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A platform for research: civil engineering, architecture and urbanism
Spatial dependence and spillover effects in customized bus demand: Empirical evidence using spatial dynamic panel models
Abstract This paper proposes customized bus (CB) demand models to investigate dynamic adjustments, spatial dependence, and spatial spillover effects using spatial dynamic panel data techniques and a balanced panel data set collected over two years. The endogeneity introduced by spatial dependence effects is resolved by extending the moment restrictions of the system GMM estimator to a spatial autoregressive dynamic panel. A wide range of variables representing factors related to 1) characteristics of service supply, 2) demographic characteristics, and 3) land use and accessibility were mined and fused to investigate their direct and spillover effects on CB demand. The results reveal the mechanism of spatial dependence such that the increments (or decrement) in demand rather than the amount of demand itself in the neighbourhood contribute to the spatial dependence effects. There is more than 43% matched demand generated in a given area for each-unit increment of demand from its neighbourhood. CB services are more attractive for passengers with long-distance trips, and therefore, increasing the focus on long-distance trips is one potential strategy for increasing ridership. Determined by the role of CB in the transportation system, areas with poor accessibility are found to have larger market niches for CB services.
Highlights CB demand shows a stronger time dependence than spatial dependence. A spatial dynamic panel data model was developed to model CB demand. The CB services have a large market potential in areas with poor accessibility. There is more than 43% matched demand generated in a given area for each-unit increment of demand from its neighbourhood.
Spatial dependence and spillover effects in customized bus demand: Empirical evidence using spatial dynamic panel models
Abstract This paper proposes customized bus (CB) demand models to investigate dynamic adjustments, spatial dependence, and spatial spillover effects using spatial dynamic panel data techniques and a balanced panel data set collected over two years. The endogeneity introduced by spatial dependence effects is resolved by extending the moment restrictions of the system GMM estimator to a spatial autoregressive dynamic panel. A wide range of variables representing factors related to 1) characteristics of service supply, 2) demographic characteristics, and 3) land use and accessibility were mined and fused to investigate their direct and spillover effects on CB demand. The results reveal the mechanism of spatial dependence such that the increments (or decrement) in demand rather than the amount of demand itself in the neighbourhood contribute to the spatial dependence effects. There is more than 43% matched demand generated in a given area for each-unit increment of demand from its neighbourhood. CB services are more attractive for passengers with long-distance trips, and therefore, increasing the focus on long-distance trips is one potential strategy for increasing ridership. Determined by the role of CB in the transportation system, areas with poor accessibility are found to have larger market niches for CB services.
Highlights CB demand shows a stronger time dependence than spatial dependence. A spatial dynamic panel data model was developed to model CB demand. The CB services have a large market potential in areas with poor accessibility. There is more than 43% matched demand generated in a given area for each-unit increment of demand from its neighbourhood.
Spatial dependence and spillover effects in customized bus demand: Empirical evidence using spatial dynamic panel models
Wang, Jiangbo (author) / Yamamoto, Toshiyuki (author) / Liu, Kai (author)
Transport Policy ; 105 ; 166-180
2021-03-10
15 pages
Article (Journal)
Electronic Resource
English
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