RAPID/Collaborative Research: Measuring the Impact of the Re-entry of Ride Sourcing in Austin, Texas: A Natural Experiment Grant uri icon

abstract

  • Approximately one year after suspending services in Austin following the defeat of Proposition 1, Uber and Lyft relaunched ridesharing services in Austin on May 29, 2017. Services resumed in response to Texas House bill 100, which created a statewide regulatory framework for transportation network companies that superseded local ordinances. In response to this development, this Grants for Rapid Response Research (RAPID) collaborative research project will analyze changes to travel behavior after a service disruption has ended. The project represents a unique natural experiment to measure the impact of these services on city infrastructure and the economy. The motivating research question is, "How does the restoration of ride-sourcing services impact travel behavior particularly with regards to number of trips, mode choice and vehicle ownership" A comparative case is provided by the collapse and subsequent reconstruction of the I-35W Bridge in Minneapolis, Minnesota, in which a 25 percent reduction in usage was seen following opening of a replacement bridge. This project will design and implement a travel survey of ride-sourcing passengers in order to quantify the impact on travel behavior as a result of Uber and Lyft restoring ridesharing services in Austin, TX. The survey will utilize a non-random, opt-in sampling methodology, to be administered over an approximate two-month period. The survey data will not be weighted or expanded, as the full universe of former ridesharing passengers is not known. Expected research results have the potential to capture adaptations by passengers and organizations in response to service restoration. The results are also expected to inform ongoing discussions on the impact of similar events on mobility in other cities. Methods for data coding as well as the data themselves will be made available to support subsequent research.

date/time interval

  • 2017 - 2018