The Economic Mechanisms of Artificial Intelligence Resources Affecting Green Risk Management: Empirical Evidence from Chinese Listed Firms

Yi Huang; Zhe Zhang; Sui Sun

doi:10.31181/ijes1512026277

Authors

Yi Huang School of Business, Huaiyin Normal University, Huaian 223300, Jiangsu, China Author https://orcid.org/0000-0001-6367-7105
Zhe Zhang School of Business, Qingdao University, Qingdao 266071, China Author https://orcid.org/0009-0006-2142-252X
Sui Sun School of Finance and Insurance, Guangxi University of Finance and Economics, Nanning 53003, China Author https://orcid.org/0009-0002-3280-3847

DOI:

https://doi.org/10.31181/ijes1512026277

Keywords:

Green Risk Management, Artificial Intelligence, Resource-based View, Strategic Allocation, Policy Synergy

Abstract

Against the backdrop of the digital economy, artificial intelligence (AI) has become a critical strategic resource for firms. Beyond enhancing economic performance, AI has opened new pathways for addressing environmental externalities. Drawing on the resource-based view (RBV), this paper examines the economic mechanisms through which AI resources influence firms’ green risk management (GRM) practices. The empirical results show that AI attention has a negative impact on GRM, whereas AI depth and AI-driven innovation exert positive effects. Further analysis indicates that AI technology attention and software depth are the main factors driving the negative impact. A resource crowding-out effect exists between AI attention and green attention, but this effect is weakened when financing constraints are low. Although no crowding-out effect is observed between AI depth and green depth, environmental uncertainty promotes the emergence of such an effect. At the same time, green innovation is identified as an indispensable mediating variable in the process through which AI attention and AI depth influence GRM. Further analysis confirms that environmental subsidies and tax incentives, as key economic policy instruments, can complement AI resources and effectively promote green risk management.

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References

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