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

TLDR

Traditional service firms use managers and customers to control workers, but digital platforms replace managers with algorithmically mediated customer ratings that shape workers’ future opportunities. The study investigates how the shift to algorithmic customer control alters the dynamics of control and resistance across the gig work process. Ethnographic data reveal that algorithmic customer control expands organizational control and worker resistance beyond task execution, with workers able to resist most early but needing to adapt tactics as opportunities decline, and that workers can manipulate algorithms through customer interactions in ways platforms cannot fully detect.

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.