IDEAS home Printed from https://ideas.repec.org/a/eee/respol/v54y2025i4s0048733325000198.html
   My bibliography  Save this article

A processual approach to skill changes in digital automation: The case of the platform economy in the service sector

Author

Listed:
  • XING, Jack Linzhou
  • SHARIF, Naubahar

Abstract

We introduce the “processual approach” to skill changes in the current wave of digital automation, which imposes comprehensive and complex impacts on skills. The approach conceptualizes work as a set of processes, each consisting of a sequence of events. In each event, a worker and/or machine make judgments and take actions to move to the next event. The processual approach asks whether and how machines influence workers' judgments or actions during each event and interrupt or transform relationships between judgments and actions. The approach enables micro-to-middle-range, inductive theorization of skill changes. To further refine the approach and demonstrate how to apply the approach, we study the case of taxi and ride-hailing, finding that service skill changes emphasize the repositioning and refocusing of skills and the interruption of workers' micro-adaptations rather than the replacement or elimination of skills. We also compare our theory with the classic Zuboffian reskilling thesis, revealing that the dual potential—automating and informating—of the current automation technologies influence distinct and separate parts of organizations, excluding platform workers from opportunities to learn transferable skills. The processual approach avoids pre-assigned and hierarchical categorization of skills, adopts a symmetric view of the role of technological and social factors in skill changes, and applies to a wide spectrum of work, especially service work.

Suggested Citation

  • XING, Jack Linzhou & SHARIF, Naubahar, 2025. "A processual approach to skill changes in digital automation: The case of the platform economy in the service sector," Research Policy, Elsevier, vol. 54(4).
  • Handle: RePEc:eee:respol:v:54:y:2025:i:4:s0048733325000198
    DOI: 10.1016/j.respol.2025.105190
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0048733325000198
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.respol.2025.105190?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.

    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:respol:v:54:y:2025:i:4:s0048733325000198. 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/locate/respol .

    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.