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Measuring and decomposing profit inefficiency through the Slacks-Based Measure

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  • Aparicio, Juan
  • Ortiz, Lidia
  • Pastor, Jesus T.

Abstract

The Slacks-Based Measure was introduced by Tone (2001) in order to estimate technical efficiency in the input-output space by taking into account all sources of technical inefficiency and satisfying, at the same time, many interesting properties. Since then, the Slacks-Based Measure has attracted the interest of numerous researchers and practitioners. The Slacks-Based Measure has been applied to technical efficiency determination, productivity change measurement, the analysis of production process performance consisting of networks, and so on. However, so far, the Slacks-Based Measure has not been directly related to profit inefficiency as a component of the overall economic performance of firms. In this note, we show how a specific normalized measure of profit inefficiency may be decomposed through the Slacks-Based Measure.

Suggested Citation

  • Aparicio, Juan & Ortiz, Lidia & Pastor, Jesus T., 2017. "Measuring and decomposing profit inefficiency through the Slacks-Based Measure," European Journal of Operational Research, Elsevier, vol. 260(2), pages 650-654.
  • Handle: RePEc:eee:ejores:v:260:y:2017:i:2:p:650-654
    DOI: 10.1016/j.ejor.2016.12.038
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    References listed on IDEAS

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    1. Aparicio, Juan & Borras, Fernando & Pastor, Jesus T. & Vidal, Fernando, 2015. "Measuring and decomposing firm׳s revenue and cost efficiency: The Russell measures revisited," International Journal of Production Economics, Elsevier, vol. 165(C), pages 19-28.
    2. William Cooper & Kyung Park & Jesus Pastor, 1999. "RAM: A Range Adjusted Measure of Inefficiency for Use with Additive Models, and Relations to Other Models and Measures in DEA," Journal of Productivity Analysis, Springer, vol. 11(1), pages 5-42, February.
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    Cited by:

    1. Xiong, Beibei & Chen, Haoxun & An, Qingxian & Wu, Jie, 2019. "A multi-objective distance friction minimization model for performance assessment through data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 279(1), pages 132-142.
    2. Halická, Margaréta & Trnovská, Mária, 2019. "Duality and profit efficiency for the hyperbolic measure model," European Journal of Operational Research, Elsevier, vol. 278(2), pages 410-421.
    3. Halická, Margaréta & Trnovská, Mária, 2018. "The Russell measure model: Computational aspects, duality, and profit efficiency," European Journal of Operational Research, Elsevier, vol. 268(1), pages 386-397.
    4. Feng Yang & Lijing Jiang & Sheng Ang, 2019. "A winner-take-all evaluation in data envelopment analysis," Annals of Operations Research, Springer, vol. 278(1), pages 141-158, July.
    5. Valentin Zelenyuk, 2018. "Profit Efficiency, DEA, FDH and Big Data," CEPA Working Papers Series WP042018, School of Economics, University of Queensland, Australia.

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