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Promoting or inhibiting: The impact of artificial intelligence application on corporate environmental performance

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  • Liu, Yeshen
  • Wang, Beibei
  • Song, Zhe

Abstract

Existing research mainly focuses on the economic consequences of artificial intelligence (AI) applications for firms, while less attention is given to its non-economic effects. This study uses data from listed non-financial companies in China between 2008 and 2021, first comparing various methods to effectively measure firm-level AI application and then assessing its impact on corporate environmental performance. The findings indicate that AI application enhances the growth of environmental performance. This growth comes primarily through decreased operating costs, increased operational efficiency, and enhanced employee productivity. AI-powered growth is concentrated among manufacturing firms and is associated with larger fixed assets. Additionally, it is concentrated in firms with lower conventional low-skilled labor and is linked to higher unconventional high-skilled labor. We also find that AI application more effectively translates environmental performance into reputation and market value. Overall, this study offers valuable insights and implications for environmental governance in emerging market firms.

Suggested Citation

  • Liu, Yeshen & Wang, Beibei & Song, Zhe, 2025. "Promoting or inhibiting: The impact of artificial intelligence application on corporate environmental performance," International Review of Financial Analysis, Elsevier, vol. 97(C).
    • Handle: RePEc:eee:finana:v:97:y:2025:i:c:s1057521924008044
    DOI: 10.1016/j.irfa.2024.103872
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    as
    1. Opazo-Basáez, Marco & Monroy-Osorio, Juan Carlos & Marić, Josip, 2024. "Evaluating the effect of green technological innovations on organizational and environmental performance: A treble innovation approach," Technovation, Elsevier, vol. 129(C).
    2. Olga Hawn & Ioannis Ioannou, 2016. "Mind the gap: The interplay between external and internal actions in the case of corporate social responsibility," Strategic Management Journal, Wiley Blackwell, vol. 37(13), pages 2569-2588, December.
    3. Robert M. Solow, 1956. "A Contribution to the Theory of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 70(1), pages 65-94.
    4. Zhai, Shaoxuan & Liu, Zhenpeng, 2023. "Artificial intelligence technology innovation and firm productivity: Evidence from China," Finance Research Letters, Elsevier, vol. 58(PB).
    5. Siano, Alfonso & Vollero, Agostino & Conte, Francesca & Amabile, Sara, 2017. "“More than words”: Expanding the taxonomy of greenwashing after the Volkswagen scandal," Journal of Business Research, Elsevier, vol. 71(C), pages 27-37.
    6. Li, Xinze & Du, Kerui & Ouyang, Xiaoling & Liu, Lili, 2022. "Does more stringent environmental regulation induce firms' innovation? Evidence from the 11th Five-year plan in China," Energy Economics, Elsevier, vol. 112(C).
    7. Basu, Susanto & Fernald, John G. & Shapiro, Matthew D., 2001. "Productivity growth in the 1990s: technology, utilization, or adjustment?," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 55(1), pages 117-165, December.
    8. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    9. Li, Chengming & Xu, Yang & Zheng, Hao & Wang, Zeyu & Han, Haiting & Zeng, Liangen, 2023. "Artificial intelligence, resource reallocation, and corporate innovation efficiency: Evidence from China's listed companies," Resources Policy, Elsevier, vol. 81(C).
    10. Pournader, Mehrdokht & Ghaderi, Hadi & Hassanzadegan, Amir & Fahimnia, Behnam, 2021. "Artificial intelligence applications in supply chain management," International Journal of Production Economics, Elsevier, vol. 241(C).
    11. Yang, Chih-Hai, 2022. "How Artificial Intelligence Technology Affects Productivity and Employment: Firm-level Evidence from Taiwan," Research Policy, Elsevier, vol. 51(6).
