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Algorithmic control: a disruption to motivation of gig workers? A critical review

Author

Listed:
  • Shalini Sharma

    (GNIOT Institute of Management Studies)

  • Shikha Bhardwaj

    (IIM Sambalpur - Indian Institute of Management Sambalpur)

  • Bhumika Gupta

    (LITEM - Laboratoire en Innovation, Technologies, Economie et Management (EA 7363) - UEVE - Université d'Évry-Val-d'Essonne - Université Paris-Saclay - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], IMT-BS - MMS - Département Management, Marketing et Stratégie - TEM - Télécom Ecole de Management - IMT - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris])

Abstract

Organizations rely on algorithms to exercise mechanized control over workers – referred to as algorithmic control (AC). The use of algorithmic control has evolved into a commonplace with platform-based work in the gig economy, where independent workers are paid for completing a given task (or "gig"). The gig economy is on a steep rise after the onset of the pandemic because employers are more concerned about smaller pieces of jobs being taken up by temporary labor, thereby saving on the investment in full-time resources. Motivation among the gig workers has always been debatable, especially with the onset of AC on the gig workers. This research is an attempt to analyze the disruption of the motivation of gig workers through digital platforms taking self-determination theory (SDT) and social exchange theory (SET) of motivation into consideration. Grounded on the theory of SET and SDT, this chapter explains the underlying characteristics of algorithmic control affecting employee motivation in the gig economy. This is a conceptual framework for the disruption of motivation of the gig workers through the IT-enabled checks on the progress of the gig workers. The future avenues of this research may gather deeper insights on the well-being of gig work and its subsequent impact on family-life integration. This chapter uniquely explores the lesser researched phenomena in the gig economy and highlights the gray side of algorithmic control on gig workers' motivation.

Suggested Citation

  • Shalini Sharma & Shikha Bhardwaj & Bhumika Gupta, 2023. "Algorithmic control: a disruption to motivation of gig workers? A critical review," Post-Print hal-04133195, HAL.
  • Handle: RePEc:hal:journl:hal-04133195
    DOI: 10.1007/978-3-031-23432-3_1
    as

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