THE INFLUENCE OF INTELLIGENT TRANSFORMATION AND LABOR STRUCTURE OPTIMIZATION ON INNOVATION PERFORMANCE IN MANUFACTURING ENTERPRISES: THE MODERATING EFFECT OF FACTOR INPUTS
Article Sidebar
Main Article Content
Abstract
Against the backdrop of China’s new economic norms, the intelligent transformation of the manufacturing industry has become a key initiative for driving innovation amid diminishing external technological spillover effects and mounting economic pressure. The gradual integration of artificial intelligence into the manufacturing sector has attracted widespread academic attention. However, existing research has primarily focused on the macro level and often lacks in-depth analysis of the mechanisms through which intelligent transformation influences innovation performance. By conducting an empirical analysis of data from A-share listed manufacturing companies from 2013 to 2022, this study finds that intelligent transformation has a significant positive impact on innovation performance, with labor structure optimization serving as a partial mediator. In this process, the investment in and application of intelligent technologies within the manufacturing sector significantly enhance innovation performance. Moreover, intelligent transformation substantially reduces the proportion of conventional low-skill labor while increasing the share of unconventional high-skill labor, with no significant effect on conventional medium-skill labor. Additionally, investments in human capital and capital intensity positively moderate both labor structure optimization and improvements in innovation performance. This study provides theoretical insights and practical recommendations for the manufacturing industry to enhance innovation performance through intelligent transformation.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Chinese Journal of Social Science and Management Editorial Division
The Office of Research and Development, Panyapiwat Institute of Management
85/1 Moo 2, Chaengwattana Rd., Bang Talat, Pakkred, Nonthaburi 11120, Thailand
Tel. 02 855 01048 E-mail: cjssm@pim.ac.th
References
Acemoglu, D., & Restrepo, P. (2018a). Artificial intelligence, automation and work. https://ssrn.com/abstract=3101994
Acemoglu, D., & Restrepo, P. (2018b). The race between man and machine: Implications of technology for growth, factor shares, and employment. American Economic Review, 108(6), 1488-1542.
Acemoglu, D., & Restrepo, P. (2019). The economics of Artificial Intelligence: An agenda. The University of Chicago Press.
Autor, D. H. (2015). Why are there still so many jobs? The history and future of workplace automation. Journal of Economic Perspectives, 29(3), 3-30.
Autor, D. H., Levy, F., & Murnane, R. J. (2003). The skill content of recent technological change: An empirical exploration. The Quarterly Journal of Economics, 118(4), 1279-1333.
Becker, G. S. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. The University of Chicago Press.
Borjas, G. J. (2005). The labor-market impact of high-skill immigration. The American Economic Review, 95(2), 56-60.
Cai, Y. Z., & Chen, N. (2019). Artificial Intelligence and high-quality growth and employment under the new technological revolution. The Journal of Quantitative & Technical Economics, (5), 3-22. [in Chinese]
Cheng, F. Y. (2022). The efficiency and spatial evolution characteristics of material capital allocation in the Guangdong-Hong Kong-Macao Greater Bay Area. Statistics and Decision, 38(14), 110-113. [in Chinese]
China Academy of Social Sciences, Institute of Industrial Economics, Intelligent Economy Research Group. (2021). Intelligent+: The intelligent transformation of manufacturing. People’s Posts and Telecommunications Press. [in Chinese]
Evans, L. B., & Siegfried, J. J. (1992). Entry and exit in United States manufacturing industries from 1977 to 1982. In D. B. Audretsch, & J. J. Siegfried (Eds.), Empirical studies in industrial organization (pp. 253-273). Springer Science+Business Media.
Frey, C. B., & Osborne, M. A. (2013). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting & Social Change, 114, 254-280.
He, F., & Liu, H. (2019). Performance improvement effect of digital transformation in physical enterprises from the perspective of the digital economy. Reform, (4), 137-148. [in Chinese]
He, Q., Li, Y. N., Cheng, Y. X., & Li, X. Y. (2020). The impact and mechanism of Artificial Intelligence technology application on employment: Micro evidence from manufacturing enterprises. China Soft Science, (S1), 213-222. [in Chinese]
Huang, Y., Liu, Y., Wu, Y., & Li, W. (2013). Regional economic growth disparities in China: The effects of educational stratification. Economic Research, (4), 94-105. [in Chinese]
International Federation of Robotics. (2023). World robotics 2022: Industrial robots. International Federation of Robotics. https://ifr.org/about-world-robotics/
Kong, G., Liu, S., & Kong, D. (2020). Robots and employment: An exploratory analysis based on industry and regional heterogeneity. China Industrial Economics, (8), 80-98. [in Chinese]
Kucharčíková, A. (2014). Investment in the human capital as the source of economic growth. Periodica Polytechnica Social and Management Sciences, 22(1), 29-35.
Leone, D., Schiavone, F., Appio, F. P., & Chiao, B. (2021). How does Artificial Intelligence enable and enhance value co-creation in industrial markets? An exploratory case study in the healthcare ecosystem. Journal of Business Research, 129, 849-859.
