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Ride-Hail Drivers, Taxi Drivers and Multiple Jobholders: Who Takes the Most Risks and Why?

Author

Listed:
  • Alexandra D Lefcoe

    (McMaster University, Canada)

  • Catherine E Connelly

    (McMaster University, Canada)

  • Ian R Gellatly

    (University of Alberta, Canada)

Abstract

Little is known about how the use of ride-hail apps (e.g. Uber, Lyft) affects drivers’ propensity to engage in risky behaviours. Drawing on labour process theory, this study examines how algorithmic control of ride-hail drivers encourages risky driving (i.e. violating road safety rules, carrying weapons). Furthermore, the theory of work precarity is used to explain why multiple jobholders (MJHers), who work for ride-hail companies, drive taxis and hold other jobs, may be more likely to take risks while driving due to income insecurity and erratic work hours. The hypotheses are tested in a sample ( N = 191) of ride-hail drivers, taxi drivers and MJHers. The results suggest that MJHers are more likely to engage in risky driving in comparison to ride-hail and taxi drivers. Theoretical, practical and policy implications are discussed.

Suggested Citation

  • Alexandra D Lefcoe & Catherine E Connelly & Ian R Gellatly, 2024. "Ride-Hail Drivers, Taxi Drivers and Multiple Jobholders: Who Takes the Most Risks and Why?," Work, Employment & Society, British Sociological Association, vol. 38(5), pages 1307-1332, October.
    • Handle: RePEc:sae:woemps:v:38:y:2024:i:5:p:1307-1332
    DOI: 10.1177/09500170231185212
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    References listed on IDEAS

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    Cited by:

    1. Mallett, Richard, 2025. "Speed traps: on the turbulent logics of the platformed motorcycle," LSE Research Online Documents on Economics 127625, London School of Economics and Political Science, LSE Library.

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