IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0299194.html

How automated machines influence employment in manufacturing enterprises?

Author

Listed:
  • Hong Jiang
  • Yingfan Ge
  • Chunhao Yang
  • Hongxin Yu

Abstract

This paper theoretically analyzes and empirically examines the impact and mechanisms of automated machines on employment in manufacturing enterprises, drawing on task-based model and using micro data from listed Chinese manufacturing enterprises between 2012 and 2019. Our findings reveal that: (1) Automated machines in manufacturing enterprises leads to a substitution effect on the total labor force, with a substitution effect on low-skilled labor and a creation effect on high-skilled labor in terms of employment structure. (2) Further analysis indicates that automated machines primarily have a positive effect on R&D and technical staff, a non-significant effect on sales staff, and a negative impact on production, administrative, and financial staff. (3) The primary influencing mechanisms of automated machines on employment in manufacturing firms are productivity effects and output scale effects, based on the mediation effect model. (4) Considering the industry linkage effect, we employ the input-output method and the Input-Output Table and find that automated machines for upstream (downstream) manufacturing enterprises will result in a substitution effect on employment for downstream (upstream) enterprises. The novelties and research contributions are as follows: (1) we conduct a structural decomposition of total employment, and further decompose employment positions into production, R&D, sales, finance, and administration. (2) We try to investigate the industry linkage effect about the impact of automated machines on the employment of upstream and downstream enterprises. (3) We use data from listed manufacturing companies, and the data of existing research are about provincial and industry-level data.

