IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i15p7006-d1715707.html
   My bibliography  Save this article

Empowering the Intelligent Transformation of the Manufacturing Sector Through New Quality Productive Forces: Value Implications, Theoretical Analysis, and Empirical Examination

Author

Listed:
  • Yinyan Hu

    (Department of Public Administration, School of Humanities and Law, Hebei University of Technology, Tianjin 300131, China)

  • Xinran Jia

    (Department of Public Administration, School of Humanities and Law, Hebei University of Technology, Tianjin 300131, China)

Abstract

Achieving sustainable development goals remains a core issue in global development. In response, China has proposed the development of new quality productive forces (NQPFs) through innovative thinking, emphasizing that fostering NQPFs is both an intrinsic requirement and a pivotal focus for advancing high-quality development. Concurrently, the intelligent transformation of the manufacturing sector serves as a critical direction for China’s economic restructuring and upgrading. This paper places “new quality productive forces” and “intelligent transformation of manufacturing” within the same analytical framework. Starting from the logical chain of “new quality productive forces—three major mechanisms—intelligent transformation of manufacturing,” it concretizes the value implications of new quality productive forces into a systematic conceptual framework driven by the synergistic interaction of three major mechanisms: the mechanism of revolutionary technological breakthroughs, the mechanism of innovative allocation of production factors, and the mechanism of deep industrial transformation and upgrading. This study constructs a “3322” evaluation index system for NQPFs, based on three formative processes, three driving forces, two supporting systems, and two-dimensional characteristics. Simultaneously, it builds an evaluation index system for the intelligent transformation of manufacturing, encompassing intelligent technology, intelligent applications, and intelligent benefits. Using national time-series data from 2012 to 2023, this study assesses the development levels of both NQPFs and the intelligent transformation of manufacturing during this period. The study further analyzes the impact of NQPFs on the intelligent transformation of the manufacturing sector. The research results indicate the following: (1) NQPFs drive the intelligent transformation of the manufacturing industry through the three mechanisms of innovative allocation of production factors, revolutionary breakthroughs in technology, and deep transformation and upgrading of industries. (2) The development of NQPFs exhibits a slow upward trend; however, the outbreak of the pandemic and Sino-US trade frictions have caused significant disruptions to the development of new-type productive forces. (3) The level of intelligent manufacturing continues to improve; however, from 2020 to 2023, due to the impact of the COVID-19 pandemic and Sino-US trade conflicts, the level of intelligent benefits has slightly declined. (4) NQPFs exert a powerful driving force on the intelligent transformation of manufacturing, exerting a significant positive impact on intelligent technology, intelligent applications, and intelligent efficiency levels.

