IDEAS home Printed from https://ideas.repec.org/h/spr/oprchp/978-3-319-07001-8_33.html
   My bibliography  Save this book chapter

Sensitivity Analysis of BCC Efficiency in DEA with Application to European Health Services

In: Operations Research Proceedings 2013

Author

Listed:
  • Andreas Kleine

    (Fern Universität Hagen)

  • Andreas Dellnitz

    (Fern Universität Hagen)

  • Wilhelm Rödder

    (Fern Universität Hagen)

Abstract

The CCR model by Charnes et al. [4] on the one hand and BCC model by Banker et al. [3] on the other hand are the most common used approaches of data envelopment analysis (DEA). If we measure efficiency of decision making units (DMUs) by the BCC model, technology is characterized by variable returns to scale. If the inputs and outputs of a DMU are scaled by two parameters such that the BCC (in)efficiency score is unchanged we call this adaptation a bicentric scaling (BS). We introduce a linear program to calculate the BS stability region of all DMUs, efficient or inefficient. Moreover we determine the scale efficiency within the stability region. The new approach is illustrated by a numerical example of European health services. We demonstrate the BS stability region for various states and illustrate consequences on scale efficiency. It is shown that some states can improve scale efficiency without losing BCC efficiency.

Suggested Citation

  • Andreas Kleine & Andreas Dellnitz & Wilhelm Rödder, 2014. "Sensitivity Analysis of BCC Efficiency in DEA with Application to European Health Services," Operations Research Proceedings, in: Dennis Huisman & Ilse Louwerse & Albert P.M. Wagelmans (ed.), Operations Research Proceedings 2013, edition 127, pages 243-248, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-07001-8_33
    DOI: 10.1007/978-3-319-07001-8_33
    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. Dellnitz, Andreas & Tavana, Madjid, 2024. "Data envelopment analysis: From non-monotonic to monotonic scale elasticities," European Journal of Operational Research, Elsevier, vol. 318(2), pages 549-559.
    2. Andreas Dellnitz & Andreas Kleine & Wilhelm Rödder, 2018. "CCR or BCC: what if we are in the wrong model?," Journal of Business Economics, Springer, vol. 88(7), pages 831-850, September.

    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:oprchp:978-3-319-07001-8_33. 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.