IDEAS home Printed from https://ideas.repec.org/a/ids/ijidsc/v10y2018i2p162-180.html
   My bibliography  Save this article

Productivity of steam power-plants using uncertain DEA-based Malmquist index in the presence of undesirable outputs

Author

Listed:
  • Kaveh Khalili-Damghani
  • Elham Haji-Sami

Abstract

Energy generation is mixed with production of emissions, called undesirable outputs. Moreover, the values of inputs and outputs of criteria are not deterministic in real productions and usually mixed with a great amount of uncertainties during planning horizon. So, measuring the productivity in the presence of uncertainty and undesirable outputs is not a trivial task. In this paper, an uncertain data envelopment analysis (DEA)-based Malmquist productivity index (MPI) is developed in presence of undesirable outputs to assess the productivity of production. The theoretical properties of the proposed models are discussed. The proposed method is applied on real case study in ten steam electricity power-plants. Moreover, the changes in technical efficiencies and changes in technology during multiple periods which influence productivity are sensed using proposed approach. The regress and progress of a power plant is demonstrated during planning horizons and the cause of these are also illustrated.

Suggested Citation

  • Kaveh Khalili-Damghani & Elham Haji-Sami, 2018. "Productivity of steam power-plants using uncertain DEA-based Malmquist index in the presence of undesirable outputs," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 10(2), pages 162-180.
  • Handle: RePEc:ids:ijidsc:v:10:y:2018:i:2:p:162-180
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=92422
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:ids:ijidsc:v:10:y:2018:i:2:p:162-180. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=306 .

    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.