IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-642-34651-4_15.html
   My bibliography  Save this book chapter

Allocating the Subsidy Among Urban Public Transport Enterprises for Good Performance and Low Carbon Transportation: An Application of DEA

In: Ltlgb 2012

Author

Listed:
  • Qianzhi Dai

    (School of Management University of Science and Technology of China)

  • Yongjun Li

    (School of Management University of Science and Technology of China)

  • Qiwei Xie

    (Institute of Automation Chinese Academy of Sciences)

  • Liang Liang

    (School of Management University of Science and Technology of China)

Abstract

This paper proposes a stimulating mechanism for allocating subsidies to urban public transport enterprises. The allocation method is based on data envelopment analysis and the satisfaction degrees of urban public transport enterprises. It first finds the set of subsidy allocation that can keep the Pareto efficient for both the whole urban public transit industry and each urban public transport enterprise to reflect the efficiency principle, and then yields a unique subsidy allocation scheme from the set of subsidy allocations with considering the equity of satisfaction degrees. The allocation mechanism can reflect the market competition regulation on some level and benefit to achieve the goal of Green Transport in urban public transit industry. An example of allocating the subsidy among urban public transport enterprises is illustrated.

Suggested Citation

  • Qianzhi Dai & Yongjun Li & Qiwei Xie & Liang Liang, 2013. "Allocating the Subsidy Among Urban Public Transport Enterprises for Good Performance and Low Carbon Transportation: An Application of DEA," Springer Books, in: Feng Chen & Yisheng Liu & Guowei Hua (ed.), Ltlgb 2012, edition 127, chapter 0, pages 59-65, Springer.
  • Handle: RePEc:spr:sprchp:978-3-642-34651-4_15
    DOI: 10.1007/978-3-642-34651-4_15
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Yu, Ming-Miin & Chen, Li-Hsueh & Hsiao, Bo, 2018. "A performance-based subsidy allocation of ferry transportation: A data envelopment approach," Transport Policy, Elsevier, vol. 68(C), pages 13-19.

    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:spr:sprchp:978-3-642-34651-4_15. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.