    12. Zhang, Qi & Yu, Zhi & Kong, Dongmin, 2019. "The real effect of legal institutions: Environmental courts and firm environmental protection expenditure," Journal of Environmental Economics and Management, Elsevier, vol. 98(C).
    13. Dongmin Kong & Jia Liu & Yanan Wang & Ling Zhu, 2024. "Employee Stock Ownership Plans and Corporate Environmental Engagement," Journal of Business Ethics, Springer, vol. 189(1), pages 177-199, January.
    14. Li, Qiang & Wang, Shengying & He, Zichun & Li, Hanqiao & Xiang, Erwei, 2023. "Does stock market index adjustment affect environmental information disclosure? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 87(C).
    15. Wang, Zongrun & Zhang, Taiyu & Ren, Xiaohang & Shi, Yukun, 2024. "AI adoption rate and corporate green innovation efficiency: Evidence from Chinese energy companies," Energy Economics, Elsevier, vol. 132(C).
    16. Alexander Kopka & Dirk Fornahl, 2024. "Artificial intelligence and firm growth — catch-up processes of SMEs through integrating AI into their knowledge bases," Small Business Economics, Springer, vol. 62(1), pages 63-85, January.
    17. Cheng, Weixuan & Li, Cheng & Zhao, Tianjiao, 2024. "The stages of enterprise digital transformation and its impact on internal control: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 92(C).
    18. Kate Crawford, 2024. "Generative AI’s environmental costs are soaring — and mostly secret," Nature, Nature, vol. 626(8000), pages 693-693, February.
    19. Wei Shi & Brian L. Connelly & Jeremy D. Mackey & Abhinav Gupta, 2019. "Placing their bets: The influence of strategic investment on CEO pay‐for‐performance," Strategic Management Journal, Wiley Blackwell, vol. 40(12), pages 2047-2077, December.
    20. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    21. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 115-146, National Bureau of Economic Research, Inc.
    22. Wang, Fangjun & Sun, Junqin & Liu, Yang Stephanie, 2019. "Institutional pressure, ultimate ownership, and corporate carbon reduction engagement: Evidence from China," Journal of Business Research, Elsevier, vol. 104(C), pages 14-26.
    23. Ming-Hui Huang & Roland T. Rust, 2021. "A strategic framework for artificial intelligence in marketing," Journal of the Academy of Marketing Science, Springer, vol. 49(1), pages 30-50, January.
    24. Marco Opazo-Basáez & Juan Carlos Monroy-Osorio & Josip Marić, 2024. "Evaluating the Effect of Green Technological Innovations on Organizational and Environmental Performance: A Treble Innovation Approach," Post-Print hal-04432410, HAL.
    25. Saumyaranjan Sahoo & Anil Kumar & Arvind Upadhyay, 2023. "How do green knowledge management and green technology innovation impact corporate environmental performance? Understanding the role of green knowledge acquisition," Business Strategy and the Environment, Wiley Blackwell, vol. 32(1), pages 551-569, January.
    26. Milan Miric & Nan Jia & Kenneth G. Huang, 2023. "Using supervised machine learning for large‐scale classification in management research: The case for identifying artificial intelligence patents," Strategic Management Journal, Wiley Blackwell, vol. 44(2), pages 491-519, February.
    27. Richard Whittington & Basak Yakis-Douglas & Kwangwon Ahn, 2016. "Cheap talk? Strategy presentations as a form of chief executive officer impression management," Strategic Management Journal, Wiley Blackwell, vol. 37(12), pages 2413-2424, December.
    28. Ouyang, Xiaoling & Fang, Xingming & Cao, Yan & Sun, Chuanwang, 2020. "Factors behind CO2 emission reduction in Chinese heavy industries: Do environmental regulations matter?," Energy Policy, Elsevier, vol. 145(C).
    29. Erik Brynjolfsson & Tom Mitchell & Daniel Rock, 2018. "What Can Machines Learn, and What Does It Mean for Occupations and the Economy?," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 43-47, May.
    30. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    31. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
    32. Pan, Yinghao & Zhang, Chao-Chao & Lee, Chien-Chiang & Lv, Suxiang, 2024. "Environmental performance evaluation of electric enterprises during a power crisis: Evidence from DEA methods and AI prediction algorithms," Energy Economics, Elsevier, vol. 130(C).
