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Introducing and modeling inefficiency contributions

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  • Asmild, Mette
  • Kronborg, Dorte
  • Matthews, Kent

Abstract

Whilst Data Envelopment Analysis (DEA) is the most commonly used non-parametric benchmarking approach, the interpretation and application of DEA results can be limited by the fact that radial improvement potentials are identified across variables. In contrast, Multi-directional Efficiency Analysis (MEA) facilitates analysis of the nature and structure of the inefficiencies estimated relative to variable-specific improvement potentials.

Suggested Citation

  • Asmild, Mette & Kronborg, Dorte & Matthews, Kent, 2016. "Introducing and modeling inefficiency contributions," European Journal of Operational Research, Elsevier, vol. 248(2), pages 725-730.
    • Handle: RePEc:eee:ejores:v:248:y:2016:i:2:p:725-730
    DOI: 10.1016/j.ejor.2015.07.060
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    2. Malin Song & Jianlin Wang & Jiajia Zhao & Tomas Baležentis & Zhiyang Shen, 2020. "Production and safety efficiency evaluation in Chinese coal mines: accident deaths as undesirable output," Annals of Operations Research, Springer, vol. 291(1), pages 827-845, August.
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    4. Manevska-Tasevska, Gordana & Hansson, Helena & Asmild, Mette & Surry, Yves, 2021. "Exploring the regional efficiency of the Swedish agricultural sector during the CAP reforms ‒ multi-directional efficiency analysis approach," Land Use Policy, Elsevier, vol. 100(C).

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