IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i21p9246-d1505874.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/21/9246/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/21/9246/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Parteka, Aleksandra & Kordalska, Aleksandra, 2023. "Artificial intelligence and productivity: global evidence from AI patent and bibliometric data," Technovation, Elsevier, vol. 125(C).
    2. Zhai, Shaoxuan & Liu, Zhenpeng, 2023. "Artificial intelligence technology innovation and firm productivity: Evidence from China," Finance Research Letters, Elsevier, vol. 58(PB).
    3. 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.
    4. 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).
    5. 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.
    6. 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).
    7. 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).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gu, Haoran & Yang, Shenggang & Xu, Zhaoyi & Cheng, Cheng, 2023. "Supply chain finance, green innovation, and productivity: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    2. Lin, Boqiang & Xu, Chongchong, 2024. "The effects of industrial robots on firm energy intensity: From the perspective of technological innovation and electrification," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    3. Yang, Baochen & An, Haokai & Song, Xinyu, 2024. "Oil price uncertainty and corporate inefficient investment: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
    4. Li, Chengming & Wang, Yilin & Zhou, Zhihan & Wang, Zeyu & Mardani, Abbas, 2023. "Digital finance and enterprise financing constraints: Structural characteristics and mechanism identification," Journal of Business Research, Elsevier, vol. 165(C).
    5. Yao, Shouyu & Pan, Yuying & Sensoy, Ahmet & Uddin, Gazi Salah & Cheng, Feiyang, 2021. "Green credit policy and firm performance: What we learn from China," Energy Economics, Elsevier, vol. 101(C).
    6. Cui, Xin & Wang, Chunfeng & Sensoy, Ahmet & Liao, Jing & Xie, Xiaochen, 2023. "Economic policy uncertainty and green innovation: Evidence from China," Economic Modelling, Elsevier, vol. 118(C).
    7. Bakhsh, Satar & Zhang, Wei, 2023. "How does natural resource price volatility affect economic performance? A threshold effect of economic policy uncertainty," Resources Policy, Elsevier, vol. 82(C).
    8. Jia, Shaoqing & Yang, Liuyong & Zhou, Fangzhao, 2022. "Geopolitical risk and corporate innovation: Evidence from China," Journal of Multinational Financial Management, Elsevier, vol. 66(C).
    9. Wan, Qunchao & Chen, Jin & Yao, Zhu & Yuan, Ling, 2022. "Preferential tax policy and R&D personnel flow for technological innovation efficiency of China's high-tech industry in an emerging economy," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    10. Wunhong Su & Xingxing Hu & Liuzhen Zhang, 2023. "Association Between Directors With Foreign Experience and Firms’ Environmental Disclosure," SAGE Open, , vol. 13(4), pages 21582440231, December.
    11. Xilin He & Renato Lopes da Costa & Debing Ni & Wucheng Han, 2024. "How Quasi-Internal Resources Enhance Firm Performance During Large-Scale Emergencies: The Role of Trade-Off Between CSR and Business Innovations," Sustainability, MDPI, vol. 16(21), pages 1-21, October.
    12. Maxwell Chukwudi Udeagha & Edwin Muchapondwa, 2023. "Environmental sustainability in South Africa: Understanding the criticality of economic policy uncertainty, fiscal decentralization, and green innovation," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(3), pages 1638-1651, June.
    13. Ye, Jiangfeng & Wan, Qunchao & Li, Ruida & Yao, Zhu & Huang, Dujuan, 2022. "How do R&D agglomeration and economic policy uncertainty affect the innovative performance of Chinese high-tech industry?," Technology in Society, Elsevier, vol. 69(C).
    14. Li, Ganglei & Shao, Yunfei, 2023. "How do top management team characteristics affect digital orientation? Exploring the internal driving forces of firm digitalization," Technology in Society, Elsevier, vol. 74(C).
    15. Weilong Wang & Jianlong Wang & Shaersaikai Wulaer & Bing Chen & Xiaodong Yang, 2021. "The Effect of Innovative Entrepreneurial Vitality on Economic Resilience Based on a Spatial Perspective: Economic Policy Uncertainty as a Moderating Variable," Sustainability, MDPI, vol. 13(19), pages 1-23, September.
    16. Ruiyu Hu & Zemenghong Bao & Zhisen Lin & Kun Lv, 2024. "The Innovative Construction of Provinces, Regional Artificial Intelligence Development, and the Resilience of Regional Innovation Ecosystems: Quasi-Natural Experiments Based on Spatial Difference-in-D," Sustainability, MDPI, vol. 16(18), pages 1-37, September.
    17. Mingjun Deng & Xusheng Fang & Ziyan Tian & Wenbing Luo, 2022. "The Impact of Environmental Uncertainty on Corporate Innovation: Evidence from Chinese Listed Companies," Sustainability, MDPI, vol. 14(9), pages 1-19, April.
    18. He, Na & Yang, Junjie & Ren, Jiahui, 2024. "Pollution and green innovation: Evidence from CEOs’ early-life experience," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 65-79.
    19. Shen, Xieyang & Yang, Sijie & Chen, Yulin & Zeng, Jianyu, 2022. "How does economic policy uncertainty influence managers' learning from peers' stock prices? Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:21:p:9246-:d:1505874. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.