Suggested Citation

  • Yinyan Hu & Xinran Jia, 2025. "Empowering the Intelligent Transformation of the Manufacturing Sector Through New Quality Productive Forces: Value Implications, Theoretical Analysis, and Empirical Examination," Sustainability, MDPI, vol. 17(15), pages 1-33, August.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:15:p:7006-:d:1715707
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/15/7006/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/15/7006/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Arthur, W Brian, 1989. "Competing Technologies, Increasing Returns, and Lock-In by Historical Events," Economic Journal, Royal Economic Society, vol. 99(394), pages 116-131, March.
    2. repec:hal:spmain:info:hdl:2441/170cd4sul89ddpnfuomvfm0jc0 is not listed on IDEAS
    3. Guo, Xiaochuan & Li, Mengmeng & Wang, Yanlin & Mardani, Abbas, 2023. "Does digital transformation improve the firm’s performance? From the perspective of digitalization paradox and managerial myopia," Journal of Business Research, Elsevier, vol. 163(C).
    4. 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.
    5. Philippe Aghion & Céline Antonin & Simon Bunel & Xavier Jaravel, 2020. "What Are the Labor and Product Market Effects of Automation? New Evidence from France," SciencePo Working papers Main hal-03403062, HAL.
    6. Carlota Perez, 2010. "Technological revolutions and techno-economic paradigms," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 34(1), pages 185-202, January.
    7. DeCanio, Stephen J., 2016. "Robots and humans – complements or substitutes?," Journal of Macroeconomics, Elsevier, vol. 49(C), pages 280-291.
    8. repec:spo:wpmain:info:hdl:2441/170cd4sul89ddpnfuomvfm0jc0 is not listed on IDEAS
    9. repec:spo:wpmain:info:hdl:2441/3n1gbsj6rs80ipqv9d42nfd0ge is not listed on IDEAS
    10. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    11. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    12. Lin, Changqing & Xiao, Shengpeng & Yin, Zihui, 2022. "How do industrial robots applications affect the quality upgrade of Chinese export trade?," Telecommunications Policy, Elsevier, vol. 46(10).
    13. Song Xu & Jiating Wang & Zhisheng Peng, 2024. "Study on the Promotional Effect and Mechanism of New Quality Productive Forces on Green Development," Sustainability, MDPI, vol. 16(20), pages 1-25, October.
    14. Lin, Boqiang & Xu, Chongchong, 2024. "Enhancing energy-environmental performance through industrial intelligence: Insights from Chinese prefectural-level cities," Applied Energy, Elsevier, vol. 365(C).
    15. Andreas Hornstein & Per Krusell, 1996. "Can Technology Improvements Cause Productivity Slowdowns?," NBER Chapters, in: NBER Macroeconomics Annual 1996, Volume 11, pages 209-276, National Bureau of Economic Research, Inc.
    16. Chin, Tachia & Li, Zhisheng & Huang, Leping & Li, Xinyu, 2025. "How artificial intelligence promotes new quality productive forces of firms: A dynamic capability view," Technological Forecasting and Social Change, Elsevier, vol. 216(C).
    17. Nasiri, Mina & Ukko, Juhani & Saunila, Minna & Rantala, Tero, 2020. "Managing the digital supply chain: The role of smart technologies," Technovation, Elsevier, vol. 96.
    18. repec:hal:spmain:info:hdl:2441/3n1gbsj6rs80ipqv9d42nfd0ge is not listed on IDEAS
    19. Bashir, Muhammad Farhan & Pan, Yanchun & Shahbaz, Muhammad & Ghosh, Sudeshna, 2023. "How energy transition and environmental innovation ensure environmental sustainability? Contextual evidence from Top-10 manufacturing countries," Renewable Energy, Elsevier, vol. 204(C), pages 697-709.
    20. Lee, Chien-Chiang & Qin, Shuai & Li, Yaya, 2022. "Does industrial robot application promote green technology innovation in the manufacturing industry?," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    21. Maryam Asghari, 2010. "The Stringency of Environmental Regulations and Technological Change: A Specific Test of the Porter Hypothesis," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 15(3), pages 95-115, fall.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gao, Jie & Li, Zhizhuo & Nguyen, Thithuha & Zhang, Wentao, 2025. "Digital transformation and enterprise employment," International Review of Economics & Finance, Elsevier, vol. 99(C).
    2. Liu, Yingji & Shen, Fangbing & Guo, Ju & Hu, Guoheng & Song, Yuegang, 2025. "Can artificial intelligence technology improve companies' capacity for green innovation? Evidence from listed companies in China," Energy Economics, Elsevier, vol. 143(C).
    3. Zhang, Xinchun & Sun, Murong & Liu, Jianxu & Xu, Aijia, 2024. "The nexus between industrial robot and employment in China: The effects of technology substitution and technology creation," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    4. Davide Dottori, 2021. "Robots and employment: evidence from Italy," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(2), pages 739-795, July.
    5. Chen, Chinchih & Frey, Carl Benedikt & Presidente, Giorgio, 2022. "Automation or globalization? The impacts of robots and Chinese imports on jobs in the United Kingdom," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 528-542.
    6. Xin, Baogui & Ye, Xiaopu, 2024. "Robotics applications, inclusive employment and income disparity," Technology in Society, Elsevier, vol. 78(C).
    7. Camiña, Ester & Díaz-Chao, Ángel & Torrent-Sellens, Joan, 2020. "Automation technologies: Long-term effects for Spanish industrial firms," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    8. Liang, Peng & Liang, Lin & Tang, Xinhui, 2024. "The impact of digital-oriented mergers and acquisitions on enterprise labor demand," International Review of Financial Analysis, Elsevier, vol. 96(PB).
    9. Du, Junhong & He, Jiajia & Yang, Jing & Chen, Xiaohong, 2024. "How industrial robots affect labor income share in task model: Evidence from Chinese A-share listed companies," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
    10. Jasmine Mondolo, 2022. "The composite link between technological change and employment: A survey of the literature," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1027-1068, September.
    11. Xu, Chongchong & Lin, Boqiang, 2025. "The AI-sustainability Nexus: How does intelligent transformation affect corporate green innovation?," International Review of Financial Analysis, Elsevier, vol. 102(C).
    12. Pablo Casas & José L. Torres, 2024. "Government size and automation," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 31(3), pages 780-807, June.
    13. Stefan Jestl, 2022. "Industrial Robots, and Information and Communication Technology: The Employment Effects in EU Labour Markets," wiiw Working Papers 215, The Vienna Institute for International Economic Studies, wiiw.
    14. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2025. "What workers and robots do: An activity-based analysis of the impact of robotization on changes in local employment," Research Policy, Elsevier, vol. 54(1).
    15. Rita Strohmaier & Marlies Schuetz & Simone Vannuccini, 2019. "A systemic perspective on socioeconomic transformation in the digital age," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 46(3), pages 361-378, September.
    16. Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2022. "Robots and the origin of their labour-saving impact," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    17. Zhou, Yuwen & Shi, Xin, 2025. "How does digital technology adoption affect corporate employment? Evidence from China," Economic Modelling, Elsevier, vol. 147(C).
    18. Gries, Thomas & Naudé, Wim, 2022. "Modelling artificial intelligence in economics," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 56, pages 1-12.
    19. Zhihui Dai & Yue Niu & Hongru Zhang & Xiaodi Niu, 2022. "Impact of the Transforming and Upgrading of China’s Labor-Intensive Manufacturing Industry on the Labor Market," Sustainability, MDPI, vol. 14(21), pages 1-25, October.
    20. Carlos Bianchi & Hugo Laguna, 2020. "Firm’s innovation strategies and employment: new evidence from Uruguay," Documentos de Trabajo (working papers) 20-06, Instituto de Economía - IECON.

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2025:i:15:p:7006-:d:1715707. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.