Citation

Welch TF, Gehrke SR, Widita A. Transportmetrica A: Transp. Sci. 2020; 16(1): 43-55.

Copyright

(Copyright © 2020, Informa - Taylor and Francis Group)

DOI

10.1080/23249935.2018.1523250

PMID

unavailable

Abstract

The emergence of new shared-use mobility options such as bikeshare and ride-hailing services render the traditional dichotomy between personal vehicles and public transit somewhat irrelevant. Transportation planners and policymakers have yet to conclude whether these mobility technologies are complementing or competing against existing public transit services. The understanding of this relationship is vital given the increasing uncertainty of funding sources for transit services, but limited by the scarcity of meaningful data provided by the private ride-hailing industry. This study applies big data analytic tools on a unique travel data set to uncover the predictors motivating a half-billion transit, taxi, and bikeshare trips in rail station walksheds across Washington, DC. Study findings indicate travel cost and natural environment factors as well as land use diversity and network connectivity metrics significantly impact the likelihood for an individual to travel via taxi or bikeshare rather than rail.

Language: en

Keywords

big data; bikeshare; mode choice; public transit; Taxi ridership