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A One-Step Procedure for Returns to Scale Classification of Decision Making Units in Data Envelopment Analysis

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  • Subhash C. Ray

    (University of Connecticut)

Abstract

The input-output bundle of an efficient decision making unit (DMU) is located at a specific point on the frontier of the production possibility set. Returns to Scale (RTS) at this point can be unequivocally characterized. For an inefficient DMU, however, the input- and output-oriented projections on to the frontier will be different and RTS classifications at these two points may differ. In the existing literature, one needs to solve two DEA problems, one input-oriented and another output-oriented to determine the nature of RTS at these two different efficient projections. This paper shows how one can determine the returns to scale properties of an inefficient bundle simultaneously at both projections from the optimal solution of a single CCR-DEA problem either output- or input-oriented. A data set used by Christensen and Greene in their well known study of US electric utilities is used for an illustration of the proposed method in a numerical example.

Suggested Citation

  • Subhash C. Ray, 2010. "A One-Step Procedure for Returns to Scale Classification of Decision Making Units in Data Envelopment Analysis," Working papers 2010-07, University of Connecticut, Department of Economics.
    • Handle: RePEc:uct:uconnp:2010-07
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    References listed on IDEAS

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    1. Kerstens, Kristiaan & Vanden Eeckaut, Philippe, 1999. "Estimating returns to scale using non-parametric deterministic technologies: A new method based on goodness-of-fit," European Journal of Operational Research, Elsevier, vol. 113(1), pages 206-214, February.
    2. Banker, Rajiv D., 1984. "Estimating most productive scale size using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 17(1), pages 35-44, July.
    3. Banker, Rajiv D. & Cooper, William W. & Seiford, Lawrence M. & Thrall, Robert M. & Zhu, Joe, 2004. "Returns to scale in different DEA models," European Journal of Operational Research, Elsevier, vol. 154(2), pages 345-362, April.
    4. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    5. V V Podinovski, 2004. "Local and global returns to scale in performance measurement," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(2), pages 170-178, February.
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    Cited by:

    1. Peter Fernandes Wanke & Rebecca de Mattos, 2014. "Capacity Issues and Efficiency Drivers in Brazilian Bulk Terminals," Brazilian Business Review, Fucape Business School, vol. 11(5), pages 72-98, October.
    2. Subhash C. Ray, 2014. "Data Envelopment Analysis: An Overview," Working papers 2014-33, University of Connecticut, Department of Economics.
    3. Lei Chen & Rangan Gupta & Zinnia Mukherjee & Peter Wanke, 2016. "Technical efficiency of Connecticut Long Island Sound lobster fishery: a nonparametric approach to aggregate frontier analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(3), pages 1533-1548, April.
    4. Subhash C. Ray, 2018. "Data Envelopment Analysis with Alternative Returns to Scale," Working papers 2018-20, University of Connecticut, Department of Economics.
    5. Wanke, Peter & Barros, C.P. & Nwaogbe, Obioma R., 2016. "Assessing productive efficiency in Nigerian airports using Fuzzy-DEA," Transport Policy, Elsevier, vol. 49(C), pages 9-19.

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    More about this item

    Keywords

    Most Productive Scale Size; Convex Technologies; Nonparametric Efficiency Analysis;
    All these keywords.

    JEL classification:

    • D2 - Microeconomics - - Production and Organizations
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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