IDEAS home Printed from https://ideas.repec.org/a/eee/jotrge/v100y2022ics096669232200031x.html
   My bibliography  Save this article

Unraveling the relative contribution of TOD structural factors to metro ridership: A novel localized modeling approach with implications on spatial planning

Author

Listed:
  • Su, Shiliang
  • Zhao, Chong
  • Zhou, Hao
  • Li, Bozhao
  • Kang, Mengjun

Abstract

TOD (transit-oriented development) has gradually earned the reputation as a promising spatial planning strategy to encourage public transit usage. Many cities across the world, especially those in the global south, have established TOD projects around metro stations. From this standpoint, the paramount question of how TOD is conductive to metro ridership is at the heart of scholarly discourse. Theoretically, the territorial organization of a TOD comprises three structural factors –node (metro station), place (surrounding land use) and their feedback. An accurate judgement of the TOD-metro ridership relationship would not be achieved if we neglected any of the three structural factors forming the TOD architecture. However, the three TOD structural factors have not frequently been considered simultaneously in prior literature. A gap remains regarding the relative contribution of TOD structural factors to metro ridership across time and space. This paper aims to address this unresolved issue using a case study of the Hangzhou metropolitan area in China. As the dependent variable, metro ridership is measured using one week of smart card records, with the three TOD structural factors as explanatory variables and sociodemographic factors as control variables, described by a set of indicators. A novel localized modeling approach using variance decomposition of geographically temporally weighted regression is demonstrated to quantify the spatially and temporally varying relative contribution of TOD structural factors. The results show that both similarities and discrepancies were identified compared to earlier studies. Most importantly, new knowledge was gained, particularly that ‘metro station’ factors contribute the most to metro ridership, followed by the feedback factor, ‘surrounding land use’ factors and sociodemographic factors both on workdays and nonworkdays. Furthermore, our analysis highlights that the relative contribution of TOD structural factors presents noticeable spatial heterogeneities across metro station areas both on workdays and nonworkdays but exhibits only obvious temporal heterogeneity on nonworkdays. Finally, TOD clusters are generated based on the relative contribution of TOD structural factors with implications for spatial planning. This study is believed to open the door for framing locally representative strategies of TOD to stimulate the use of public transit.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:jotrge:v:100:y:2022:i:c:s096669232200031x
    DOI: 10.1016/j.jtrangeo.2022.103308
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096669232200031X
    Download Restriction: no

