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Improved efficiency measures through directional distance formulation of data envelopment analysis

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  • Ali Diabat
  • Udaya Shetty
  • T. Pakkala

Abstract

This paper develops a model for an improved efficiency measure through directional distance formulation of data envelopment analysis. It deals with cases where positive and negative values co-exist as production factors. The developed model has properties such as scalar quantity for measuring efficiency and it identifies all sources of inefficiency. The measure is weakly monotonic; units and translation do not vary with respect to inputs and outputs. The proposed model, under some restrictions, reduces to basic Data Envelopment Analysis (DEA) models such as Charnes-Cooper-Rhodes (CCR), Banker-Charnes-Cooper (BCC), and a slack based model (SBM). In addition to the above, the proposed model includes the closest targets for a given inefficient unit to achieve efficiency with less effort. The proposed model is validated using a case study done on Information Technology firms operating in India. Copyright Springer Science+Business Media New York 2015

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  • Ali Diabat & Udaya Shetty & T. Pakkala, 2015. "Improved efficiency measures through directional distance formulation of data envelopment analysis," Annals of Operations Research, Springer, vol. 229(1), pages 325-346, June.
    • Handle: RePEc:spr:annopr:v:229:y:2015:i:1:p:325-346:10.1007/s10479-013-1470-9
    DOI: 10.1007/s10479-013-1470-9
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    Cited by:

    1. Kao, Chiang, 2022. "Measuring efficiency in a general production possibility set allowing for negative data: An extension and a focus on returns to scale," European Journal of Operational Research, Elsevier, vol. 296(1), pages 267-276.
    2. Mustapha Daruwana Ibrahim & Sahand Daneshvar & Hüseyin Güden & Bela Vizvari, 2020. "Target setting in data envelopment analysis: efficiency improvement models with predefined inputs/outputs," OPSEARCH, Springer;Operational Research Society of India, vol. 57(4), pages 1319-1336, December.
    3. Antunes, Jorge & Tan, Yong & Wanke, Peter & Jabbour, Charbel Jose Chiappetta, 2023. "Impact of R&D and innovation in Chinese road transportation sustainability performance: A novel trigonometric envelopment analysis for ideal solutions (TEA-IS)," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    4. Youchao Tan & Udaya Shetty & Ali Diabat & T. Pakkala, 2015. "Aggregate directional distance formulation of DEA with integer variables," Annals of Operations Research, Springer, vol. 235(1), pages 741-756, December.
    5. Victoria Wojcik & Harald Dyckhoff & Sebastian Gutgesell, 2017. "The desirable input of undesirable factors in data envelopment analysis," Annals of Operations Research, Springer, vol. 259(1), pages 461-484, December.
    6. Kao, Chiang, 2020. "Measuring efficiency in a general production possibility set allowing for negative data," European Journal of Operational Research, Elsevier, vol. 282(3), pages 980-988.

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