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Artificial Intelligence and Enterprise Green Innovation: Intrinsic Mechanisms and Heterogeneous Effects

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  • Dongwei Li

    (School of Business Administration, South China University of Technology, Guangzhou 510641, China
    School of Political and Economic Management, Guizhou Minzu University, Guiyang 550025, China)

  • Jing Xiao

    (School of Business Administration, South China University of Technology, Guangzhou 510641, China)

  • Fangfang Yang

    (School of Political and Economic Management, Guizhou Minzu University, Guiyang 550025, China)

Abstract

Enterprise green innovation (EGI) has become an essential measure for manufacturing enterprises to achieve sustainable development, and the application of artificial intelligence (AI) may become a new driving solution. This study empirically analyzes the impact and internal transmission mechanism of AI on EGI of Chinese manufacturing listed enterprises from 2010 to 2022. Research has found that (1) AI significantly impacts EGI, and this basic conclusion has passed various endogeneity and robustness tests. (2) The mechanism test results indicate that enterprise technological capability, innovation investment, and executives’ environmental awareness significantly mediate between AI and EGI. (3) Heterogeneity analysis shows that the significant positive impact of AI on EGI is only established in enterprises with overseas backgrounds, large-scale, highly competitive regional markets, and low-carbon pilot cities. The above conclusions have contributed essentially to the literature on EGI and AI.

Suggested Citation

  • Dongwei Li & Jing Xiao & Fangfang Yang, 2024. "Artificial Intelligence and Enterprise Green Innovation: Intrinsic Mechanisms and Heterogeneous Effects," Sustainability, MDPI, vol. 16(21), pages 1-18, October.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:21:p:9246-:d:1505874
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    References listed on IDEAS

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    1. Zhai, Shaoxuan & Liu, Zhenpeng, 2023. "Artificial intelligence technology innovation and firm productivity: Evidence from China," Finance Research Letters, Elsevier, vol. 58(PB).
    2. Cui, Xin & Wang, Chunfeng & Liao, Jing & Fang, Zhenming & Cheng, Feiyang, 2021. "Economic policy uncertainty exposure and corporate innovation investment: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    3. 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).
    4. Chen, Ji & Wu, Liudan & Hao, Lili & Yu, Xiao & Streimikiene, Dalia, 2024. "Does the import of green products encourage green technology innovation? Empirical evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    5. Xiaofeng Quan & Yun Ke & Yuting Qian & Yao Zhang, 2023. "CEO Foreign Experience and Green Innovation: Evidence from China," Journal of Business Ethics, Springer, vol. 182(2), pages 535-557, January.
    6. Parteka, Aleksandra & Kordalska, Aleksandra, 2023. "Artificial intelligence and productivity: global evidence from AI patent and bibliometric data," Technovation, Elsevier, vol. 125(C).
    7. Constance E. Helfat & Aseem Kaul & David J. Ketchen & Jay B. Barney & Olivier Chatain & Harbir Singh, 2023. "Renewing the resource‐based view: New contexts, new concepts, and new methods," Strategic Management Journal, Wiley Blackwell, vol. 44(6), pages 1357-1390, June.
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    1. Jolanta Słoniec & Monika Kulisz & Marta Małecka-Dobrogowska & Zhadyra Konurbayeva & Łukasz Sobaszek, 2025. "Awareness of the Impact of IT/AI on Energy Consumption in Enterprises: A Machine Learning-Based Modelling Towards a Sustainable Digital Transformation," Energies, MDPI, vol. 18(21), pages 1-24, October.
    2. Panteha Farmanesh & Niloofar Solati Dehkordi & Asim Vehbi & Kavita Chavali, 2025. "Artificial Intelligence and Green Innovation in Small and Medium-Sized Enterprises and Competitive-Advantage Drive Toward Achieving Sustainable Development Goals," Sustainability, MDPI, vol. 17(5), pages 1-20, March.

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