IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i8p3369-d1377521.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/8/3369/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/8/3369/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiaxing Du & Han Cai & Xiu Jin, 2024. "Exploring the Association Between Artificial Intelligence Management and Green Innovation: Expanding the Research Field for Sustainable Outcomes," Sustainability, MDPI, vol. 16(21), pages 1-28, October.

    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. Lin, Boqiang & Xie, Yongjing, 2024. "The role of venture capital in determining the total factor productivity of renewable energy enterprises: In the context of government subsidy reduction," Energy Economics, Elsevier, vol. 132(C).
    2. Chunhua Lu & Hong Li, 2023. "Have China’s Regional Carbon Emissions Trading Schemes Promoted Industrial Resource Allocation Efficiency? The Evidence from Heavily Polluted Industries at the Provincial Level," Sustainability, MDPI, vol. 15(3), pages 1-20, February.
    3. Xue, Qinyuan & Jin, Yifei & Zhang, Cheng, 2024. "ESG rating results and corporate total factor productivity," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    4. Bing Zhou & Gong Zhang & Shulei Bi, 2023. "How Does Emissions Trading Affect the Efficiency of Enterprise Resource Allocation? Evidence From China," SAGE Open, , vol. 13(4), pages 21582440231, November.
    5. Liu, Dongwang, 2024. "Local government competition and resource allocation efficiency," Finance Research Letters, Elsevier, vol. 60(C).
    6. Guo, Yunxia & Yu, Mengyao & Xu, Mingchen & Tang, Ying & Huang, Jingran & Liu, Jia & Hao, Yu, 2023. "Productivity gains from green finance: A holistic and regional examination from China," Energy Economics, Elsevier, vol. 127(PA).
    7. Yuanyu Cao & Tao Xu, 2024. "The Impact of Environmental Social Responsibility on Total Factor Productivity: Evidence from Listed Companies in China," Sustainability, MDPI, vol. 16(18), pages 1-26, September.
    8. Geoffrey Barrows & Hélène Ollivier & Ariell Reshef, 2023. "Production Function Estimation with Multi-Destination Firms," CESifo Working Paper Series 10716, CESifo.
    9. Andrés César & Guillermo Falcone, 2020. "Heterogeneous Effects of Chinese Import Competition on Chilean Manufacturing Plants," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Spring 20), pages 1-60, December.
    10. Yuan, Li & Rao, Siqi & Yang, Shenggang & Dai, Pengyi, 2023. "Does equity market openness increase productivity? the dual effects of Shanghai-Hong Kong stock Connect program in China," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    11. Guo, Shu & Zhang, ZhongXiang, 2023. "Green credit policy and total factor productivity: Evidence from Chinese listed companies," Energy Economics, Elsevier, vol. 128(C).
    12. Zhaohui Yan & Mingli Wang & Yumeng Sun & Zihui Nan, 2023. "The Impact of Research and Development Investment on Total Factor Productivity of Animal Husbandry Enterprises: Evidence from Listed Companies in China," Agriculture, MDPI, vol. 13(9), pages 1-21, September.
    13. Aragón, Fernando M. & Restuccia, Diego & Rud, Juan Pablo, 2022. "Are small farms really more productive than large farms?," Food Policy, Elsevier, vol. 106(C).
    14. Matteo G. Richiardi & Luis Valenzuela, 2024. "Firm heterogeneity and the aggregate labour share," LABOUR, CEIS, vol. 38(1), pages 66-101, March.
    15. Amit Gandhi & Salvador Navarro & David Rivers, 2011. "On the Identification of Production Functions: How Heterogeneous is Productivity?," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20119, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
    16. David Van Dijcke, 2022. "On the Non-Identification of Revenue Production Functions," Papers 2212.04620, arXiv.org, revised May 2024.
    17. David Greenaway & Alessandra Guariglia & Zhihong Yu, 2014. "The more the better? Foreign ownership and corporate performance in China," The European Journal of Finance, Taylor & Francis Journals, vol. 20(7-9), pages 681-702, September.
    18. Guangfan Sun & Xin Lin & Junyi Chen & Nuo Xu & Ping Xiong & Hanqi Li, 2023. "Cultural inclusion and corporate sustainability: evidence from food culture and corporate total factor productivity in China," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-15, December.
    19. Mary Amiti & Cédric Duprez & Jozef Konings & John Van Reenen, 2023. "FDI and Superstar Spillovers: Evidence from Firm-to-Firm Transactions," NBER Working Papers 31128, National Bureau of Economic Research, Inc.
    20. De loecker, Jan & Asker, John & Collard-Wexler, Allan, 2011. "Productivity volatility and the misallocation of resources in developing economies," CEPR Discussion Papers 8469, C.E.P.R. Discussion Papers.

    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:8:p:3369-:d:1377521. 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.