The Heterogeneous Effects of P2P Ride-Hailing on Traffic: Evidence from Uber’s Entry in California

Despite their promise, popularity, and rapid growth, the transit implications of ride-hailing platforms (e.g., Uber, Lyft) are not altogether clear. On the one hand, ride-hailing services can provide pooling (i.e., traffic reductions) advantages by efficiently matching customer demand (i.e., trips) with resources (i.e., cars) or by facilitating car-sharing. On the other hand, ride-hailing may also induce extra travel because of increased convenience and travel mode substitution, which may create crowding (i.e., traffic increases). The authors seek to reconcile these divergent perspectives here, exploring the heterogeneous determinants of ride-hailing's effects. Taking advantage of Uber's staggered entry into various geographic markets in California, the authors execute a regression-based difference-in-differences analysis to estimate the impact of ride-hailing services on traffic volumes. Using monthly micro data from more than 9,000 vehicle detector station units deployed across California, the authors show that Uber's effect (either pooling or crowding) on traffic depends on various contextual factors. The authors find some evidence of pooling effects on weekdays; however, Uber's entry leads to significant crowding effects on weekends. Furthermore, the crowding effect is amplified on interior roads and in areas characterized by high population density. Although ride-hailing seems to have a substitution effect on public transportation, the authors find ride-hailing services may have a complementary effect for carpooling users. Finally, the authors show that premium ride-hailing services (e.g., Uber Black) almost exclusively lead to a crowding effect. The authors conduct a battery of robustness tests (e.g., propensity score matching, alternative treatment approaches, placebo tests) to ensure the consistency of our findings.

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    • Abstracts reprinted with permission of INFORMS (Institute for Operations Research and the Management Sciences, http://www.informs.org).
  • Authors:
    • Dhanorkar, Suvrat
    • Burtch, Gordon
  • Publication Date: 2022-5

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  • English

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  • Accession Number: 01849401
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jun 24 2022 10:54AM