Measuring the Impact of an Unanticipated Disruption of Uber/Lyft in Austin, TX

18 Pages Posted: 31 May 2017 Last revised: 20 Mar 2018

See all articles by Robert Hampshire

Robert Hampshire

University of Michigan at Ann Arbor - Transportation Research Institute

Chris Simek

Texas A&M University - Texas Transportation Institute

Tayo Fabusuyi

University of Michigan at Ann Arbor - Transportation Research Institute; Numeritics

Xuan Di

Columbia University

Xi Chen

University of Michigan at Dearborn

Date Written: May 31, 2017

Abstract

On May 7, 2016, residents of Austin, Texas, voted against Proposition 1, which would have allowed ridesourcing/transportation networking companies (TNCs) to continue using their own background check systems. The defeat of the proposition prompted Uber and Lyft to suspend services in Austin indefinitely. The disruption provided for a natural experiment to evaluate the impact of Uber and Lyft on users’ travel demand and the supply side implications of the entry of new players. Our paper focuses solely on the demand side user response to the disruption. In examining the impact, we conducted an online survey that combines stated and revealed preference questions (N=1,840) of former Uber and/or Lyft users in Austin to explore the effect of the disruption on travel behavior.

In order to test our hypothesis of the impact of the service suspension on changes in travel mode choice and trip frequency we used regression analyses to model both the before and after travel behavioral pattern. Our analysis revealed that of the population surveyed, 45% switched to the use of personal vehicles after disruption while only 3% shifted to public transit. Individuals who switched to personal vehicles also include 8.9% of respondents who reported purchasing a vehicle in response to the service disruption. In addition, an individual who switched to a personal vehicle increased his or her probability of a higher trip frequency post disruption by 14%. The probability of a higher trip frequency for individuals who were satisfied with the quality of Uber and Lyft services pre-disruption however decreased from 21% to 6%.

Keywords: On-demand transportation, ride-sourcing, ride-hailing, transportation network companies, service suspension, travel behavior, vehicle ownership, mode shift

Suggested Citation

Hampshire, Robert and Simek, Chris and Fabusuyi, Tayo and Di, Xuan and Chen, Xi, Measuring the Impact of an Unanticipated Disruption of Uber/Lyft in Austin, TX (May 31, 2017). Available at SSRN: https://ssrn.com/abstract=2977969 or http://dx.doi.org/10.2139/ssrn.2977969

Robert Hampshire (Contact Author)

University of Michigan at Ann Arbor - Transportation Research Institute ( email )

2901 Baxter Road
Ann Arbor, MI 48109
United States

Chris Simek

Texas A&M University - Texas Transportation Institute ( email )

College Station, TX 77843-3135
United States

Tayo Fabusuyi

University of Michigan at Ann Arbor - Transportation Research Institute ( email )

2901 Baxter Road
Ann Arbor, MI 48109
United States

Numeritics ( email )

5907 Penn Avenue
Suite 313
Pittsburgh, PA 15206

Xuan Di

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

Xi Chen

University of Michigan at Dearborn ( email )

4901 Evergreen Road
Dearborn, MI 48128-1491
United States

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