IDEAS home Printed from https://ideas.repec.org/a/eee/eurman/v41y2023i6p899-913.html
   My bibliography  Save this article

Labor process theory and critical HRM: A systematic review and agenda for future research

Author

Listed:
  • Omidi, Afshin
  • Dal Zotto, Cinzia
  • Gandini, Alessandro

Abstract

Labor process theory (LPT) is a critical approach to studies on work and employment; it is rooted in the Marxist tradition, which addresses conflictual relations between capital and labor and connects work transformations with broader structural contexts. LPT has been one of the theoretical lenses through which critical human resource management (HRM) scholars have attempted to challenge taken-for-granted concepts and approaches introduced by mainstream, positivist, and functionalist HRM research. Yet, an effort to consolidate its significance in critical HRM is missing in the extant literature. Drawing on a systematic review of 103 research articles published from 2000 to 2021, the present paper identified four key themes in previous LPT-informed HRM research, including institutional forces, control regimes, solidarity and resistance, and the deskilling-upskilling paradox. Based on this review, the article discusses what critical HRM scholars can learn from this collective understanding of LPT and how they could also employ this theory to advance critical HRM research. The main argument brought forward is the idea that LPT is worthwhile to challenge the excessive optimism propagated by the pluralist approaches in HRM.

Suggested Citation

  • Omidi, Afshin & Dal Zotto, Cinzia & Gandini, Alessandro, 2023. "Labor process theory and critical HRM: A systematic review and agenda for future research," European Management Journal, Elsevier, vol. 41(6), pages 899-913.
    • Handle: RePEc:eee:eurman:v:41:y:2023:i:6:p:899-913
    DOI: 10.1016/j.emj.2023.05.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0263237323000592
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.emj.2023.05.003?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Long Xu & Yunsheng Zhou & Liang Chen, 2024. "Digital Transformation and Breakthrough Innovation in Chinese Manufacturing Firms: Based on Ability-Motivation-Opportunity (AMO) Framework of Human Capital," SAGE Open, , vol. 14(3), pages 21582440241, July.

    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:eee:eurman:v:41:y:2023:i:6:p:899-913. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/115/description#description .

    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.