Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Analysis of Metro ridership at station level and station-to-station level in Nanjing: an approach based on direct demand models
Abstract A growing base of research adopts direct demand models to reveal associations between transit ridership and influence factors in recent years. This study is designed to investigate the factors affecting rail transit ridership at both station level and station-to-station level by adopting multiple regression model and multiplicative model respectively, specifically using an implemented Metro system in Nanjing, China, where Metro implementation is on the rise. Independent variables include factors measuring land-use mix, intermodal connection, station context, and travel impedance. Multiple regression model proves 11 variables are significantly associated with Metro ridership at station level: population, employment, business/office floor area, CBD dummy variable, number of major educational sites, entertainment venues and shopping centers, road length, feeder bus lines, bicycle park-and-ride (P&R) spaces, and transfer dummy variable. Results from multiplicative model indicate that factors influencing Metro station ridership may also influence Metro station-to-station ridership, varied by both trip ends (origin/destination) and time of day. In comparison with previous case studies, CBD dummy variable and bicycle P&R are statistically significant to explain Metro ridership in Nanjing. In addition, Metro travel impedance variables have significant influence on station-to-station ridership, representing the basic time-decay relationship in travel distribution. Potential implications of the model results include estimating Metro ridership at station level and station-to-station level by considering the significant variables, recognizing the necessity to establish a cooperative multi-modal transit system, and identifying opportunities for transit-oriented development.
Analysis of Metro ridership at station level and station-to-station level in Nanjing: an approach based on direct demand models
Abstract A growing base of research adopts direct demand models to reveal associations between transit ridership and influence factors in recent years. This study is designed to investigate the factors affecting rail transit ridership at both station level and station-to-station level by adopting multiple regression model and multiplicative model respectively, specifically using an implemented Metro system in Nanjing, China, where Metro implementation is on the rise. Independent variables include factors measuring land-use mix, intermodal connection, station context, and travel impedance. Multiple regression model proves 11 variables are significantly associated with Metro ridership at station level: population, employment, business/office floor area, CBD dummy variable, number of major educational sites, entertainment venues and shopping centers, road length, feeder bus lines, bicycle park-and-ride (P&R) spaces, and transfer dummy variable. Results from multiplicative model indicate that factors influencing Metro station ridership may also influence Metro station-to-station ridership, varied by both trip ends (origin/destination) and time of day. In comparison with previous case studies, CBD dummy variable and bicycle P&R are statistically significant to explain Metro ridership in Nanjing. In addition, Metro travel impedance variables have significant influence on station-to-station ridership, representing the basic time-decay relationship in travel distribution. Potential implications of the model results include estimating Metro ridership at station level and station-to-station level by considering the significant variables, recognizing the necessity to establish a cooperative multi-modal transit system, and identifying opportunities for transit-oriented development.
Analysis of Metro ridership at station level and station-to-station level in Nanjing: an approach based on direct demand models
Zhao, Jinbao (Autor:in) / Deng, Wei (Autor:in) / Song, Yan (Autor:in) / Zhu, Yueran (Autor:in)
Transportation ; 41
2013
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
BKL:
55.80$jVerkehrswesen$jTransportwesen: Allgemeines
/
55.80
Verkehrswesen, Transportwesen: Allgemeines
/
74.75$jVerkehrsplanung$jVerkehrspolitik
/
74.75
Verkehrsplanung, Verkehrspolitik
What influences Metro station ridership in China? Insights from Nanjing
| Online Contents | 2013
What influences Metro station ridership in China? Insights from Nanjing
| Elsevier | 2013
An analysis of Metro ridership at the station-to-station level in Seoul
| Online Contents | 2011
An analysis of Metro ridership at the station-to-station level in Seoul
| Online Contents | 2011