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Journal of Management Information Systems Vol. 39 No. 2 2022

Examining the Impact of Algorithmic Control on Uber Drivers’ Technostress

W. Alec Cram1; Martin Wiener2; Monideepa Tarafdar3; Alexander Benlian4

1 School of Accounting & Finance, University of Waterloo, Waterloo, ON, Canada · 2 Technische Universität Dresden, Dresden, Germany · 3 Isenberg School of Management, University of Massachusetts Amherst, Amherst MA · 4 Technische Universität Darmstadt, Darmstadt, Germany

open access

Abstract

This study examines how the use of algorithmic control within gig economy platforms relates to the well-being and behavior of workers. Specifically, we explore how two different forms of algorithmic control—gatekeeping and guiding—correspond with (positive) challenge technostressors and (negative) threat technostressors experienced by Uber drivers. We also examine the moderating impact of algorithmic control transparency on these relationships, as well as the outcomes of technostressors in terms of continuance intentions and workaround use. Based on a survey of 621 U.S.-based Uber drivers, we find that gatekeeping and guiding algorithmic control positively relate to both challenge and threat technostressors. The study bridges the literature on control and technostress by conceptualizing algorithmic control as a condition that puts workers under stress. This stress is found to contribute to important behavioral consequences pertaining to both continuance intentions and workaround use. Findings from our work suggest that gig economy organizations can use algorithmic control to enhance challenge technostressors for their workers, thereby contributing to the cultivation of a more committed workforce. Furthermore, we find evidence disputing the assumption that algorithmic control transparency can mitigate the negative effects of threat technostressors.

DOI
10.1080/07421222.2022.2063556
Volume
39
Issue
2
Pages
426-453
Language
en
Sources
crossref openalex

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