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

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  1. Yuxin He & Yang Zhao & Kwok Leung Tsui, 2021. "An adapted geographically weighted LASSO (Ada-GWL) model for predicting subway ridership," Transportation, Springer, vol. 48(3), pages 1185-1216, June.
  2. Li, Shaoying & Lyu, Dijiang & Huang, Guanping & Zhang, Xiaohu & Gao, Feng & Chen, Yuting & Liu, Xiaoping, 2020. "Spatially varying impacts of built environment factors on rail transit ridership at station level: A case study in Guangzhou, China," Journal of Transport Geography, Elsevier, vol. 82(C).
  3. Karnberger, Stephan & Antoniou, Constantinos, 2020. "Network–wide prediction of public transportation ridership using spatio–temporal link–level information," Journal of Transport Geography, Elsevier, vol. 82(C).
  4. Su, Shiliang & Zhao, Chong & Zhou, Hao & Li, Bozhao & Kang, Mengjun, 2022. "Unraveling the relative contribution of TOD structural factors to metro ridership: A novel localized modeling approach with implications on spatial planning," Journal of Transport Geography, Elsevier, vol. 100(C).
  5. Bo Wan & Xudan Zhao & Yuhan Sun & Tao Yang, 2023. "Unraveling the Impact of Spatial Configuration on TOD Function Mix Use and Spatial Intensity: An Analysis of 47 Morning Top-Flow Stations in Beijing (2018–2020)," Sustainability, MDPI, vol. 15(10), pages 1-27, May.
  6. Wu, Pan & Xu, Lunhui & Zhong, Lingshu & Gao, Kun & Qu, Xiaobo & Pei, Mingyang, 2022. "Revealing the determinants of the intermodal transfer ratio between metro and bus systems considering spatial variations," Journal of Transport Geography, Elsevier, vol. 104(C).
  7. Zhang, Xiaojian & Zhao, Xilei, 2022. "Machine learning approach for spatial modeling of ridesourcing demand," Journal of Transport Geography, Elsevier, vol. 100(C).
  8. Daeyoung Kwon & Sung Eun Sally Oh & Sangwon Choi & Brian H. S. Kim, 2023. "Viability of compact cities in the post-COVID-19 era: subway ridership variations in Seoul Korea," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 71(1), pages 175-203, August.
  9. Andersson, David Emanuel & Shyr, Oliver F. & Yang, Jimmy, 2021. "Neighbourhood effects on station-level transit use: Evidence from the Taipei metro," Journal of Transport Geography, Elsevier, vol. 94(C).
  10. Kexin Lei & Quanhua Hou & Weijia Li & Meng Zhao & Jizhe Zhou & Lingda Zhang & Shihan Chen & Yaqiong Duan, 2022. "The Impact of Land Use on Time-Varying Passenger Flow Based on Site Classification," Land, MDPI, vol. 11(12), pages 1-19, December.
  11. Su, Shiliang & Zhang, Hui & Wang, Miao & Weng, Min & Kang, Mengjun, 2021. "Transit-oriented development (TOD) typologies around metro station areas in urban China: A comparative analysis of five typical megacities for planning implications," Journal of Transport Geography, Elsevier, vol. 90(C).
  12. Aston, Laura & Currie, Graham & Kamruzzaman, Md. & Delbosc, Alexa & Teller, David, 2020. "Study design impacts on built environment and transit use research," Journal of Transport Geography, Elsevier, vol. 82(C).
  13. Christian Martin Mützel & Joachim Scheiner, 2022. "Investigating spatio-temporal mobility patterns and changes in metro usage under the impact of COVID-19 using Taipei Metro smart card data," Public Transport, Springer, vol. 14(2), pages 343-366, June.
  14. Sung, Hyungun & Choi, Keechoo & Lee, Sugie & Cheon, SangHyun, 2014. "Exploring the impacts of land use by service coverage and station-level accessibility on rail transit ridership," Journal of Transport Geography, Elsevier, vol. 36(C), pages 134-140.
  15. Yan, Xiang & Liu, Xinyu & Zhao, Xilei, 2020. "Using machine learning for direct demand modeling of ridesourcing services in Chicago," Journal of Transport Geography, Elsevier, vol. 83(C).
