IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-04300355.html
   My bibliography  Save this paper

Work Experience on Algorithm-Based Platforms: The Bright and Dark Sides of Turking

Author

Listed:
  • Mehmet A. Orhan

    (Métis Lab EM Normandie - EM Normandie - École de Management de Normandie)

  • Insaf Khelladi

    (PULV - Pôle Universitaire Léonard de Vinci)

  • S. Castellano

    (Métis Lab EM Normandie - EM Normandie - École de Management de Normandie)

  • Sanjay Singh

    (Maynooth University - National University of Ireland Maynooth)

Abstract

The prevalent use of digital labor platforms has transformed the nature of work globally. Such algorithm-based platforms have triggered many technological, legal, ethical, and human resource management challenges. Despite some benefits (i.e., flexibility), the precarious conditions and commodification of jobs are major concerns in these platform-based employment conditions. The remote-work paradigm shift during the COVID-19 pandemic has made the interplay between technology, digitalization, and precarious workers' well-being a critical issue to address. This paper focuses on microtask platforms by examining overall well-being associated with turking as a work experience. Using a sample of 401 Amazon Mechanical Turk workers during the early stage of the COVID-19 pandemic, data were collected on individual conditions affecting the overall quality of workers' lives. The results from two structural equation models demonstrated the direct and mediating effects of task characteristics, excessive working, and financial pressure, mirroring the bright and dark sides of turking. Greater turking task significance and meaningfulness increase personal growth opportunities, ultimately improving workers' perceived quality of life. However, excessive work and greater financial pressure decrease self-acceptance and overall quality of life. This study examines the complicated nature of work experience on algorithm-based platforms by unpacking individual factors that affect workers' well-being. \textcopyright 2022 Elsevier Inc.

Suggested Citation

  • Mehmet A. Orhan & Insaf Khelladi & S. Castellano & Sanjay Singh, 2022. "Work Experience on Algorithm-Based Platforms: The Bright and Dark Sides of Turking," Post-Print hal-04300355, HAL.
  • Handle: RePEc:hal:journl:hal-04300355
    DOI: 10.1016/j.techfore.2022.121907
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:hal:journl:hal-04300355. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.