Can artificial intelligence improve enterprise environmental performance: Evidence from China

被引:0
|
作者
wang, Junkai [1 ]
Wang, Aimeng [2 ]
Luo, Kaikai [3 ]
Nie, Yaoxiang [4 ]
机构
[1] School of Management, Lanzhou University, Lanzhou, China
[2] College of International Collaboration, Dalian Maritime University, Dalian, China
[3] School of International Politics and Economics, University of Chinese Academy of Social Sciences, Beijing, China
[4] Simon Business School, University of Rochester, Rochester,NY, United States
关键词
Carbon capture and utilization - Decentralized finance - Green economy;
D O I
10.1016/j.jenvman.2024.123079
中图分类号
学科分类号
摘要
Artificial intelligence needs to be embraced urgently by enterprises as a means to achieve green development and address the efficiency quagmire in the context of green, low-carbon and sustainable development. To estimate a corporation's pioneering progress in artificial intelligence, this paper outlines the use of web-crawling procedures to capture company related terms within yearly reports by exploring the approaches adapted to Artificial intelligence. Based on data from Chinese listed companies from 2010 to 2021, this paper empirically explores the impact and mechanism of artificial intelligence on corporate environmental performance. The results illustrate that firms' ecological performance can be greatly enhanced by the artificial intelligence with this idea remaining valid following various checks for determination strength. The results from mechanism-based assessment indicate that implementation of AI in businesses is useful for promoting green innovation process while mitigating financial risks that influences corporate environmental performance positively. The correlation between artificial intelligence and environmental performance is stronger concerning state ownership, heavily polluting, and stringent environmental regulation of firms according to heterogeneity analysis. The research shows the way that artificial intelligence affects ecosystems, alongside its mechanisms, fosters a new perspective upon artificial intelligence and environmental excellence. © 2024 Elsevier Ltd
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