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Sustainable manufacturing intelligence: pathways for high-quality and energy efficient economic growth

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Abstract

Manufacturing intelligence is an important starting point to achieve high-quality economic growth. Based on the non-radial and non-angular DEA-SBM model, combined with the Malmquist index method, this paper calculates the total factor productivity and green total factor productivity of 286 prefecture-level cities in China, which are used as the indicators of high-quality economic growth. At the same time, the proxy variables of manufacturing intelligence are further constructed, and the impact of intelligent manufacturing on high-quality and energy-efficient economic growth is empirically analyzed. It is found that intelligent manufacturing significantly promotes China’s high-quality and energy-efficient economic growth. Productivity is further decomposed into specific indicators such as technical efficiency, technological progress, pure technical efficiency, pure technical progress, scale efficiency and scale technology, and the mechanism of intelligent manufacturing is analyzed from multiple angles. The research finds that manufacturing intelligence improves the total factor productivity through technological progress effect. Green total factor productivity has been improved through the improvement of technical efficiency effect, but the development of intelligence has brought new challenges to China's labor market. In order to further develop the potential of intelligence, it is necessary to further improve the enterprises’ scale efficiency, while increasing the research and development of energy technology.

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Acknowledgements

This work was sponsored by Humanities and Social Sciences Research Fund of the Ministry of Education(21YJC790041); National Natural Science Foundation of China (72363017); Science and Technology Research Project of Jiangxi Provincial Department of Education(GJJ210514); The 71st China Postdoctoral Science Foundation project (306895).

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Authors and Affiliations

  1. School of Economics, Wuhan Polytechnic University, Wuhan, 430023, China

    Lei **a & Shui Yu

  2. School of Applied Economics, Jiangxi University of Finance and Economics, Nanchang, 330013, China

    Qingjiang Han

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  1. Lei **a
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  2. Qingjiang Han
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Correspondence to Qingjiang Han.

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**a, L., Han, Q. & Yu, S. Sustainable manufacturing intelligence: pathways for high-quality and energy efficient economic growth. Econ Change Restruct 57, 100 (2024). https://doi.org/10.1007/s10644-024-09692-z

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