  16. Vergel-Tovar, C. Erik & Rodriguez, Daniel A., 2018. "The ridership performance of the built environment for BRT systems: Evidence from Latin America," Journal of Transport Geography, Elsevier, vol. 73(C), pages 172-184.
  17. Jaewoo Lee & Keemin Sohn, 2014. "Identifying the Impact on Land Prices of Replacing At-grade or Elevated Railways with Underground Subways in the Seoul Metropolitan Area," Urban Studies, Urban Studies Journal Limited, vol. 51(1), pages 44-62, January.
  18. Lijie Yu & Yarong Cong & Kuanmin Chen, 2020. "Determination of the Peak Hour Ridership of Metro Stations in Xi’an, China Using Geographically-Weighted Regression," Sustainability, MDPI, vol. 12(6), pages 1-22, March.
  19. Jie Huang & David Levinson & Jiaoe Wang & Haitao Jin, 2019. "Job-worker spatial dynamics in Beijing: Insights from Smart Card Data," Working Papers 2019-01, University of Minnesota: Nexus Research Group.
  20. Ingvardson, Jesper Bláfoss & Nielsen, Otto Anker, 2018. "How urban density, network topology and socio-economy influence public transport ridership: Empirical evidence from 48 European metropolitan areas," Journal of Transport Geography, Elsevier, vol. 72(C), pages 50-63.
  21. Ding, Chuan & Cao, Xinyu & Liu, Chao, 2019. "How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds," Journal of Transport Geography, Elsevier, vol. 77(C), pages 70-78.
  22. Kepaptsoglou, Konstantinos & Stathopoulos, Antony & Karlaftis, Matthew G., 2017. "Ridership estimation of a new LRT system: Direct demand model approach," Journal of Transport Geography, Elsevier, vol. 58(C), pages 146-156.
  23. Jun, Myung-Jin & Choi, Keechoo & Jeong, Ji-Eun & Kwon, Ki-Hyun & Kim, Hee-Jae, 2015. "Land use characteristics of subway catchment areas and their influence on subway ridership in Seoul," Journal of Transport Geography, Elsevier, vol. 48(C), pages 30-40.
  24. Zhenjun Zhu & Jun Zeng & Xiaolin Gong & Yudong He & Shucheng Qiu, 2021. "Analyzing Influencing Factors of Transfer Passenger Flow of Urban Rail Transit: A New Approach Based on Nested Logit Model Considering Transfer Choices," IJERPH, MDPI, vol. 18(16), pages 1-14, August.
  25. Lee, Hye Kyung & Jiao, Junfeng & Choi, Seung Jun, 2021. "Identifying spatiotemporal transit deserts in Seoul, South Korea," Journal of Transport Geography, Elsevier, vol. 95(C).
  26. Kim, Suji & Lee, Sujin & Ko, Eunjeong & Jang, Kitae & Yeo, Jiho, 2021. "Changes in car and bus usage amid the COVID-19 pandemic: Relationship with land use and land price," Journal of Transport Geography, Elsevier, vol. 96(C).
  27. Lei Pang & Yuxiao Jiang & Jingjing Wang & Ning Qiu & Xiang Xu & Lijian Ren & Xinyu Han, 2023. "Research of Metro Stations with Varying Patterns of Ridership and Their Relationship with Built Environment, on the Example of Tianjin, China," Sustainability, MDPI, vol. 15(12), pages 1-18, June.
  28. Jinbao Zhao & Wei Deng & Yan Song & Yueran Zhu, 2014. "Analysis of Metro ridership at station level and station-to-station level in Nanjing: an approach based on direct demand models," Transportation, Springer, vol. 41(1), pages 133-155, January.
  29. Yadi Zhu & Feng Chen & Zijia Wang & Jin Deng, 2019. "Spatio-temporal analysis of rail station ridership determinants in the built environment," Transportation, Springer, vol. 46(6), pages 2269-2289, December.
  30. Iseki, Hiroyuki & Liu, Chao & Knaap, Gerrit, 2018. "The determinants of travel demand between rail stations: A direct transit demand model using multilevel analysis for the Washington D.C. Metrorail system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 635-649.
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