Authors: Steven Gehrke*, Northern Arizona University
Topics: Transportation Geography, Urban and Regional Planning
Keywords: Uber, Ride-hailing, Ridesourcing, Transportation Network Company (TNC), Built Environment
Session Type: Paper
Presentation File: No File Uploaded
Chiefly led by Uber, on-demand ride-hailing services have transformed the urban American transportation landscape in merely the past decade. Utilizing the proliferation of internet-enabled smartphones, this app-based company has provided city inhabitants with a convenient and reliable door-to-door mobility service, which has arguably improved car-based accessibility while also generating a host of negative environmental and societal externalities. While to date the utilization of Uber has largely been an urban phenomenon, the lasting success of this new mobility option likely rests within its ability to expand its services into suburban communities. Yet, given the competitive nature of the ride-hailing marketplace and genuine concerns over passenger and driver anonymity, transportation planners and urban policymakers have been stymied in their ability to access the disaggregate data sets needed to help assess whether these services are in fact extending beyond city centers and identify which factors may be contributing to any expansion into more peripheral suburban neighborhoods. By introducing a creative strategy using the privacy-related suppression processes of Uber Movement data, this study quantifies the continued expansion of Uber’s ride-hailing service into outlying communities from 2016 to 2018 by employing a multilevel modeling approach to recognize the neighborhood-level socioeconomic and built environment factors most related to this service expansion in three major American cities: Boston, San Francisco, and Washington, DC.
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