Subway Station Accessibility and Its Impacts on the Spatial and Temporal Variations of Its Outbound Ridership
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 12
Abstract
Understanding the influencing factors of subway station outbound ridership provides sights into current subway system operations and future expansion needs. The accessibility of a subway station quantifies the potential opportunities that can be accessed by its outbound riders and can be a key factor that influences its existing ridership. This study captures the impacts of 10 types of subway station accessibility on the spatial and temporal variation of the outbound ridership. The geographically and temporally weighted regression (GTWR) modeling framework was used to quantify the spatiotemporal correlation and the spatiotemporal nonstationarity among subway station outbound ridership using 1-month smart card data of one of the largest subway networks in the world (Shanghai, China) containing over 60 million exits. In addition, four separate GTWR models were estimated to capture the potential differences between regular and irregular subway riders and between weekdays and weekends. The results suggest that the GTWR model outperforms the ordinary least-square models and GWR models in both goodness of model fit and explanatory accuracy. The model estimation results highlight the spatial and temporal varying impacts of four types of subway station accessibility on the outbound ridership, including accessibility to commercial locations, bus stations, healthcare facilities, and recreation locations. The results provide valuable insights for predicting subway outbound ridership as a function of spatially and temporally explicit variables which may have implications on addressing operational, tactical, and strategic challenges related to subway systems.
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Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The study was supported by the China Communication Construction Company Ltd. R&D program with the Grant No. 2019-ZJKJ-ZDZX02 and the Science and Technology Project of Zhejiang Province (2021C01011). This study was also supported by the Fundamental Research Funds for the Central Universities (22120220124). This study was funded by the National Natural Science Foundation of China (Grant No. 52272322).
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Journal of Transportation Engineering, Part A: Systems
Volume 148 • Issue 12 • December 2022
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© 2022 American Society of Civil Engineers.
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Received: Apr 16, 2022
Accepted: Jul 20, 2022
Published online: Sep 22, 2022
Published in print: Dec 1, 2022
Discussion open until: Feb 22, 2023
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