Quantifying the competitiveness of transit relative to taxi with multifaceted data

Zhandong Xu, Jun Xie*, Xiaobo Liu, Yu Nie

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


This paper proposes an assessment framework to quantify the competitiveness of transit relative to a taxi-like service. The framework centers on a transit route builder, which searches, using a hyperpath-based algorithm, for the best available transit route that matches the origin and the destination of a given taxi trip. Based on the optimal transit route, we then measure the relative competitiveness of the transit service according to the preference of a rational traveler, which is determined by the generalized cost defined by fare, in-vehicle travel time and other service attributes. The framework is evaluated using a case study constructed with multifaceted data sources collected in Shenzhen, China. The results show that, while 90% of all taxi trips are faster than its best alternative transit option, only about 36% is shorter. Also, the relative competitiveness of transit decreases with the passenger's value of time, and increases with the average trip distance. We also find that the preference of the middle-income passengers for transit is the most sensitive to the changes in trip distance, mode (bus or rail) and fare.

Original languageEnglish (US)
Pages (from-to)324-343
Number of pages20
JournalTransportmetrica A: Transport Science
Issue number2
StatePublished - 2022


  • Transit
  • competitiveness
  • generalized cost
  • hyperpath
  • value of time

ASJC Scopus subject areas

  • Transportation
  • General Engineering


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