An analysis of Metro ridership at the station‐to‐station level in Seoul

While most aggregate studies of transit ridership are conducted at either the stop or the route level, the present study focused on factors affecting Metro ridership in the Seoul metropolitan area at the station‐to‐station level. The station‐to‐station analysis made it possible to distinguish the effect of origin factors on Metro ridership from that of destination factors and to cut down the errors caused by the aggregation of travel impedance‐related variables. After adopting two types of direct‐demand patronage forecasting models, the multiplicative model and the Poisson regression model, the former was found to be superior to the latter because it clearly identified the negative influences of competing modes on Metro ridership. Such results are rarely found with aggregate level analyses. Moreover, the importance of built environment in explaining Metro demand was confirmed by separating built environment variables for origin and destination stations and by differentiating ridership by the time of day. For morning peak hours, the population‐related variables of the origin stations played a key role in accounting for Metro ridership, while employment‐related variables prevailed in destination stations. In evening peak hours, both employment‐ and population‐related variables were significant in accounting for the Metro ridership at the destination station. This showed that a significant number of people in the Seoul metropolitan area appear to take various non‐home‐based trips after work, which is consistent with the results from direct household travel surveys.