    File URL: https://libkey.io/10.1016/j.jtrangeo.2022.103308?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Caset, Freke & Blainey, Simon & Derudder, Ben & Boussauw, Kobe & Witlox, Frank, 2020. "Integrating node-place and trip end models to explore drivers of rail ridership in Flanders, Belgium," Journal of Transport Geography, Elsevier, vol. 87(C).
    2. Reid Ewing & Robert Cervero, 2010. "Travel and the Built Environment," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 265-294.
    3. Gutiérrez, Javier & Cardozo, Osvaldo Daniel & García-Palomares, Juan Carlos, 2011. "Transit ridership forecasting at station level: an approach based on distance-decay weighted regression," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1081-1092.
    4. Chakour, Vincent & Eluru, Naveen, 2016. "Examining the influence of stop level infrastructure and built environment on bus ridership in Montreal," Journal of Transport Geography, Elsevier, vol. 51(C), pages 205-217.
    5. Zhang, Yuerong & Marshall, Stephen & Manley, Ed, 2019. "Network criticality and the node-place-design model: Classifying metro station areas in Greater London," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    6. Dong, Hongwei, 2021. "Evaluating the impacts of transit-oriented developments (TODs) on household transportation expenditures in California," Journal of Transport Geography, Elsevier, vol. 90(C).
    7. Daniel (Jian) Sun & Yuhan Zhao & Qing-Chang Lu, 2015. "Vulnerability Analysis of Urban Rail Transit Networks: A Case Study of Shanghai, China," Sustainability, MDPI, vol. 7(6), pages 1-18, May.
    8. Ettema, Dick & Nieuwenhuis, Roy, 2017. "Residential self-selection and travel behaviour: What are the effects of attitudes, reasons for location choice and the built environment?," Journal of Transport Geography, Elsevier, vol. 59(C), pages 146-155.
    9. Jeffrey, Dana & Boulangé, Claire & Giles-Corti, Billie & Washington, Simon & Gunn, Lucy, 2019. "Using walkability measures to identify train stations with the potential to become transit oriented developments located in walkable neighbourhoods," Journal of Transport Geography, Elsevier, vol. 76(C), pages 221-231.
    10. 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.
    11. Miguel Padeiro & Ana Louro & Nuno Marques da Costa, 2019. "Transit-oriented development and gentrification: a systematic review," Transport Reviews, Taylor & Francis Journals, vol. 39(6), pages 733-754, November.
    12. Liu, Xintao & Wu, Jiawei & Huang, Jianwei & Zhang, Junwei & Chen, Bi Yu & Chen, Anthony, 2021. "Spatial-interaction network analysis of built environmental influence on daily public transport demand," Journal of Transport Geography, Elsevier, vol. 92(C).
    13. Lyu, Guowei & Bertolini, Luca & Pfeffer, Karin, 2016. "Developing a TOD typology for Beijing metro station areas," Journal of Transport Geography, Elsevier, vol. 55(C), pages 40-50.
    14. 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).
    15. Nilsson, Isabelle & Delmelle, Elizabeth, 2018. "Transit investments and neighborhood change: On the likelihood of change," Journal of Transport Geography, Elsevier, vol. 66(C), pages 167-179.
    16. 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).
    17. Jinkyung Choi & Yong Lee & Taewan Kim & Keemin Sohn, 2012. "An analysis of Metro ridership at the station-to-station level in Seoul," Transportation, Springer, vol. 39(3), pages 705-722, May.
    18. 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).
    19. Nasri, Arefeh & Zhang, Lei, 2014. "The analysis of transit-oriented development (TOD) in Washington, D.C. and Baltimore metropolitan areas," Transport Policy, Elsevier, vol. 32(C), pages 172-179.
    20. Liu, Yunzhe & Singleton, Alex & Arribas-Bel, Daniel, 2020. "Considering context and dynamics: A classification of transit-orientated development for New York City," Journal of Transport Geography, Elsevier, vol. 85(C).
    21. Mi-Kyeong Kim & Sangpil Kim & Hong-Gyoo Sohn, 2018. "Relationship between Spatio-Temporal Travel Patterns Derived from Smart-Card Data and Local Environmental Characteristics of Seoul, Korea," Sustainability, MDPI, vol. 10(3), pages 1-18, March.
    22. Jinhyun Hong & Qing Shen & Lei Zhang, 2014. "How do built-environment factors affect travel behavior? A spatial analysis at different geographic scales," Transportation, Springer, vol. 41(3), pages 419-440, May.
    23. Yanjie Ji & Xinwei Ma & Mingyuan Yang & Yuchuan Jin & Liangpeng Gao, 2018. "Exploring Spatially Varying Influences on Metro-Bikeshare Transfer: A Geographically Weighted Poisson Regression Approach," Sustainability, MDPI, vol. 10(5), pages 1-23, May.
    24. 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.
    25. Li, Zekun & Han, Zixuan & Xin, Jing & Luo, Xin & Su, Shiliang & Weng, Min, 2019. "Transit oriented development among metro station areas in Shanghai, China: Variations, typology, optimization and implications for land use planning," Land Use Policy, Elsevier, vol. 82(C), pages 269-282.
    26. Delmelle, Elizabeth C., 2021. "Transit-Induced Gentrification and Displacement: The State of the Debate," SocArXiv 5ka2g, Center for Open Science.
    27. Shao, Qifan & Zhang, Wenjia & Cao, Xinyu & Yang, Jiawen & Yin, Jie, 2020. "Threshold and moderating effects of land use on metro ridership in Shenzhen: Implications for TOD planning," Journal of Transport Geography, Elsevier, vol. 89(C).
    28. Yang Liu & Yanjie Ji & Zhuangbin Shi & Liangpeng Gao, 2018. "The Influence of the Built Environment on School Children’s Metro Ridership: An Exploration Using Geographically Weighted Poisson Regression Models," Sustainability, MDPI, vol. 10(12), pages 1-16, December.
