IDEAS home Printed from https://ideas.repec.org/h/spr/oprchp/978-3-540-77903-2_52.html
   My bibliography  Save this book chapter

Efficiency Measurement of Organizations in Multi-Stage Systems

In: Operations Research Proceedings 2007

Author

Listed:
  • Andreas Kleine

    (University of Hohenheim (510 A))

Abstract

Traditional Data Envelopment Analysis (DEA) characterizes decision making units by a vector of external inputs and outputs. By the use of a scalarizing function the inputs and outputs are aggregated to an efficiency measure for each unit. DEA models are based on the assumption that the production process is a “black box”, i.e. inputs are transformed in this box into outputs. In many cases more information about the production process is available. This is especially the case in multi-stage production systems. Decision making units of the underlying network employ intermediate and external inputs simultaneously. Unlike external inputs, which are assumed in classical models, intermediate inputs are provided directly by decision making units of the network. This means that intermediate goods affect the performance measure of at least two decision making units, the unit providing services and the unit applying these services. For this very reason a general DEA-model is introduced, which takes the special features of units in a multi-stage system into consideration.

Suggested Citation

  • Andreas Kleine, 2008. "Efficiency Measurement of Organizations in Multi-Stage Systems," Operations Research Proceedings, in: Jörg Kalcsics & Stefan Nickel (ed.), Operations Research Proceedings 2007, pages 337-342, Springer.
  • Handle: RePEc:spr:oprchp:978-3-540-77903-2_52
    DOI: 10.1007/978-3-540-77903-2_52
    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:oprchp:978-3-540-77903-2_52. 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.