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The role of AI capabilities in environmental management: Evidence from USA firms

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Listed:
  • Jiao, Anqi
  • Lu, Juntai
  • Ren, Honglin
  • Wei, Jia

Abstract

This study investigates the role of Artificial Intelligence (AI) capabilities in influencing firms' greenwashing behaviors. We find a robust negative association between firms' AI capabilities and unrepresentative environmental disclosure. An instrumental variable approach is employed to establish causality. The effects are more pronounced for firms (1) with a greater exposure to regulatory climate risk, (2) managed by Republican-leaning managers, (3) with stronger governance structures, (4) possessing greater product market pricing power, (5) operating in multiple regions, and (6) with CEOs with higher pay-for-performance sensitivity. We further demonstrate that AI capabilities aid firms in transitioning to green operations through engaging in green and clean innovation. Finally, we find that AI capabilities correlate with lower greenhouse gas emissions. Overall, our findings shed light on the real impact of AI-related technologies in the energy industry.

Suggested Citation

  • Jiao, Anqi & Lu, Juntai & Ren, Honglin & Wei, Jia, 2024. "The role of AI capabilities in environmental management: Evidence from USA firms," Energy Economics, Elsevier, vol. 134(C).
    • Handle: RePEc:eee:eneeco:v:134:y:2024:i:c:s014098832400361x
    DOI: 10.1016/j.eneco.2024.107653
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    as
    1. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2022. "Artificial Intelligence and Jobs: Evidence from Online Vacancies," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 293-340.
    2. Kent Walker & Fang Wan, 2012. "The Harm of Symbolic Actions and Green-Washing: Corporate Actions and Communications on Environmental Performance and Their Financial Implications," Journal of Business Ethics, Springer, vol. 109(2), pages 227-242, August.
    3. Bronwyn H. Hall & Adam Jaffe & Manuel Trajtenberg, 2005. "Market Value and Patent Citations," RAND Journal of Economics, The RAND Corporation, vol. 36(1), pages 16-38, Spring.
    4. Christopher Marquis & Michael W. Toffel & Yanhua Zhou, 2016. "Scrutiny, Norms, and Selective Disclosure: A Global Study of Greenwashing," Organization Science, INFORMS, vol. 27(2), pages 483-504, April.
    5. Leonid Kogan & Dimitris Papanikolaou & Amit Seru & Noah Stoffman, 2017. "Technological Innovation, Resource Allocation, and Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(2), pages 665-712.
    6. Antoine Dechezleprêtre & Cal B. Muckley & Parvati Neelakantan, 2021. "Is firm-level clean or dirty innovation valued more?," The European Journal of Finance, Taylor & Francis Journals, vol. 27(1-2), pages 31-61, January.
    7. Joanna Ho & Feng Tian & Anne Wu & Sean Xin Xu, 2017. "Seeking Value Through Deviation? Economic Impacts of IT Overinvestment and Underinvestment," Information Systems Research, INFORMS, vol. 28(4), pages 850-862, December.
    8. Arouri, Mohamed & El Ghoul, Sadok & Gomes, Mathieu, 2021. "Greenwashing and product market competition," Finance Research Letters, Elsevier, vol. 42(C).
    9. Shahbaz, Muhammad & Siddiqui, Aaliyah & Ahmad, Shabbir & Jiao, Zhilun, 2023. "Financial development as a new determinant of energy diversification: The role of natural capital and structural changes in Australia," Energy Economics, Elsevier, vol. 126(C).
    10. Gozgor, Giray & Paramati, Sudharshan Reddy, 2022. "Does energy diversification cause an economic slowdown? Evidence from a newly constructed energy diversification index," Energy Economics, Elsevier, vol. 109(C).
    11. Yu-Shan Chen & Ching-Hsun Chang, 2013. "Greenwash and Green Trust: The Mediation Effects of Green Consumer Confusion and Green Perceived Risk," Journal of Business Ethics, Springer, vol. 114(3), pages 489-500, May.
    12. Chishti, Muhammad Zubair & Xia, Xiqiang & Dogan, Eyup, 2024. "Understanding the effects of artificial intelligence on energy transition: The moderating role of Paris Agreement," Energy Economics, Elsevier, vol. 131(C).
