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Estimating most productive scale size with double frontiers data envelopment analysis

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  • Wang, Ying-Ming
  • Lan, Yi-Xin

Abstract

In this paper, most productive scale size (MPSS) for input and output mixes is measured from pessimistic point of view by using pessimistic data envelopment analysis (DEA). It is proved that the decision making unit (DMU) with the maximum pessimistic efficiency represents MPSS. However, the optimistic and the pessimistic measurements may identify different DMU as MPSS. To find the optimal DMU that represents MPSS, a double frontiers approach is developed by using the Hurwicz criterion to integrate both the information on the optimistic and the pessimistic frontiers. Numerical examples are provided to show the applications of the proposed methods in estimating MPSS.

Suggested Citation

  • Wang, Ying-Ming & Lan, Yi-Xin, 2013. "Estimating most productive scale size with double frontiers data envelopment analysis," Economic Modelling, Elsevier, vol. 33(C), pages 182-186.
    • Handle: RePEc:eee:ecmode:v:33:y:2013:i:c:p:182-186
    DOI: 10.1016/j.econmod.2013.04.021
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    References listed on IDEAS

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    Cited by:

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    4. A. Davoodi & M. Zarepisheh & H. Rezai, 2015. "The nearest MPSS pattern in data envelopment analysis," Annals of Operations Research, Springer, vol. 226(1), pages 163-176, March.
    5. Lei Chen & Fei-Mei Wu & Feng Feng & Fujun Lai & Ying-Ming Wang, 2018. "A Common Set of Weights for Ranking Decision-Making Units with Undesirable Outputs: A Double Frontiers Data Envelopment Analysis Approach," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(06), pages 1-25, December.
    6. Embaye, Weldensie T. & Bergtold, Jason S., 2017. "Effect of Crop Insurance Subsidy on Total Farm Productivity of Kansas Farms, US," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258107, Agricultural and Applied Economics Association.
    7. Eshagh Esfandiar & Robabeh Eslami & Mohammad Khoveyni & Alireza Gilani, 2023. "Identifying the closest most productive scale size unit in data envelopment analysis," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(2), pages 623-660, June.
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