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The impact of artificial intelligence on green technology cycles in China

Author

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  • Fu, Tong
  • Qiu, Zhaoxuan
  • Yang, Xiangyang
  • Li, Zijun
Abstract
In the context of the global climate crisis being of great concern and the accelerated development and application of AI, it is of great significance to study how artificial intelligence (AI) empowers green technological innovation (GTI) in enterprises and assists them in green and low-carbon transformation. This paper explores the impact of AI on firms' GTI. By exploiting Chinese A-share listed companies from 2007 to 2022, we show that AI significantly enhances GTI, and the GTI incentive effect of AI is more prominent in SOEs, large-scale firms and manufacturing firms. Moreover, we show that AI promotes corporate GTI through labor structure (LS) upgrading, internal management (IM) optimization and environmental regulation (ER) enhancement. For policy implication, we further find that the green background of corporate executives (GB) and digital economy development concern (DE) play a significant positive moderating role between AI and corporate GTI. Finally, this paper puts forward corresponding policy recommendations for policy support, environmental regulation, internal management and international cooperation from the three perspectives of government, enterprise and international.

Suggested Citation

  • Fu, Tong & Qiu, Zhaoxuan & Yang, Xiangyang & Li, Zijun, 2024. "The impact of artificial intelligence on green technology cycles in China," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    • Handle: RePEc:eee:tefoso:v:209:y:2024:i:c:s004016252400619x
    DOI: 10.1016/j.techfore.2024.123821
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    References listed on IDEAS

