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.
|Number of pages||7|
|Journal||Computers, environment and urban systems|
|Early online date||16 Oct 2017|
|Publication status||Published - 1 Jan 2018|
- Crowdsourced transportation
- Spatial autoregressive model