Spatial disparities of Uber accessibility: An exploratory analysis in Atlanta, USA

Mingshu Wang (Corresponding Author), Lan Mu

Research output: Contribution to journalArticleAcademicpeer-review

33 Citations (Scopus)

Abstract

Inequality of accessibility in transportation systems is a constant concern, which is intensified by the transportation economization process and the digital divide. How should the accessibility of crowdsourced transportation is measured and understood? Without any prior assumption, this paper openly explores spatial disparities of accessibility in the city of Atlanta, USA using both the UberX (the most popular Uber product) and the UberBLACK (the premium Uber product) data. Accessibility is measured by both the expectation and variability of Uber wait time. With spatial autoregressive models, we find that after controlling for other socioeconomic factors, wealth and race do not have significant associations with Uber accessibility. Additionally, higher road network density, population density, and less commuting time to work correlate with greater Uber accessibility. More public transport stops are related to better accessibility of UberX but worse accessibility of UberBLACK. Finally, implications for policy-makers are provided.
Original languageEnglish
Pages (from-to)169-175
Number of pages7
JournalComputers, environment and urban systems
Volume67
Early online date16 Oct 2017
DOIs
Publication statusPublished - 1 Jan 2018
Externally publishedYes

Keywords

  • Accessibility
  • Crowdsourced transportation
  • Disparity
  • Spatial autoregressive model
  • Uber
  • ITC-ISI-JOURNAL-ARTICLE

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