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

Work, Employment and Society, Ahead of Print.
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.

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Posted in: Journal Article Abstracts on 09/09/2023 | Link to this post on IFP |
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