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The Impact of Artificial Intelligence Adoption Intensity on Corporate Sustainability Performance: The Moderated Mediation Effect of Organizational Change

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  • Jiachen Li

    (Department of Business Administration, Gachon University, Seongnam-si 13120, Republic of Korea)

  • Xiu Jin

    (Department of Business Administration, Gachon University, Seongnam-si 13120, Republic of Korea)

Abstract

With the rapid development of the economy and society, enterprises are increasingly prioritizing environmental and social sustainability alongside economic benefits. As a critical driver of technological innovation, the effective application of artificial intelligence (AI) to enhance corporate sustainability performance has garnered considerable attention from both academia and industry. This study explores the impact of AI adoption intensity on corporate sustainability performance, with a particular focus on the mediating role of organizational change and its moderated mediation effect. Employing an empirical analysis approach, this study collected 451 employee survey responses from manufacturing enterprises. The results indicate that AI adoption intensity substantially enhances corporate sustainability performance, reflected in comprehensive improvements in economic, environmental, and social benefits. Furthermore, organizational change serves as a crucial mediator between AI adoption and sustainability performance, with this mediation effect moderated by internal and external environmental factors. The study finds that enterprises with high digital capabilities and innovative cultures are more effective in leveraging AI to enhance sustainability performance. This suggests that in promoting AI applications, enterprises should not only focus on technology adoption but also emphasize internal organizational change and the development of digital capabilities to fully achieve sustainability goals. Through empirical analysis, this study provides an in-depth understanding of the application paths and mechanisms of AI in corporate sustainability, offering a theoretical foundation and practical guidance for corporate managers in strategy and policymaking.

Suggested Citation

  • Jiachen Li & Xiu Jin, 2024. "The Impact of Artificial Intelligence Adoption Intensity on Corporate Sustainability Performance: The Moderated Mediation Effect of Organizational Change," Sustainability, MDPI, vol. 16(21), pages 1-21, October.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:21:p:9350-:d:1508192
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    References listed on IDEAS

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    1. Issa, Helmi & Jabbouri, Rachid & Palmer, Mark, 2022. "An artificial intelligence (AI)-readiness and adoption framework for AgriTech firms," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    2. Min Wang & Youshi He & Jianya Zhou & Kai Ren, 2022. "Evaluating the Effect of Chinese Environmental Regulation on Corporate Sustainability Performance: The Mediating Role of Green Technology Innovation," IJERPH, MDPI, vol. 19(11), pages 1-18, June.
    3. Pietronudo, Maria Cristina & Croidieu, Grégoire & Schiavone, Francesco, 2022. "A solution looking for problems? A systematic literature review of the rationalizing influence of artificial intelligence on decision-making in innovation management," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    4. Maria Cristina Pietronudo & Gregoire Croidieu & Francesco Schiavone, 2022. "A solution looking for problems? A systematic literature review of the rationalizing influence of artificial intelligence on decision-making in innovation management," Post-Print hal-04325569, HAL.
    5. Zhao, Shuang & Zhang, Liqun & Peng, Lin & Zhou, Haiyan & Hu, Feng, 2024. "Enterprise pollution reduction through digital transformation? Evidence from Chinese manufacturing enterprises," Technology in Society, Elsevier, vol. 77(C).
    6. Dima Jamali, 2008. "A Stakeholder Approach to Corporate Social Responsibility: A Fresh Perspective into Theory and Practice," Journal of Business Ethics, Springer, vol. 82(1), pages 213-231, September.
    7. David J. Teece, 2007. "Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance," Strategic Management Journal, Wiley Blackwell, vol. 28(13), pages 1319-1350, December.
    8. Dorian Proksch & Anna Frieda Rosin & Stephan Stubner & Andreas Pinkwart, 2024. "The influence of a digital strategy on the digitalization of new ventures: The mediating effect of digital capabilities and a digital culture," Journal of Small Business Management, Taylor & Francis Journals, vol. 62(1), pages 1-29, January.
    9. Füller, Johann & Hutter, Katja & Wahl, Julian & Bilgram, Volker & Tekic, Zeljko, 2022. "How AI revolutionizes innovation management – Perceptions and implementation preferences of AI-based innovators," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    10. Carmen Isensee & Kai-Michael Griese & Frank Teuteberg, 2021. "Sustainable artificial intelligence: A corporate culture perspective [Sustainable artificial intelligence: Eine unternehmenskulturelle Perspektive]," Sustainability Nexus Forum, Springer, vol. 29(3), pages 217-230, December.
    11. Chatterjee, Sheshadri & Rana, Nripendra P. & Dwivedi, Yogesh K. & Baabdullah, Abdullah M., 2021. "Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
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