Case
Uber and driver economics
EPI analysis shows drivers' earnings after costs are far below the headline figures and that the scale of the gig economy is overstated; the New York Times describes behavioural design that lengthens driving hours. US data, 2017–2018.
- Industry
- Ride-hailing
Frameworks applied
This case is read through the frameworks below.
- Transaction cost economicsWhen deciding whether to make or buy an activity, which ones should a business owner keep in-house and which should go to the market or a digital platform?
- Mitigating vs organisational strategies for platformsWhen policymakers want digital platforms to treat workers and users more fairly, should they regulate platforms as owned today or change ownership and governance itself?
- Four risk-shifting mechanisms in AI-driven managementWhen bringing AI into scheduling, timekeeping or productivity monitoring, which risks is an HR manager quietly shifting from the firm onto workers?
Sources
References
Listed A–Z by author surname, Harvard style. A source with a DOI links to https://doi.org/…; one without links to its page or says plainly that it has no DOI.
- Coyle, D. (2017) ‘Precarious and productive work in the digital economy’, National Institute Economic Review, 240(1), pp. R5–R14.doi:10.1177/002795011724000110Source page
- Mishel, L. (2018) Uber and the labor market: Uber drivers' compensation, wages, and the scale of Uber and the gig economy. Washington, DC: Economic Policy Institute.No DOIepi.orgSource page
- Scheiber, N. (2017) How Uber uses psychological tricks to push its drivers' buttons. The New York Times.No DOInytimes.comSource page