    13. Di Giuli, Alberta & Kostovetsky, Leonard, 2014. "Are red or blue companies more likely to go green? Politics and corporate social responsibility," Journal of Financial Economics, Elsevier, vol. 111(1), pages 158-180.
    14. Song, Malin & Pan, Heting & Shen, Zhiyang & Tamayo-Verleene, Kristine, 2024. "Assessing the influence of artificial intelligence on the energy efficiency for sustainable ecological products value," Energy Economics, Elsevier, vol. 131(C).
    15. Bernstein, Asaf & Billings, Stephen B. & Gustafson, Matthew T. & Lewis, Ryan, 2022. "Partisan residential sorting on climate change risk," Journal of Financial Economics, Elsevier, vol. 146(3), pages 989-1015.
    16. Lau, Chi Keung & Gozgor, Giray & Mahalik, Mantu Kumar & Patel, Gupteswar & Li, Jing, 2023. "Introducing a new measure of energy transition: Green quality of energy mix and its impact on CO2 emissions," Energy Economics, Elsevier, vol. 122(C).
    17. Qin, Meng & Hu, Wei & Qi, Xinzhou & Chang, Tsangyao, 2024. "Do the benefits outweigh the disadvantages? Exploring the role of artificial intelligence in renewable energy," Energy Economics, Elsevier, vol. 131(C).
    18. Liao, Feimei & Sun, Yinghao & Xu, Shulin, 2023. "Financial report comment letters and greenwashing in environmental, social and governance disclosures: Evidence from China," Energy Economics, Elsevier, vol. 127(PB).
    19. Ghoddusi, Hamed & Creamer, Germán G. & Rafizadeh, Nima, 2019. "Machine learning in energy economics and finance: A review," Energy Economics, Elsevier, vol. 81(C), pages 709-727.
    20. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
    21. Zhang, Dongyang & Wang, Jinli & Wang, Yizhi, 2023. "Greening through centralization of environmental monitoring?," Energy Economics, Elsevier, vol. 123(C).
    22. Sanjeev Dewan & Charles Shi & Vijay Gurbaxani, 2007. "Investigating the Risk-Return Relationship of Information Technology Investment: Firm-Level Empirical Analysis," Management Science, INFORMS, vol. 53(12), pages 1829-1842, December.
    23. Chishti, Muhammad Zubair & Sinha, Avik & Zaman, Umer & Shahzad, Umer, 2023. "Exploring the dynamic connectedness among energy transition and its drivers: Understanding the moderating role of global geopolitical risk," Energy Economics, Elsevier, vol. 119(C).
    24. Lucian Bebchuk & Alma Cohen & Allen Ferrell, 2009. "What Matters in Corporate Governance?," The Review of Financial Studies, Society for Financial Studies, vol. 22(2), pages 783-827, February.
    25. Zhang, Dongyang, 2022. "Green financial system regulation shock and greenwashing behaviors: Evidence from Chinese firms," Energy Economics, Elsevier, vol. 111(C).
    26. Hu, Shuo & Wang, Ailun & Du, Kerui, 2023. "Environmental tax reform and greenwashing: Evidence from Chinese listed companies," Energy Economics, Elsevier, vol. 124(C).
    27. Song, Yuegang & Wang, Ziqi & Song, Changqing & Wang, Jianhua & Liu, Rong, 2024. "Impact of artificial intelligence on renewable energy supply chain vulnerability: Evidence from 61 countries," Energy Economics, Elsevier, vol. 131(C).
    28. Sinha, Avik & Bekiros, Stelios & Hussain, Nazim & Nguyen, Duc Khuong & Khan, Sana Akbar, 2023. "How social imbalance and governance quality shape policy directives for energy transition in the OECD countries?," Energy Economics, Elsevier, vol. 120(C).
    29. Xingqiang Du, 2015. "How the Market Values Greenwashing? Evidence from China," Journal of Business Ethics, Springer, vol. 128(3), pages 547-574, May.
    30. Zhou, Wei & Zhuang, Yan & Chen, Yan, 2024. "How does artificial intelligence affect pollutant emissions by improving energy efficiency and developing green technology," Energy Economics, Elsevier, vol. 131(C).
    31. Liu, Yuxiang & Zhang, Jiewei & Dai, Yue, 2023. "Analyst following and greenwashing decision," Finance Research Letters, Elsevier, vol. 58(PC).
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    More about this item

    Keywords

    Artificial intelligence; IT investment; Greenwashing; Environmental management; Innovation;
    All these keywords.

    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • L20 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - General
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management

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