    33. Murtaza Hussain & Shaohua Yang & Umer Sahil Maqsood & R. M. Ammar Zahid, 2024. "Tapping into the green potential: The power of artificial intelligence adoption in corporate green innovation drive," Business Strategy and the Environment, Wiley Blackwell, vol. 33(5), pages 4375-4396, July.
    34. Wenbin Long & Le Luo & Hongfeng Sun & Qiqi Zhong, 2023. "Does going abroad lead to going green? Firm outward foreign direct investment and domestic environmental performance," Business Strategy and the Environment, Wiley Blackwell, vol. 32(1), pages 484-498, January.
    35. Joel Bothello & Ioannis Ioannou & Vlad‐Andrei Porumb & Yasemin Zengin‐Karaibrahimoglu, 2023. "CSR decoupling within business groups and the risk of perceived greenwashing," Strategic Management Journal, Wiley Blackwell, vol. 44(13), pages 3217-3251, December.
    36. Alvaro Cuervo-Cazurra & Saptarshi Purkayastha & Kannan Ramaswamy, 2023. "Variations in the Corporate Social Responsibility-Performance Relationship in Emerging Market Firms," Organization Science, INFORMS, vol. 34(4), pages 1626-1650, July.
    37. Shaojian Chen & Hui Mao & Junqin Sun, 2022. "Low-Carbon City Construction and Corporate Carbon Reduction Performance: Evidence From a Quasi-Natural Experiment in China," Journal of Business Ethics, Springer, vol. 180(1), pages 125-143, September.
    38. Sowa, Konrad & Przegalinska, Aleksandra & Ciechanowski, Leon, 2021. "Cobots in knowledge work," Journal of Business Research, Elsevier, vol. 125(C), pages 135-142.
    39. Wang, Linhui & Wang, Hui & Cao, Zhanglu & He, Yongda & Dong, Zhiqing & Wang, Shixiang, 2022. "Can industrial intellectualization reduce carbon emissions? — Empirical evidence from the perspective of carbon total factor productivity in China," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    40. Zhang, Dongyang, 2022. "Green financial system regulation shock and greenwashing behaviors: Evidence from Chinese firms," Energy Economics, Elsevier, vol. 111(C).
    41. Ye, Fei & Ouyang, You & Li, Yina, 2023. "Digital investment and environmental performance: The mediating roles of production efficiency and green innovation," International Journal of Production Economics, Elsevier, vol. 259(C).
    42. Hu, Shuo & Wang, Ailun & Du, Kerui, 2023. "Environmental tax reform and greenwashing: Evidence from Chinese listed companies," Energy Economics, Elsevier, vol. 124(C).
    43. Po-Hsuan Hsu & Hao Liang & Pedro Matos, 2023. "Leviathan Inc. and Corporate Environmental Engagement," Management Science, INFORMS, vol. 69(12), pages 7719-7758, December.
    44. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation," NBER Working Papers 24449, National Bureau of Economic Research, Inc.
    45. Zhang, Ning & Huang, Xuhui & Qi, Chao, 2022. "The effect of environmental regulation on the marginal abatement cost of industrial firms: Evidence from the 11th Five-Year Plan in China," Energy Economics, Elsevier, vol. 112(C).
    46. Jordi Surroca & Josep A. Tribó & Sandra Waddock, 2010. "Corporate responsibility and financial performance: the role of intangible resources," Strategic Management Journal, Wiley Blackwell, vol. 31(5), pages 463-490, May.
    47. Moyer, Jonathan D. & Hughes, Barry B., 2012. "ICTs: Do they contribute to increased carbon emissions?," Technological Forecasting and Social Change, Elsevier, vol. 79(5), pages 919-931.
    48. Patrick Mikalef & Kieran Conboy & Jenny Eriksson Lundström & Aleš Popovič, 2022. "Thinking responsibly about responsible AI and ‘the dark side’ of AI," European Journal of Information Systems, Taylor & Francis Journals, vol. 31(3), pages 257-268, May.
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    More about this item

    Keywords

    Artificial intelligence application; Environmental performance; Operating costs; Operational efficiency; Employee productivity;
    All these keywords.

    JEL classification:

    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management

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