IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2023i2p1239-d1030818.html
   My bibliography  Save this article

Workers’ Health under Algorithmic Management: Emerging Findings and Urgent Research Questions

Author

Listed:
  • Emilia F. Vignola

    (Department of Community Health and Social Sciences, City University of New York Graduate School of Public Health and Health Policy, 55 West 125th Street, New York, NY 10027, USA)

  • Sherry Baron

    (Barry Commoner Center for Health and the Environment, Queens College, City University of New York, 311 Remsen Hall, 65-30 Kissena Blvd, Queens, NY 11367, USA)

  • Elizabeth Abreu Plasencia

    (Barry Commoner Center for Health and the Environment, Queens College, City University of New York, 311 Remsen Hall, 65-30 Kissena Blvd, Queens, NY 11367, USA)

  • Mustafa Hussein

    (Department of Health Policy and Management, City University of New York Graduate School of Public Health and Health Policy, 55 West 125th Street, New York, NY 10027, USA)

  • Nevin Cohen

    (Department of Health Policy and Management, City University of New York Graduate School of Public Health and Health Policy, 55 West 125th Street, New York, NY 10027, USA)

Abstract

Algorithms are increasingly used instead of humans to perform core management functions, yet public health research on the implications of this phenomenon for worker health and well-being has not kept pace with these changing work arrangements. Algorithmic management has the potential to influence several dimensions of job quality with known links to worker health, including workload, income security, task significance, schedule stability, socioemotional rewards, interpersonal relations, decision authority, and organizational trust. To describe the ways algorithmic management may influence workers’ health, this review summarizes available literature from public health, sociology, management science, and human-computer interaction studies, highlighting the dimensions of job quality associated with work stress and occupational safety. We focus on the example of work for platform-based food and grocery delivery companies; these businesses are growing rapidly worldwide and their effects on workers and policies to address those effects have received significant attention. We conclude with a discussion of research challenges and needs, with the goal of understanding and addressing the effects of this increasingly used technology on worker health and health equity.

Suggested Citation

  • Emilia F. Vignola & Sherry Baron & Elizabeth Abreu Plasencia & Mustafa Hussein & Nevin Cohen, 2023. "Workers’ Health under Algorithmic Management: Emerging Findings and Urgent Research Questions," IJERPH, MDPI, vol. 20(2), pages 1-14, January.
  • Handle: RePEc:gam:jijerp:v:20:y:2023:i:2:p:1239-:d:1030818
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/2/1239/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/20/2/1239/
    Download Restriction: no
    ---><---

    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:jijerp:v:20:y:2023:i:2:p:1239-:d:1030818. 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: 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.