A Study on the Impact of Industrial Robot Applications on Labor Resource Allocation
Tallennettuna:
| Julkaisussa: | Systems vol. 13, no. 7 (2025), p. 569-612 |
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| Muut tekijät: | , |
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MDPI AG
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| Aiheet: | |
| Linkit: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 001 | 3233253255 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2079-8954 | ||
| 024 | 7 | |a 10.3390/systems13070569 |2 doi | |
| 035 | |a 3233253255 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231636 |2 nlm | ||
| 100 | 1 | |a Wu Kexu |u School of Economics and Management, University of Electronic Science and Technology of China, Chengdu 611731, China; 202111150513@std.uestc.edu.cn | |
| 245 | 1 | |a A Study on the Impact of Industrial Robot Applications on Labor Resource Allocation | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a With the rapid advancement of artificial intelligence and smart manufacturing technologies, the penetration of industrial robots into Chinese markets has profoundly reshaped the structure of the labor market. However, existing studies have largely concentrated on the employment substitution effect and the diffusion path of these technologies, while systematic analyses of how industrial robots affect labor resource allocation efficiency across different regional and industrial contexts in China remain scarce. In particular, research on the mechanisms and heterogeneity of these effects is still underdeveloped, calling for deeper investigation into their transmission channels and policy implications. Drawing on panel data from 280 prefecture-level cities in China from 2006 to 2023, this paper employs a Bartik-style instrumental variable approach to measure the level of industrial robot penetration and constructs a two-way fixed effects model to assess its impact on urban labor misallocation. Furthermore, the analysis introduces two mediating variables, industrial upgrading and urban innovation capacity, and applies a mediation effect model combined with Bootstrap methods to empirically test the underlying transmission mechanisms. The results reveal that a higher level of industrial robot adoption is significantly associated with a lower degree of labor misallocation, indicating a notable improvement in labor resource allocation efficiency. Heterogeneity analysis shows that this effect is more pronounced in cities outside the Yangtze River Economic Belt, in those experiencing severe population aging, and in areas with a relatively weak manufacturing base. Mechanism tests further indicate that industrial robots indirectly promote labor allocation efficiency by facilitating industrial upgrades and enhancing innovation capacity. However, in the short term, improvements in innovation capacity may temporarily intensify labor mismatch due to structural frictions. Overall, industrial robots not only exert a direct positive impact on the efficiency of urban labor allocation but also indirectly contribute to resource optimization through structural transformation and innovation system development. These findings underscore the need to account for regional disparities and demographic structures when advancing intelligent manufacturing strategies. Policymakers should coordinate the development of vocational training systems and innovation ecosystems to strengthen the dynamic alignment between technological adoption and labor market restructuring, thereby fostering more inclusive and high-quality economic growth. | |
| 610 | 4 | |a International Federation of Robotics | |
| 651 | 4 | |a United States--US | |
| 651 | 4 | |a China | |
| 653 | |a Regional development | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Labor | ||
| 653 | |a Efficiency | ||
| 653 | |a Resource allocation | ||
| 653 | |a Productivity | ||
| 653 | |a Cities | ||
| 653 | |a Statistical methods | ||
| 653 | |a Automation | ||
| 653 | |a Manufacturing | ||
| 653 | |a Economic growth | ||
| 653 | |a Economic development | ||
| 653 | |a Intelligent manufacturing systems | ||
| 653 | |a Innovations | ||
| 653 | |a Heterogeneity | ||
| 653 | |a Industrial robots | ||
| 700 | 1 | |a Tang, Zhiwei |u School of Public Administration, University of Electronic Science and Technology of China, Chengdu 611731, China; tangzw@uestc.edu.cn | |
| 700 | 1 | |a Zhang Longpeng |u School of Public Administration, University of Electronic Science and Technology of China, Chengdu 611731, China; tangzw@uestc.edu.cn | |
| 773 | 0 | |t Systems |g vol. 13, no. 7 (2025), p. 569-612 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3233253255/abstract/embedded/Y2VX53961LHR7RE6?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3233253255/fulltextwithgraphics/embedded/Y2VX53961LHR7RE6?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3233253255/fulltextPDF/embedded/Y2VX53961LHR7RE6?source=fedsrch |