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An extended slacks-based measure model for data envelopment analysis with negative data

Author

Listed:
  • Mansour Mohammadpour

    (Department of Mathematics, Boukan Branch, Islamic Azad University, Boukan, Iran)

  • Farhad Hosseinzadeh-Lotfi

    (Department of Mathematics, Science and Research Branch, Islamic Azad University, Hesarak, Poonak, Tehran, Iran)

  • Gholam-Reza Jahanshahloo

    (Department of Mathematics, Science and Research Branch, Islamic Azad University, Hesarak, Poonak, Tehran, Iran)

Abstract

Data envelopment analysis (DEA) is a non-parametric approach based on linear programming that has been widely applied for evaluating the relative efficiency of a set of homogeneous decision-making units (DMUs) with multiple inputs and outputs. The original DEA models use positive input and output variables that are measured on a ratio scale, but these models do not apply to the variables in which negative data can appear. However, with the widespread use of interval scale data and undesirable data, the emphasis has been directed towards the simultaneous consideration of the positive and negative data in DEA models. In this paper, using the slacks-based measure, we propose an extended model to evaluate the efficiency of DMUs, even if some variables are measured on an interval scale and some on a ratio scale. Moreover, the extended model allows for the presence of all interval-scale variables, which are capable of taking both negative and positive values.

Suggested Citation

  • Mansour Mohammadpour & Farhad Hosseinzadeh-Lotfi & Gholam-Reza Jahanshahloo, 2015. "An extended slacks-based measure model for data envelopment analysis with negative data," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(7), pages 1206-1211, July.
    • Handle: RePEc:pal:jorsoc:v:66:y:2015:i:7:p:1206-1211
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    Cited by:

    1. Lee, Hsuan-Shih, 2021. "Slacks-based measures of efficiency and super-efficiency in presence of nonpositive data," Omega, Elsevier, vol. 103(C).

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