Suggested Citation

  • Hong Jiang & Yingfan Ge & Chunhao Yang & Hongxin Yu, 2024. "How automated machines influence employment in manufacturing enterprises?," PLOS ONE, Public Library of Science, vol. 19(3), pages 1-21, March.
  • Handle: RePEc:plo:pone00:0299194
    DOI: 10.1371/journal.pone.0299194
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0299194
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0299194&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0299194?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jay Dixon & Bryan Hong & Lynn Wu, 2021. "The Robot Revolution: Managerial and Employment Consequences for Firms," Management Science, INFORMS, vol. 67(9), pages 5586-5605, September.
    2. Lordan, Grace & Neumark, David, 2018. "People versus machines: The impact of minimum wages on automatable jobs," Labour Economics, Elsevier, vol. 52(C), pages 40-53.
    3. Wassily Leontief, 1955. "Some Basic Problems of Empirical Input-Output Analysis," NBER Chapters, in: Input-Output Analysis: An Appraisal, pages 9-52, National Bureau of Economic Research, Inc.
    4. Südekum, Jens & Dauth, Wolfgang & Findeisen, Sebastian & Woessner, Nicole, 2017. "German Robots – The Impact of Industrial Robots on Workers," CEPR Discussion Papers 12306, Centre for Economic Policy Research.
    5. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation, and Work," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 197-236, National Bureau of Economic Research, Inc.
    6. Daron Acemoglu & Pascual Restrepo, 2017. "Secular Stagnation? The Effect of Aging on Economic Growth in the Age of Automation," American Economic Review, American Economic Association, vol. 107(5), pages 174-179, May.
    7. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - Working Papers Series dp-298, Boston University - Department of Economics.
    8. Allen, Robert C., 2009. "Engels' pause: Technical change, capital accumulation, and inequality in the british industrial revolution," Explorations in Economic History, Elsevier, vol. 46(4), pages 418-435, October.
    9. Trajtenberg, Manuel, 2018. "AI as the next GPT: a Political-Economy Perspective," CEPR Discussion Papers 12721, Centre for Economic Policy Research.
    10. Paul Goldsmith-Pinkham & Isaac Sorkin & Henry Swift, 2020. "Bartik Instruments: What, When, Why, and How," American Economic Review, American Economic Association, vol. 110(8), pages 2586-2624, August.
    11. Dauth, Wolfgang & Findeisen, Sebastian & Südekum, Jens & Wößner, Nicole, 2017. "German robots - the impact of industrial robots on workers," IAB-Discussion Paper 201730, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    12. de Vries, Gaaitzen J. & Gentile, Elisabetta & Miroudot, Sébastien & Wacker, Konstantin M., 2020. "The rise of robots and the fall of routine jobs," Labour Economics, Elsevier, vol. 66(C).
    13. David H. Autor & Lawrence F. Katz & Alan B. Krueger, 1998. "Computing Inequality: Have Computers Changed the Labor Market?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(4), pages 1169-1213.
    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. 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).
    2. Mahuaqing Zuo & Yuhan Zhao & Shasha Yu, 2024. "Industrial robot applications and individual migration decision: evidence from households in China," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    3. Ana L. ABELIANSKY & Eda ALGUR & David E. BLOOM & Klaus PRETTNER, 2020. "The future of work: Meeting the global challenges of demographic change and automation," International Labour Review, International Labour Organization, vol. 159(3), pages 285-306, September.
    4. Wang, Ting & Zhang, Yi & Liu, Chun, 2024. "Robot adoption and employment adjustment: Firm-level evidence from China," China Economic Review, Elsevier, vol. 84(C).
    5. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "Economic Policy for Artificial Intelligence," Innovation Policy and the Economy, University of Chicago Press, vol. 19(1), pages 139-159.
    6. Klump, Rainer & Jurkat, Anne & Schneider, Florian, 2021. "Tracking the rise of robots: A survey of the IFR database and its applications," MPRA Paper 107909, University Library of Munich, Germany.
    7. Lei Xia & Qingjiang Han & Shui Yu, 2024. "RETRACTED ARTICLE: Sustainable manufacturing intelligence: pathways for high-quality and energy efficient economic growth," Economic Change and Restructuring, Springer, vol. 57(3), pages 1-30, June.
    8. Albrecht, Thorben & Kellermann, Christian, 2020. "Künstliche Intelligenz und die Zukunft der digitalen Arbeitsgesellschaft: Konturen einer ganzheitlichen Technikfolgenabschätzung," Working Paper Forschungsförderung 200, Hans-Böckler-Stiftung, Düsseldorf.
    9. Ben Vermeulen & Jan Kesselhut & Andreas Pyka & Pier Paolo Saviotti, 2018. "The Impact of Automation on Employment: Just the Usual Structural Change?," Sustainability, MDPI, vol. 10(5), pages 1-27, May.
    10. Ke-Liang Wang & Ting-Ting Sun & Ru-Yu Xu, 2023. "The impact of artificial intelligence on total factor productivity: empirical evidence from China’s manufacturing enterprises," Economic Change and Restructuring, Springer, vol. 56(2), pages 1113-1146, April.
    11. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2021. "Stop worrying and love the robot: An activity-based approach to assess the impact of robotization on employment dynamics," GLO Discussion Paper Series 802, Global Labor Organization (GLO).
    12. Jie Zhou, 2024. "The Impact of the Digital Economy on Employment Scale in the Yangtze River Delta Region," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 14(5), pages 1-5.
    13. Heluo, Yuxi & Fabel, Oliver, 2024. "Job computerization, occupational employment and wages: A comparative study of the United States, Germany, and Japan," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    14. Jia, Nan & Yan, Xueling & Yu, Shule, 2024. "Does increasing robot density exacerbate wealth inequality?," Journal of Asian Economics, Elsevier, vol. 95(C).
    15. Stähler, Nikolai, 2021. "The Impact of Aging and Automation on the Macroeconomy and Inequality," Journal of Macroeconomics, Elsevier, vol. 67(C).
    16. 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.
    17. Pablo Casas & Concepción Román, 2024. "The impact of artificial intelligence in the early retirement decision," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 51(3), pages 583-618, August.
    18. Mutascu, Mihai, 2021. "Artificial intelligence and unemployment: New insights," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 653-667.
    19. Fossen, Frank M. & Sorgner, Alina, 2022. "New digital technologies and heterogeneous wage and employment dynamics in the United States: Evidence from individual-level data," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    20. Geiger, Niels & Prettner, Klaus & Schwarzer, Johannes A., 2018. "Automatisierung, Wachstum und Ungleichheit," Hohenheim Discussion Papers in Business, Economics and Social Sciences 13-2018, University of Hohenheim, Faculty of Business, Economics and Social Sciences.

    More about this item

    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:plo:pone00:0299194. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.