IDEAS home Printed from https://ideas.repec.org/h/spr/isochp/978-3-030-43384-0_7.html
   My bibliography  Save this book chapter

Fair Target Setting for Intermediate Products in Two-Stage Systems with Data Envelopment Analysis

In: Data Science and Productivity Analytics

Author

Listed:
  • Qingxian An

    (Central South University)

  • Haoxun Chen

    (University of Technology of Troyes)

  • Beibei Xiong

    (Hunan University)

  • Jie Wu

    (University of Science and Technology of China)

  • Liang Liang

    (University of Science and Technology of China)

Abstract

In a two-stage system with two divisions connected in series, fairly setting the target outputs for the first stage or equivalently the target inputs for the second stage is critical, in order to ensure that the two stages have incentives to collaborate with each other to achieve the best performance of the whole system. Data envelopment analysis (DEA) as a non-parametric approach for efficiency evaluation of multi-input, multi-output systems has drawn a lot of attention. Recently, many two-stage DEA models were developed for studying the internal structures of two-stage systems. However, there was no work studying the fair setting of the target intermediate products (or intermediate measures) although unreasonable setting will result in unfairness to the two stages because setting higher (fewer) intermediate measures means that the first (second) stage must make more efforts to achieve the overall production plan. In this chapter, a new DEA model taking account of fairness in the setting of the intermediate products is proposed, where the fairness is interpreted based on the Nash bargaining game model, in which the two stages negotiate their target efficiencies in the two-stage system based on their individual efficiencies. This approach is illustrated by an empirical application to insurance companies.

Suggested Citation

  • Qingxian An & Haoxun Chen & Beibei Xiong & Jie Wu & Liang Liang, 2020. "Fair Target Setting for Intermediate Products in Two-Stage Systems with Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Vincent Charles & Juan Aparicio & Joe Zhu (ed.), Data Science and Productivity Analytics, chapter 0, pages 201-226, Springer.
  • Handle: RePEc:spr:isochp:978-3-030-43384-0_7
    DOI: 10.1007/978-3-030-43384-0_7
    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:978-3-030-43384-0_7. 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.