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Direct modeling of subway ridership at the station level: a study based on mixed geographically weighted regression

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References

2004Factors influencing light-rail station boardings in the United States443 cited
2012Application of geographically weighted regression to the direct forecasting of transit ridership at station-level377 cited
2010Factors generating boardings at Metro stations in the Seoul metropolitan area248 cited
2011An analysis of Metro ridership at the station-to-station level in Seoul197 cited
2014Exploring the impacts of land use by service coverage and station-level accessibility on rail transit ridership182 cited
2013Analysis of Metro ridership at station level and station-to-station level in Nanjing: an approach based on direct demand models167 cited
2003The Factors Influencing Transit Ridership: A Review and Analysis of the Ridership Literature128 cited
2017Spatial variations in active mode trip volume at intersections: a local analysis utilizing geographically weighted regression81 cited
2013A station-level ridership model for the metro network in Montreal, Quebec74 cited
2013Predicting Transit Ridership at Stop Level: Role of Service and Urban Form56 cited
2016A GIS‐based method to identify cost‐effective routes for rural deviated fixed route transit31 cited

Cited by

2023Spatio-Temporal Investigation of Public Transport Demand Using Smart Card Data16 cited
2021How Do Different Treatments of Catchment Area Affect the Station Level Demand Modeling of Urban Rail Transit?

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16 cited

2022Influence of Built Environment on Subway Trip Origin and Destination: Insights Based on Mobile Positioning Data13 cited

2022Spatially Varying Relation between Built Environment and Station-Level Subway Passenger-Distance11 cited

2025Exploring the multiscale relationship between the built environment and metro station ridership8 cited

2024The temporal distribution of ridership in metro stations from land-use perspective6 cited

2021Effects of Coverage Area Treatment, Spatial Analysis Unit, and Regression Model on the Results of Station-Level Demand Modeling of Urban Rail Transit6 cited