IDEAS home Printed from https://ideas.repec.org/a/ids/ijisen/v23y2016i1p111-123.html
   My bibliography  Save this article

Efficiency evaluation of Mazandaran industrial parks by using neuro-DEA approach

Author

Listed:
  • M. Sharifi
  • J. Rezaeian

Abstract

Industrial park development is an important policy tool in many countries because the technology growth supported by parks can strengthens the industry and the economy of the country and, statistic recognising and ranking of industrial parks and zones is essential for improving industrial park development. In this paper, we evaluated efficiency of 25 industrial parks in one of the province of Iran using DEA, CCR output oriented and also the rank of DMUs using AP model for efficient DMUs in 2011-2012 and 2012-2013. Then we applied an artificial neural network and used its ability in prediction and analysed efficiency and rating of DMUs in 2012-2013 using integrated data envelopment analysis (DEA) and artificial neural networks (ANNs). Finally, the comparison between these two approaches in 2012-2013 is presented.

Suggested Citation

  • M. Sharifi & J. Rezaeian, 2016. "Efficiency evaluation of Mazandaran industrial parks by using neuro-DEA approach," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 23(1), pages 111-123.
  • Handle: RePEc:ids:ijisen:v:23:y:2016:i:1:p:111-123
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=75803
    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:ijisen:v:23:y:2016:i:1:p:111-123. 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=188 .

    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.