IDEAS home Printed from https://ideas.repec.org/a/taf/tjrtxx/v3y2015i2p81-96.html
   My bibliography  Save this article

Methodologies for assessing costs of rail transit systems based on small sample data

Author

Listed:
  • Xingju Wang
  • Zhanmin Zhang
  • Jinjie Chen
  • Zhe Han

Abstract

China has developed plans to build 87 mass transit rail lines, totalling 2500 km, in 25 cities from 2009 to 2015. The life-cycle costs of the urban rail transit systems have become the focus of both the government and the private sector involved in these large-scale investments. However, the availability of quality data has posed a major challenge to such life-cycle cost analyses; in other words, for any methodology to be effective, it must have the capability of working with very limited amount of available data, or small sample data. In this article, two cost assessment methodologies, fuzzy cluster and support vector machine, are proposed to analyse the life-cycle cost of urban rail transit systems based on small sample data. A case study featuring Line 1 of the Shijiazhuang urban rail transit system was employed to demonstrate the validity of the proposed methodologies. The analysis results indicate that the two assessment methodologies are valid for the life-cycle cost assessment of urban rail transit systems when only small sample data are available.

Suggested Citation

  • Xingju Wang & Zhanmin Zhang & Jinjie Chen & Zhe Han, 2015. "Methodologies for assessing costs of rail transit systems based on small sample data," International Journal of Rail Transportation, Taylor & Francis Journals, vol. 3(2), pages 81-96, June.
    • Handle: RePEc:taf:tjrtxx:v:3:y:2015:i:2:p:81-96
    DOI: 10.1080/23248378.2015.1015222
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23248378.2015.1015222
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/23248378.2015.1015222?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.

    More about this item

    Statistics

    Access and download statistics

    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:taf:tjrtxx:v:3:y:2015:i:2:p:81-96. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tjrt20 .

    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.