Paper Type

Short

Paper Number

PACIS2026-2094

Description

Digital labour platforms frequently promote flexibility as a defining feature of gig work the ability to decide when, where, and for how long to work. Yet flexibility and autonomy are often treated as overlapping constructs, obscuring how flexibility is actually produced in everyday practice. Drawing on an interpretive ethnographic study of 29 bike ride-hailing workers in Chennai, India, we develop a process account of how flexibility is produced under algorithmic management. Our findings show that workers form working rules about how an opaque algorithm works, test these through concrete actions, and revise them based on platform responses- a repeating loop through which tried-and-tested responses harden into rules governing when, where, and how long to work. We show that, in bike ride-hailing, flexibility is not a built-in feature of platform design but something workers actively produce through engagement with systems that leave them no control over how their work is executed.

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Jul 5th, 12:00 AM

How Flexibility Congeals: Sociomaterial Negotiation in Bike Ride Hailing Platform Work

Digital labour platforms frequently promote flexibility as a defining feature of gig work the ability to decide when, where, and for how long to work. Yet flexibility and autonomy are often treated as overlapping constructs, obscuring how flexibility is actually produced in everyday practice. Drawing on an interpretive ethnographic study of 29 bike ride-hailing workers in Chennai, India, we develop a process account of how flexibility is produced under algorithmic management. Our findings show that workers form working rules about how an opaque algorithm works, test these through concrete actions, and revise them based on platform responses- a repeating loop through which tried-and-tested responses harden into rules governing when, where, and how long to work. We show that, in bike ride-hailing, flexibility is not a built-in feature of platform design but something workers actively produce through engagement with systems that leave them no control over how their work is executed.