IDEAS home Printed from https://ideas.repec.org/a/ids/ijpqma/v22y2017i2p262-280.html
   My bibliography  Save this article

Linear robust data envelopment analysis: CCR model with uncertain data

Author

Listed:
  • Mahmood Sabouhi
  • Mostafa Mardani

Abstract

Data envelopment analysis (DEA) traditionally assumes that input and output data of the different decision making units (DMUs) are measured with precision. However, in many real applications inputs and outputs are often imprecise. This paper proposes a linear robust data envelopment analysis (LRDEA) model using imprecise data represented by an uncertainty set. The method is based on the robust optimisation approach of Bertsimas and Sim to seek maximisation of efficiency under uncertainty (as does the original DEA model). In this approach, it is possible to vary the degree of conservatism to allow for a decision maker to understand the tradeoff between a constraint's protection and its efficiency. The method incorporates the degree of conservatism in the maximum probability bound for constraint violation. Application of the proposed model (LRDEA) to analyse the technical and scale efficiency of potato production in 23 Iranian provinces demonstrates the reliability and flexibility of the model.

Suggested Citation

  • Mahmood Sabouhi & Mostafa Mardani, 2017. "Linear robust data envelopment analysis: CCR model with uncertain data," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 22(2), pages 262-280.
    • Handle: RePEc:ids:ijpqma:v:22:y:2017:i:2:p:262-280
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=86369
    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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Majid Mohammed Kunambi & Hongxing Zheng, 2024. "Contextual Comparative Analysis of Dar es Salaam and Mombasa Port Performance by Using a Hybrid DEA(CVA) Model," Logistics, MDPI, vol. 8(1), pages 1-20, January.
    2. Pejman Peykani & Jafar Gheidar-Kheljani & Reza Farzipoor Saen & Emran Mohammadi, 2022. "Generalized robust window data envelopment analysis approach for dynamic performance measurement under uncertain panel data," Operational Research, Springer, vol. 22(5), pages 5529-5567, November.
    3. Bello, S. & Onolemhemhen, R., 2024. "Does carbon pricing policy influence carbon emission intensity? New Evidence from Canadian Provinces," Cambridge Working Papers in Economics 2445, Faculty of Economics, University of Cambridge.
    4. Mostafa Mardani Najafabadi & Niloofar Ashktorab, 2023. "Mathematical programming approaches for modeling a sustainable cropping pattern under uncertainty: a case study in Southern Iran," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 9731-9755, September.
    5. Mostafa Mardani Najafabadi & Hanieh Kazmi & Somayeh Shirzadi Laskookalayeh & Abas Abdeshahi, 2023. "Investigating the ability of fuzzy and robust DEA models to apply uncertainty conditions: an application for date palm producers," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 776-801, June.

    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:ijpqma:v:22:y:2017:i:2:p:262-280. 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=177 .

    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.