Li, M., & Huang, H. (2022). Application of industrial robots and innovation performance of manufacturing enterprises: The mediating effect of R&D investment and employee knowledge capability. Chinese Human Resources Science, (3), 73-84. [in Chinese]
Li, W., & Zheng, M. (2016). Substantial innovation or strategic innovation? The impact of macro-industrial policy on micro-enterprise innovation. Economic Research Journal, 51(4), 60-73. [in Chinese]
Liu, B. (2019). China in the global value chain: Open strategy and deep integration. China Social Sciences Press. https://d.dedao.cn/EScj00xO3VcjEXON [in Chinese]
Liu, Z. (2017). Economics of education. Beijing Normal University Press. https://d.dedao.cn/EUDhZUieTtqrUdrq [in Chinese]
Mankiw, N. G. (1999). Principles of economics (vol. 2). Peking University Press. [in Chinese]
Pérez, C. (1983). Structural change and assimilation of new technologies in the economic and social systems. Futures, 15(5), 357-375.
Qi, H., Cao, X., & Liu, Y. (2020). The impact of the digital economy on corporate governance: From the perspective of information asymmetry and managerial irrational behavior. Reform, (4), 50-64. [in Chinese]
Romer, P. M. (1990). Endogenous technological change. Journal of Political Economy, 98(5), S71-S102.
Say, J. B. (1997). An introduction to political economy: The production, distribution, and consumption of wealth. The Commercial Press. [in Chinese]
Su, J., & Yang, Y. (2024). Global economic outlook from the perspective of technological innovation: A long-cycle view. Southern Economy, 7, 1-11. [in Chinese]
Tian, X., & Li, R. (2022). Empowering the transformation and development of the real economy through digital technology: An analytical framework based on Schumpeter’s endogenous growth theory. Management World, 38(5), 56-74. [in Chinese]
Wang, C. L., & Ahmed, P. L. (2007). Dynamic capabilities: A review and research agenda. International Journal of Management Reviews, 9(1), 31-51.
Wang, L., Hu, S., & Dong, Z. (2022). Artificial Intelligence technology, task attributes, and occupational substitution risk: Micro-level empirical evidence. Management World, (7), 60-79. [in Chinese]
Wang, R., & Huang, G. (2022). Advanced human capital structure, structure matching, and manufacturing productivity improvement. Statistics and Decision, (11), 88-92. [in Chinese]
Wang, S., & Chen, J. (2019). The technological-economic paradigm of the digital economy. Shanghai Economic Review, (12), 80-94. [in Chinese]
Wang, Y., & Dong, W. (2020). How does the rise of robots affect China’s labor market? Evidence from listed manufacturing companies. Economic Research Journal, 55(10), 159-175. [in Chinese]
Wang, Z. Y., Wang, N., & Shan, X. G. (2021). Research on the issues of China’s technological innovation practice in the stage of innovation 3.0. Science of Science and Management of S&T, (4), 127-141. [in Chinese]
Wu, F., Hu, H., Lin, H., & Ren, X. (2021). The impact of corporate digital transformation on capital market performance: Empirical evidence from stock liquidity. Management World, 37(7), 130-144. [in Chinese]
Xie, M., Xia, Y., Pan, J., & Guo, J. (2020). Artificial Intelligence, technological progress, and low-skilled employment: An empirical study based on Chinese manufacturing enterprises. Chinese Management Science, 28(12), 54-66. [in Chinese]
Xu, D. (2020). Future intelligent road: Analyzing 33 pitfalls of intelligent manufacturing with case studies. Electronic Industry Press. [in Chinese]
Xu, Y., & Xu, H. (2019). Two models of “machine for people” and their social impacts. Cultural Anti-Culture, (3), 88-143. [in Chinese]
Yan, X., Zhu, B., & Ma, C. (2020). The use of industrial robots and manufacturing employment: Evidence from China. Statistical Research, 37(1), 74-87. [in Chinese]
Yang, C. C., & Lin, C. Y. (2009). Does intellectual capital mediate the relationship between HRM and organizational performance? Perspective of a healthcare industry in Taiwan. The International Journal of Human Resource Management, 20(9), 1965-1984.
Ying, L., Yang, J., & Gao, M. (2020). Intelligent manufacturing and corporate performance: An empirical test based on the PSM-DID method. Finance & Accounting Monthly, (12), 11-17. [in Chinese]
Yu, F., Wang, L., & Li, X. (2020). The effects of government subsidies on new energy vehicle enterprises: The moderating role of intelligent transformation. Energy Policy, 141, 111463.
Zhang, Y., & Li, H. (2022). The impact of intelligent transformation on internal labor structure. Human Resource Development of China, 39(1), 98-118. [in Chinese]
Zhao, S., Shi, X., Lu, Y., & Liu, X. (2020). Can mergers and acquisitions promote the optimization and upgrading of labor structure? Financial Research, (10), 150-169. [in Chinese]
Zhou, G., Li, L., & Meng, L. (2021). The impact of intelligence on China’s labor market: Analysis based on employment breadth and intensity. Financial Research, (6), 39-58. [in Chinese]