    as
    1. Nahar, Sharmin, 2024. "Modeling the effects of artificial intelligence (AI)-based innovation on sustainable development goals (SDGs): Applying a system dynamics perspective in a cross-country setting," Technological Forecasting and Social Change, Elsevier, vol. 201(C).
    2. Fu, Tong & Huang, Dasen & Feng, Lingbing & Tang, Xiaoping, 2024. "More is better? The impact of predictor choice on the INE oil futures volatility forecasting," Energy Economics, Elsevier, vol. 134(C).
    3. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    4. Yang, Xiaoran & Ran, Rong & Chen, Yejing & Zhang, Jie, 2024. "Does digital government transformation drive regional green innovation? Evidence from cities in China," Energy Policy, Elsevier, vol. 187(C).
    5. Goldfarb, Avi & Taska, Bledi & Teodoridis, Florenta, 2023. "Could machine learning be a general purpose technology? A comparison of emerging technologies using data from online job postings," Research Policy, Elsevier, vol. 52(1).
    6. Zhou, Guangyou & Zhu, Jieyu & Luo, Sumei, 2022. "The impact of fintech innovation on green growth in China: Mediating effect of green finance," Ecological Economics, Elsevier, vol. 193(C).
    7. Gloria Cicerone & Alessandra Faggian & Sandro Montresor & Francesco Rentocchini, 2023. "Regional artificial intelligence and the geography of environmental technologies: does local AI knowledge help regional green-tech specialization?," Regional Studies, Taylor & Francis Journals, vol. 57(2), pages 330-343, February.
    8. Xin Li & Fei Guo & Jiaqi Wang, 2024. "A path towards enterprise environmental performance improvement: How does CEO green experience matter?," Business Strategy and the Environment, Wiley Blackwell, vol. 33(2), pages 820-838, February.
    9. Ouyang, Xiaoling & Li, Qiong & Du, Kerui, 2020. "How does environmental regulation promote technological innovations in the industrial sector? Evidence from Chinese provincial panel data," Energy Policy, Elsevier, vol. 139(C).
    10. Serguey Braguinsky & Atsushi Ohyama & Tetsuji Okazaki & Chad Syverson, 2021. "Product Innovation, Product Diversification, and Firm Growth: Evidence from Japan's Early Industrialization," American Economic Review, American Economic Association, vol. 111(12), pages 3795-3826, December.
    11. 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.
    12. Philippe Aghion & Benjamin F. Jones & Charles I. Jones, 2018. "Artificial Intelligence and Economic Growth," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 237-282, National Bureau of Economic Research, Inc.
    13. Singh, Sanjay Kumar & Chen, Jin & Del Giudice, Manlio & El-Kassar, Abdul-Nasser, 2019. "Environmental ethics, environmental performance, and competitive advantage: Role of environmental training," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 203-211.
    14. Huang, Xiaoqi & Liu, Wei & Zhang, Zhan & Zou, Xinyu & Li, Pujuan, 2023. "Quantity or quality: Environmental legislation and corporate green innovations," Ecological Economics, Elsevier, vol. 204(PB).
    15. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    16. Chotia, Varun & Cheng, Yue & Agarwal, Reeti & Vishnoi, Sushant Kumar, 2024. "AI-enabled Green Business Strategy: Path to carbon neutrality via environmental performance and green process innovation," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    17. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    18. Fu, Tong & Li, Zijun & Qiu, Zhaoxuan & Tong, Xinle, 2024. "The policy gap between finance and economy: Evidence from China's green finance policy," Energy Economics, Elsevier, vol. 134(C).
    19. David Hémous & Morten Olsen, 2022. "The Rise of the Machines: Automation, Horizontal Innovation, and Income Inequality," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(1), pages 179-223, January.
    20. 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).
    21. Yaya Li & Yuru Zhang & An Pan & Minchun Han & Eleonora Veglianti, 2022. "Carbon emission reduction effects of industrial robot applications: Heterogeneity characteristics and influencing mechanisms," Post-Print hal-04522085, HAL.
    22. Abou-Foul, Mohamad & Ruiz-Alba, Jose L. & López-Tenorio, Pablo J., 2023. "The impact of artificial intelligence capabilities on servitization: The moderating role of absorptive capacity-A dynamic capabilities perspective," Journal of Business Research, Elsevier, vol. 157(C).
    23. Rogge, Karoline S. & Reichardt, Kristin, 2016. "Policy mixes for sustainability transitions: An extended concept and framework for analysis," Research Policy, Elsevier, vol. 45(8), pages 1620-1635.
    24. Xiaohang Ren & Ya Xiao & Feng He & Giray Gozgor, 2024. "The contagion of extreme risks between fossil and green energy markets: evidence from China," Quantitative Finance, Taylor & Francis Journals, vol. 24(5), pages 627-642, May.
    25. Mark T. Buntaine & Michael Greenstone & Guojun He & Mengdi Liu & Shaoda Wang & Bing Zhang, 2024. "Does the Squeaky Wheel Get More Grease? The Direct and Indirect Effects of Citizen Participation on Environmental Governance in China," American Economic Review, American Economic Association, vol. 114(3), pages 815-850, March.
    26. Ajay Agrawal & Joshua S. Gans & Avi Goldfarb, 2019. "Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 31-50, Spring.
    27. Ioannides, Yannis M. & Zhang, Junfu, 2017. "Walled cities in late imperial China," Journal of Urban Economics, Elsevier, vol. 97(C), pages 71-88.
    28. Shao, Yanmin & Xu, Kunliang & Shan, Yuan George, 2024. "Leveraging corporate digitalization for green technology innovation: The mediating role of resource endowments," Technovation, Elsevier, vol. 133(C).
    29. Yang, Xiangyang & Li, Zijun & Qiu, Zhaoxuan & Wang, Jinmin & Liu, Bei, 2024. "ESG performance and corporate technology innovation: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 206(C).
    30. 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.
    31. 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).
    32. Johnson, Prince Chacko & Laurell, Christofer & Ots, Mart & Sandström, Christian, 2022. "Digital innovation and the effects of artificial intelligence on firms’ research and development – Automation or augmentation, exploration or exploitation?," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    33. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
    34. Zhang, Dongyang & Wang, Jinli & Wang, Yizhi, 2023. "Greening through centralization of environmental monitoring?," Energy Economics, Elsevier, vol. 123(C).
    35. Cheng, Can & Luo, Jiayu & Zhu, Chun & Zhang, Shangfeng, 2024. "Artificial intelligence and the skill premium: A numerical analysis of theoretical models," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    36. Wang, Xin & Gan, Yufei & Zhou, Shiqi & Wang, Xinqiao, 2024. "Digital technology adoption, absorptive capacity, CEO green experience and the quality of green innovation: Evidence from China," Finance Research Letters, Elsevier, vol. 63(C).
    37. Agrawal, Ajay & McHale, John & Oettl, Alexander, 2024. "Artificial intelligence and scientific discovery: a model of prioritized search," Research Policy, Elsevier, vol. 53(5).
    38. Bei Liu & Jinmin Wang & Xinle Tong & Zhihua Zhou & Zhaoxuan Qiu, 2024. "Institutional investor shareholding and the quality of corporate innovation: Moderating effects based on internal and external environment," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 45(1), pages 326-338, January.
    39. Fu, Tong & Yang, Yang & Zhang, Hongru & Mao, Zhenxing (Eddie), 2023. "Risk culture as a blessing in tourism development: Long-run effects of epidemic disasters," Annals of Tourism Research, Elsevier, vol. 103(C).
    40. Li, Yaya & Zhang, Yuru & Pan, An & Han, Minchun & Veglianti, Eleonora, 2022. "Carbon emission reduction effects of industrial robot applications: Heterogeneity characteristics and influencing mechanisms," Technology in Society, Elsevier, vol. 70(C).
    41. Gao, Qiang & Cheng, Changming & Sun, Guanglin, 2023. "Big data application, factor allocation, and green innovation in Chinese manufacturing enterprises," Technological Forecasting and Social Change, Elsevier, vol. 192(C).
    42. Li Wang & Hongyu Yang, 2024. "Digital technology innovation and corporate ESG performance: evidence from China," Economic Change and Restructuring, Springer, vol. 57(6), pages 1-32, December.
    43. Shinwari, Riazullah & Wang, Yangjie & Gozgor, Giray & Mousavi, Mahdi, 2024. "Does FDI affect energy consumption in the belt and road initiative economies? The role of green technologies," Energy Economics, Elsevier, vol. 132(C).
    44. Mingjun Deng & Hao Tang & Wenbing Luo, 2024. "Can the green experience of CEO improve ESG performance in heavy polluting companies? Evidence from China," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 45(4), pages 2373-2392, June.
    45. Lee, Chien-Chiang & Qin, Shuai & Li, Yaya, 2022. "Does industrial robot application promote green technology innovation in the manufacturing industry?," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    46. Chen, Yongyu & Peng, Zihao & Peng, Caodie & Xu, Wanli, 2023. "Impact of new government–business relations on urban digital economy: Empirical evidence from China," Finance Research Letters, Elsevier, vol. 58(PA).
    47. Michael E. Porter & Claas van der Linde, 1995. "Toward a New Conception of the Environment-Competitiveness Relationship," Journal of Economic Perspectives, American Economic Association, vol. 9(4), pages 97-118, Fall.
    48. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    49. Yang, Siying & Liu, Fengshuo, 2024. "Impact of industrial intelligence on green total factor productivity: The indispensability of the environmental system," Ecological Economics, Elsevier, vol. 216(C).
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