IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v95y2024ics0038012124001678.html
   My bibliography  Save this article

Does the clusters of high-speed railway network match the urban agglomerations? A case study in China

Author

Listed:
  • Wang, Zhaojing
  • Ye, Xianxing
  • Ma, Xiaoping

Abstract

High-speed railways play a crucial role in intercity transportation, shaping the spatial interactions within urban agglomerations. However, a mismatch between transportation clusters and the spatial structure of urban agglomerations hampers regional economic integration. To address this issue, this paper proposes a community classification model, employing the Louvain algorithm, to analyze the aggregation of high-speed railway networks (HSRN). It compares central cities in city clusters with HSRN communities in relevant areas, examining the influence of central cities on urban agglomerations. The model is applied to a case study of China's high-speed railway network. The community classifications of HSRN are then compared with planned or future urban agglomerations at the national, provincial, and civic levels. The findings reveal that HSRN in China exhibits distinct clusters that align with the distribution of urban agglomerations. The existing central cities within these agglomerations provide good service levels in the HSRN network. However, HSRN communities within each urban agglomeration are overly scattered and should be integrated to reduce accessibility inequalities. This study offers suggestions for the development planning of HSRN and contributes to the economic integration of urban agglomerations.

Suggested Citation

  • Wang, Zhaojing & Ye, Xianxing & Ma, Xiaoping, 2024. "Does the clusters of high-speed railway network match the urban agglomerations? A case study in China," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    • Handle: RePEc:eee:soceps:v:95:y:2024:i:c:s0038012124001678
    DOI: 10.1016/j.seps.2024.101968
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012124001678
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.seps.2024.101968?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:soceps:v:95:y:2024:i:c:s0038012124001678. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: http://www.elsevier.com/locate/seps .

    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.