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Impact of Industrial Intelligence on Total Factor Productivity

Author

Listed:
  • Ke An

    (Chinese Institute for Policy and Practice of Rural Development, Ningbo University, Ningbo 315211, China)

  • Yike Shan

    (Business School, Ningbo University, Ningbo 315211, China)

  • Sheng Shi

    (Business School, Ningbo University, Ningbo 315211, China)

Abstract

Industrial intelligence is gaining more prominence in the new era of the technical revolution. This paper conducts an empirical test based on the panel data of 30 Chinese provinces (municipalities and autonomous regions) from 2006 to 2017. Firstly, the stochastic frontier analysis developed from the transcendental logarithmic production function is applied to calculate the total factor productivity of 30 provinces in China. The fluctuation of the total factor productivity is employed to reflect the quality of economic development. Secondly, the multilevel mediation model is applied to conduct the empirical test. Then, the robustness and endogeny of the conclusions are tested, and a further discussion is finally made, respectively, for eastern, central and western China. The results show that: (1) Industrial intelligence has a promoting effect on the improvement of total factor productivity. (2) Industrial intelligence can increase the demand for highly skilled labor and reduce the demand for low-skilled labor, but it has no significant impact on the demand for medium-skilled labor. (3) Industrial intelligence influences the improvement of total factor productivity through labor force structure.

Suggested Citation

  • Ke An & Yike Shan & Sheng Shi, 2022. "Impact of Industrial Intelligence on Total Factor Productivity," Sustainability, MDPI, vol. 14(21), pages 1-21, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14535-:d:963923
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