environment
Guangdong University of Technology (CN), Sichuan University (CN), Guangzhou University (CN), Tongling University (CN)
Openalex Percentile: Top 47%
Corporate Social Responsibility Reporting
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