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Government Subsidies, Green Innovation, and Firm Total Factor Productivity of Listed Artificial Intelligence Firms in China

Author

Listed:
  • Guangwei Zhang

    (Economic and Trade Law School, Shandong University of Politcal Science and Law, Jinan 250014, China
    WIPO Research Center, Tongji University, Shanghai 200062, China)

  • Yahan Shi

    (International School of Law and Finance, East China University of Political Science and Law, Shanghai 200042, China)

  • Nuozhou Huang

    (Shanghai International College of Intellectual Property, Tongji University, Shanghai 200062, China)

Abstract

The world is being reshaped under global economic development driven by new advances in information technology. Artificial intelligence, an essential potential technology, will play a vital role in technological change and industrial upgrades. Exploring the relationship between government subsidies, green innovation, and total factor productivity will help us analyze government decisions’ effects and better promote artificial intelligence’s technological innovation process. Based on data from China’s listed artificial intelligence companies from 2011 to 2020, this study uses the Levinsohn–Petrin method to measure the total factor productivity of companies and analyzes the impact of government subsidies on the total factor productivity of AI companies, the mediating effect of green innovation, and the moderating effect of intellectual property protection intensity. The research results show that (1) government subsidies can promote the total factor productivity of AI enterprises; (2) green innovation capabilities play a mediating role between government subsidies and enterprise total factor productivity, and government subsidies can indirectly promote green innovation to promote the improvement of total factor productivity effectively; (3) in the AI industry, the promotion effect of government subsidies on total factor productivity is more significant among state-owned enterprises, while the impact mechanism of government subsidies on private enterprises is not significant; and (4) the intensity of intellectual property protection has played a positive moderating role in the impact of government subsidies for artificial intelligence enterprises on total factor productivity. However, the current intensity of intellectual property protection remains unable to promote improvements in enterprise total factor productivity by stimulating green innovation. The research results will help us better understand the relationship between government subsidies and the development of corporate economic benefits and promote more scientific and effective government decision-making.

Suggested Citation

  • Guangwei Zhang & Yahan Shi & Nuozhou Huang, 2024. "Government Subsidies, Green Innovation, and Firm Total Factor Productivity of Listed Artificial Intelligence Firms in China," Sustainability, MDPI, vol. 16(8), pages 1-20, April.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:8:p:3369-:d:1377521
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    References listed on IDEAS

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    1. Xiaofeng Xu & Xiangyu Chen & Yi Xu & Tao Wang & Yifan Zhang, 2022. "Improving the Innovative Performance of Renewable Energy Enterprises in China: Effects of Subsidy Policy and Intellectual Property Legislation," Sustainability, MDPI, vol. 14(13), pages 1-24, July.
    2. Scott L. Baier & Gerald P. Dwyer & Robert Tamura, 2006. "How Important are Capital and Total Factor Productivity for Economic Growth?," Economic Inquiry, Western Economic Association International, vol. 44(1), pages 23-49, January.
    3. Chang-Tai Hsieh & Peter J. Klenow, 2009. "Misallocation and Manufacturing TFP in China and India," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(4), pages 1403-1448.
    4. Pei Wang & Cong Dong & Nan Chen & Ming Qi & Shucheng Yang & Amuji Bridget Nnenna & Wenxin Li, 2021. "Environmental Regulation, Government Subsidies, and Green Technology Innovation—A Provincial Panel Data Analysis from China," IJERPH, MDPI, vol. 18(22), pages 1-19, November.
    5. Richard Harris & Shengyu Li, 2019. "Government assistance and total factor productivity: firm-level evidence from China," Journal of Productivity Analysis, Springer, vol. 52(1), pages 1-27, December.
    6. Yihao Cao & Ehsan Elahi & Zainab Khalid & Ping Li & Pengsheng Sun, 2023. "How Do Intellectual Property Rights Affect Green Technological Innovation? Empirical Evidence from China," Sustainability, MDPI, vol. 15(10), pages 1-17, May.
    7. Zumian Xiao & Hongfeng Peng & Zheyao Pan, 2022. "Innovation, external technological environment and the total factor productivity of enterprises," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(1), pages 3-29, March.
    8. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(2), pages 317-341.
    9. Kumbhakar, Subal C. & Li, Mingyang & Lien, Gudbrand, 2023. "Do subsidies matter in productivity and profitability changes?," Economic Modelling, Elsevier, vol. 123(C).
    10. Wang, Yafei & Bai, Ying & Quan, Tianshu & Ran, Rong & Hua, Lei, 2023. "Influence and effect of industrial agglomeration on urban green total factor productivity—On the regulatory role of innovation agglomeration and institutional distance," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1158-1173.
    11. Marzieh Abolhassani & Zhi Wang & Jakob de Haan, 2020. "How Does Government Control Affect Firm Value? New Evidence for China," Kyklos, Wiley Blackwell, vol. 73(1), pages 3-21, February.
    12. Zhang, Cheng & Zhou, Bo & Tian, Xuan, 2022. "Political connections and green innovation: The role of a corporate entrepreneurship strategy in state-owned enterprises," Journal of Business Research, Elsevier, vol. 146(C), pages 375-384.
    13. Lin, Boqiang & Zhang, Aoxiang, 2023. "Government subsidies, market competition and the TFP of new energy enterprises," Renewable Energy, Elsevier, vol. 216(C).
    14. Jun Wen & Lingxiao Li & Xinxin Zhao & Chenyang Jiao & Wenjie Li, 2022. "How Government Size Expansion Can Affect Green Innovation—An Empirical Analysis of Data on Cross-Country Green Patent Filings," IJERPH, MDPI, vol. 19(12), pages 1-22, June.
    15. Zhao, Liange & Wang, Dongmei & Wang, Xueyuan & Zhang, Zhijian, 2023. "Impact of green finance on total factor productivity of heavily polluting enterprises: Evidence from green finance reform and innovation pilot zone," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 765-785.
    16. Jiahui Xu & Chee-Pung Ng & Toong Hai Sam & Asokan Vasudevan & Poh Kiong Tee & Alex Hou Hong Ng & Wong Chee Hoo, 2023. "Fiscal and Tax Policies, Access to External Financing and Green Innovation Efficiency: An Evaluation of Chinese Listed Firms," Sustainability, MDPI, vol. 15(15), pages 1-19, July.
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