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The implications of ridehailing for risky driving and road accident injuries and fatalities

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  • Kirk, David S.
  • Cavalli, Nicolo
  • Brazil, Noli

Abstract

The nature of transportation has fundamentally transformed in recent years with the rise of ridehailing providers such as Uber. Yet, few studies have examined whether there is an association between ridehailing and rates of road accident injuries, and virtually all of the existing studies focus on the exceptional case of the United States. In this study, we exploit differences in the timing of the deployment of Uber across Britain to test the association between the advent of Uber's ridehailing services and rates of fatal and non-fatal road accidents. We find that the deployment of Uber in Great Britain is associated with a marginally significant reduction in the number of serious road accident injuries (e.g., fractures and internal injuries), although not the number of serious accidents. Slight injuries (e.g., sprains and bruises) declined outside of London after the rollout of Uber, but increased within London. We do not observe a statistically significant association between Uber and traffic fatalities. One interpretation for the decline in serious road injuries is that Uber may be a substitute form of transportation for risky drivers, including drink-drivers. However, ridehailing is also a substitute for public transit, particularly buses. The increase in the number of cars on the road may explain why slight injuries increased in London following Uber's rollout.

Suggested Citation

  • Kirk, David S. & Cavalli, Nicolo & Brazil, Noli, 2020. "The implications of ridehailing for risky driving and road accident injuries and fatalities," Social Science & Medicine, Elsevier, vol. 250(C).
    • Handle: RePEc:eee:socmed:v:250:y:2020:i:c:s0277953620300125
    DOI: 10.1016/j.socscimed.2020.112793
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    References listed on IDEAS

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    1. Angela K. Dills & Sean E. Mulholland, 2018. "Ride‐Sharing, Fatal Crashes, and Crime," Southern Economic Journal, John Wiley & Sons, vol. 84(4), pages 965-991, April.
    2. Maarten L. Buis, 2010. "Stata tip 87: Interpretation of interactions in nonlinear models," Stata Journal, StataCorp LP, vol. 10(2), pages 305-308, June.
    3. Jessica Lynn Peck, 2017. "New York City Drunk Driving After Uber," Working Papers 13, City University of New York Graduate Center, Ph.D. Program in Economics.
    4. John M. Barrios & Yael Hochberg & Hanyi Yi, 2020. "The Cost of Convenience: Ridehailing and Traffic Fatalities," NBER Working Papers 26783, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Andrea Gilardi & Jorge Mateu & Riccardo Borgoni & Robin Lovelace, 2022. "Multivariate hierarchical analysis of car crashes data considering a spatial network lattice," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1150-1177, July.
    2. Eleftheria Kontou & Noreen McDonald, 2021. "Associating ridesourcing with road safety outcomes: Insights from Austin, Texas," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-18, March.
    3. Wadud, Zia, 2020. "The effects of e-ridehailing on motorcycle ownership in an emerging-country megacity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 301-312.
    4. María Flor & Armando Ortuño & Begoña Guirao, 2022. "Does the Implementation of Ride-Hailing Services Affect Urban Road Safety? The Experience of Madrid," IJERPH, MDPI, vol. 19(5), pages 1-18, March.

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