4.7 Article

Equitable? Exploring ridesourcing waiting time and its determinants

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trd.2021.102774

Keywords

Built environment; Shared mobility; Ridesourcing; Transportation inequity; Multilevel modeling; Taxi

Funding

  1. National Natural Science Foundation of China [71704145, 51774241]
  2. Humanity and Social Science Foundation of Ministry of Education of China [18YJCZH138]
  3. Fundamental Research Funds for the Central Universities [2682017CX019]
  4. China Postdoctoral Science Foundation
  5. Sichuan Youth Science and Technology Innovation Research Team Project [2019JDTD0002, 2020JDTD0027]

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The study found that waiting time is positively correlated with trip-level characteristics like traffic conditions and surge multiplier as well as with built environment factors. The multilevel model performed better in capturing the relationship between these variables.
Waiting time (WT) is an important measure that can reflect accessibility to ridesourcing service. Previous studies explored the effects of built environment factors on WT based on estimated WT but did not control for trip-level characteristics, which may lead to biased parameter estimation. Thus, we further study this topic by using the actual WT recorded by the RideAustrin platform and considering trip-level variables. The single-level and multilevel proportional hazards models are constructed, and model comparison shows that the multilevel model performs better. We find that waiting time is positively correlated with trip-level characteristics such as traffic conditions, surge multiplier, and rainy weather. Regarding built environment factors, WT is positively related to distance to CBD and negatively related to road density, transit stop density, and land-use entropy. WT is also higher in areas with a high fraction of Hispanic/Latino and Black residents but lower in areas of low income.

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