IDEAS home Printed from https://ideas.repec.org/h/spr/isochp/978-1-4899-7705-2_14.html
   My bibliography  Save this book chapter

A Radial Framework for Estimating the Efficiency and Returns to Scale of a Multi-component Production System in DEA

In: Handbook of Operations Analytics Using Data Envelopment Analysis

Author

Listed:
  • Jingjing Ding

    (Hefei University of Technology)

  • Chenpeng Feng

    (Hefei University of Technology)

  • Huaqing Wu

    (Hefei University of Technology)

Abstract

This chapter provides radial measurements of efficiency for the production process possessing multi-components under different production technologies. Our approach is based on the construction of various empirical production possibility sets. Then we propose a procedure that is unaffected affected by multiple optima for estimating returns to scale. The theoretical connections between the traditional black box and the proposed multi-component approach are established, which ascertains consistency in estimating the efficiency and returns to scale. Moreover, we introduce two homogeneity conditions, which clarify the difference between our approach and the existing one, and are important for evaluating performance in multi-component setting. Finally, an empirical study of the pollution treatment processes in China is presented, and compared to the results from black-box approach. Many insightful findings related to the operations of the pollution treatment processes in China are secured.

Suggested Citation

  • Jingjing Ding & Chenpeng Feng & Huaqing Wu, 2016. "A Radial Framework for Estimating the Efficiency and Returns to Scale of a Multi-component Production System in DEA," International Series in Operations Research & Management Science, in: Shiuh-Nan Hwang & Hsuan-Shih Lee & Joe Zhu (ed.), Handbook of Operations Analytics Using Data Envelopment Analysis, chapter 0, pages 351-384, Springer.
    • Handle: RePEc:spr:isochp:978-1-4899-7705-2_14
    DOI: 10.1007/978-1-4899-7705-2_14
    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.

    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:isochp:978-1-4899-7705-2_14. 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.