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Stimulating effects of intelligent policy on the performance of listed manufacturing companies in China

Author

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  • Liu, Jun
  • Yang, Yuan-jun
  • Cao, Ya-ru
  • Forrest, Jeffrey Yi-Lin

Abstract

Based on the pilot projects of intelligent manufacturing of the Ministry of Industry and Information Technology of the People’s Republic of China and the annual data reported by listed companies, this paper studies the effect of China's intelligent policy on the performance of listed manufacturing companies by using the panel data of relevant enterprises from 2011 to 2017, as well as the mechanism of impact. Our empirical tests, using the difference-in-difference method, shows that intelligent policy can significantly improve the economic performance of manufacturing enterprises by guiding enterprises to optimize their intelligent management, strengthening investment in intelligent equipment and promoting collaborative manufacturing. Further empirical tests show that the impact of intelligent policy on economic performance is different in time. In the later selected pilot enterprises, the impact of intelligent policy on their economic performance is more significant; there is regional heterogeneity in the effects of intelligent policy: in regions with low intelligence, the positive impact of intelligent policy on the economic performance of manufacturing industry is more significant. Based on these conclusions, relevant intelligent policy suggestions are put forward.

Suggested Citation

  • Liu, Jun & Yang, Yuan-jun & Cao, Ya-ru & Forrest, Jeffrey Yi-Lin, 2021. "Stimulating effects of intelligent policy on the performance of listed manufacturing companies in China," Journal of Policy Modeling, Elsevier, vol. 43(3), pages 558-573.
    • Handle: RePEc:eee:jpolmo:v:43:y:2021:i:3:p:558-573
    DOI: 10.1016/j.jpolmod.2021.01.005
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    1. 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.
    2. Joseph Zeira, 1998. "Workers, Machines, and Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(4), pages 1091-1117.
    3. Shiller, Robert J., 2017. "Economic risks associated with deep change in technology, and their mitigation," Journal of Policy Modeling, Elsevier, vol. 39(4), pages 616-624.
    4. Zhang, Qi & Yu, Zhi & Kong, Dongmin, 2019. "The real effect of legal institutions: Environmental courts and firm environmental protection expenditure," Journal of Environmental Economics and Management, Elsevier, vol. 98(C).
    5. Georg Graetz & Guy Michaels, 2018. "Robots at Work," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 753-768, December.
    6. Qunyong Wang, 2015. "Fixed-effect panel threshold model using Stata," Stata Journal, StataCorp LLC, vol. 15(1), pages 121-134, March.
    7. Georg Graetz & Guy Michaels, 2015. "Robots at work: the impact on productivity and jobs," CentrePiece - The magazine for economic performance 447, Centre for Economic Performance, LSE.
    8. Michael Baker & Jonathan Gruber & Kevin Milligan, 2008. "Universal Child Care, Maternal Labor Supply, and Family Well-Being," Journal of Political Economy, University of Chicago Press, vol. 116(4), pages 709-745, August.
    9. Lins, Karl V., 2003. "Equity Ownership and Firm Value in Emerging Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 38(1), pages 159-184, March.
    10. Robert E. Hoyt & Andre P. Liebenberg, 2011. "The Value of Enterprise Risk Management," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 78(4), pages 795-822, December.
    11. 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.
    12. Biagi, Federico & Falk, Martin, 2017. "The impact of ICT and e-commerce on employment in Europe," Journal of Policy Modeling, Elsevier, vol. 39(1), pages 1-18.
    13. Freel, Mark S., 2003. "Sectoral patterns of small firm innovation, networking and proximity," Research Policy, Elsevier, vol. 32(5), pages 751-770, May.
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    1. Wang, Jianlong & Liu, Yong & Wang, Weilong & Wu, Haitao, 2024. "Does artificial intelligence improve enterprise carbon emission performance? Evidence from an intelligent transformation policy in China," Technology in Society, Elsevier, vol. 79(C).
    2. Jin, Minghui & Chen, Yang, 2024. "Has green innovation been improved by intelligent manufacturing?—Evidence from listed Chinese manufacturing enterprises," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    3. Ningning Ni & Xinya Chen & Yifan Guo & Xing Zhao, 2025. "Toward Economic Recovery: Can Industrial Intelligence Improve Total Factor Productivity?," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(3), pages 12226-12257, September.
    4. Zhang, Linghao & Jin, Xinwei & Wu, Kai, 2025. "How do common institutional investors adapt to early technology adoption?," Journal of Business Research, Elsevier, vol. 199(C).
    5. Lipeng Sun & Nur Ashikin Mohd Saat, 2023. "How Does Intelligent Manufacturing Affect the ESG Performance of Manufacturing Firms? Evidence from China," Sustainability, MDPI, vol. 15(4), pages 1-20, February.

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