    29. Vale, David S., 2015. "Transit-oriented development, integration of land use and transport, and pedestrian accessibility: Combining node-place model with pedestrian shed ratio to evaluate and classify station areas in Lisbo," Journal of Transport Geography, Elsevier, vol. 45(C), pages 70-80.
    30. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Du, Qiang & Zhou, Yuqing & Huang, Youdan & Wang, Yalei & Bai, Libiao, 2022. "Spatiotemporal exploration of the non-linear impacts of accessibility on metro ridership," Journal of Transport Geography, Elsevier, vol. 102(C).
    2. Su, Shiliang & Wang, Zhuolun & Li, Bozhao & Kang, Mengjun, 2022. "Deciphering the influence of TOD on metro ridership: An integrated approach of extended node-place model and interpretable machine learning with planning implications," Journal of Transport Geography, Elsevier, vol. 104(C).
    3. Zhang, Zhaolin & Zhai, Guocong & Xie, Kun & Xiao, Feng, 2022. "Exploring the nonlinear effects of ridesharing on public transit usage: A case study of San Diego," Journal of Transport Geography, Elsevier, vol. 104(C).
    4. Lan Wu & Xiaorui Yuan & Chaoyin Yin & Ming Yang & Hongjian Ouyang, 2023. "Car Ownership Behavior Model Considering Nonlinear Impacts of Multi-Scale Built Environment Characteristics," Sustainability, MDPI, vol. 15(12), pages 1-14, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Su, Shiliang & Wang, Zhuolun & Li, Bozhao & Kang, Mengjun, 2022. "Deciphering the influence of TOD on metro ridership: An integrated approach of extended node-place model and interpretable machine learning with planning implications," Journal of Transport Geography, Elsevier, vol. 104(C).
    2. Gao, Fan & Yang, Linchuan & Han, Chunyang & Tang, Jinjun & Li, Zhitao, 2022. "A network-distance-based geographically weighted regression model to examine spatiotemporal effects of station-level built environments on metro ridership," Journal of Transport Geography, Elsevier, vol. 105(C).
    3. Rao, Fujie & Pafka, Elek, 2021. "Shopping morphologies of urban transit station areas: A comparative study of central city station catchments in Toronto, San Francisco, and Melbourne," Journal of Transport Geography, Elsevier, vol. 96(C).
    4. Liao, Cong & Scheuer, Bronte, 2022. "Evaluating the performance of transit-oriented development in Beijing metro station areas: Integrating morphology and demand into the node-place model," Journal of Transport Geography, Elsevier, vol. 100(C).
    5. Ying Liang & Wei Song & Xiaofeng Dong, 2021. "Evaluating the Space Use of Large Railway Hub Station Areas in Beijing toward Integrated Station-City Development," Land, MDPI, vol. 10(11), pages 1-22, November.
    6. 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.
    7. 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.
    8. Du, Qiang & Zhou, Yuqing & Huang, Youdan & Wang, Yalei & Bai, Libiao, 2022. "Spatiotemporal exploration of the non-linear impacts of accessibility on metro ridership," Journal of Transport Geography, Elsevier, vol. 102(C).
    9. 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).
    10. Shao, Qifan & Zhang, Wenjia & Cao, Xinyu & Yang, Jiawen & Yin, Jie, 2020. "Threshold and moderating effects of land use on metro ridership in Shenzhen: Implications for TOD planning," Journal of Transport Geography, Elsevier, vol. 89(C).
    11. Liu, Yunzhe & Singleton, Alex & Arribas-Bel, Daniel, 2020. "Considering context and dynamics: A classification of transit-orientated development for New York City," Journal of Transport Geography, Elsevier, vol. 85(C).
    12. Wei Wu & Prasanna Divigalpitiya, 2022. "Assessment of Accessibility and Activity Intensity to Identify Future Development Priority TODs in Hefei City," Land, MDPI, vol. 11(9), pages 1-17, September.
    13. Zhou, Mingzhi & Zhou, Jiali & Zhou, Jiangping & Lei, Shuyu & Zhao, Zhan, 2023. "Introducing social contacts into the node-place model: A case study of Hong Kong," Journal of Transport Geography, Elsevier, vol. 107(C).
    14. Cummings, Christopher & Mahmassani, Hani, 2022. "Does intercity rail station placement matter? Expansion of the node-place model to identify station location impacts on Amtrak ridership," Journal of Transport Geography, Elsevier, vol. 99(C).
    15. Shin, Yonggeun & Kim, Dong-Kyu & Kim, Eui-Jin, 2022. "Activity-based TOD typology for seoul transit station areas using smart-card data," Journal of Transport Geography, Elsevier, vol. 105(C).
    16. Caset, Freke & Blainey, Simon & Derudder, Ben & Boussauw, Kobe & Witlox, Frank, 2020. "Integrating node-place and trip end models to explore drivers of rail ridership in Flanders, Belgium," Journal of Transport Geography, Elsevier, vol. 87(C).
    17. 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.
    18. Phani Kumar, P. & Ravi Sekhar, Ch. & Parida, Manoranjan, 2018. "Residential dissonance in TOD neighborhoods," Journal of Transport Geography, Elsevier, vol. 72(C), pages 166-177.
    19. Wang, Jing & Wan, Feng & Dong, Chunjiao & Yin, Chaoying & Chen, Xiaoyu, 2023. "Spatiotemporal effects of built environment factors on varying rail transit station ridership patterns," Journal of Transport Geography, Elsevier, vol. 109(C).
    20. 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).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jotrge:v:100:y:2022:i:c:s096669232200031x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-transport-geography .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.