Expanding the Locus of Resistance: Understanding the Co-constitution of Control and Resistance in the Gig Economy

Lindsey D. Cameron () and Hatim Rahman ()
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Lindsey D. Cameron: Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104
Hatim Rahman: Kellogg School of Management, Northwestern University, Evanston, Illinois 60208

Organization Science, 2022, vol. 33, issue 1, 38-58

Abstract: Existing literature examines control and resistance in the context of service organizations that rely on both managers and customers to control workers during the execution of work. Digital platform companies, however, eschew managers in favor of algorithmically mediated customer control—that is, customers rate workers, and algorithms tally and track these ratings to control workers’ future platform-based opportunities. How has this shift in the distribution of control among platforms, customers, and workers affected the relationship between control and resistance? Drawing on workers’ experiences from a comparative ethnography of two of the largest platform companies, we find that platform use of algorithmically mediated customer control has expanded the service encounter such that organizational control and workers’ resistance extend well beyond the execution of work. We find that workers have the most latitude to deploy resistance early in the labor process but must adjust their resistance tactics because their ability to resist decreases in each subsequent stage of the labor process. Our paper, thus, develops understanding of resistance by examining the relationship between control and resistance before, during, and after a task, providing insight into how control and resistance function in the gig economy. We also demonstrate the limitations of platforms’ reliance on algorithmically mediated customer control by illuminating how workers’ everyday interactions with customers can influence and manipulate algorithms in ways that platforms cannot always observe.

Keywords: algorithms; control resistance; labor process theory; service work; gig economy; Uber; Lyft (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ororsc:v:33:y:2022:i:1:p:38-58

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