Abstract Customized buses (CBs) are a complementary but essential component of the public transit system and have gained increasing popularity. However, knowledge remains limited regarding how CB service performs and what factors significantly influence the performance, particularly at a stop-to-stop level. By utilizing over two years of CB subscription data from Shanghai, we applied both the multiplicative model and the XGBoost model to identify key determinants of CB ridership and to examine nonlinear associations at a stop-to-stop level. The results suggest that: (1) travel impedance and the built environment, especially distance to the nearest metro station and distance to the city center, are significant predictors of CB ridership; (2) the effects of the built environment are nonlinear and vary by side of stop and time of day. The findings assist CB providers and policymakers in identifying appropriate market niches and areas with the greatest potential for allocating stops and designing routes.
Travel impedance, the built environment, and customized-bus ridership: A stop-to-stop level analysis
2023-08-18
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Factors Influencing Stop-Level Transit Ridership in Arnhem–Nijmegen City Region, Netherlands
Transportation Research Record | 2019
|Local modeling as a solution to the lack of stop-level ridership data
Elsevier | 2023
|