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A distance-based measure of super efficiency in data envelopment analysis: an application to gas companies

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  • Alireza Amirteimoori
  • Sohrab Kordrostami

Abstract

Conventional data envelopment analysis (DEA) assists decision makers in distinguishing between efficient and inefficient decision making units (DMUs) in a homogeneous group. Standard DEA models can not provide more information about efficient units. Super-efficiency DEA models can be used in ranking the performance of efficient DMUs and overcome this obstacle. Because of the possible infeasibility, the use of super efficiency models has been restricted. This research proposes a methodology to determine a distance-based measure of super-efficiency. The proposed methodology overcomes the infeasibility problem of the existing ranking methodologies. The applicability of the proposed model is illustrated in the context of the analysis of gas companies’ performance. Copyright Springer Science+Business Media, LLC. 2012

Suggested Citation

  • Alireza Amirteimoori & Sohrab Kordrostami, 2012. "A distance-based measure of super efficiency in data envelopment analysis: an application to gas companies," Journal of Global Optimization, Springer, vol. 54(1), pages 117-128, September.
    • Handle: RePEc:spr:jglopt:v:54:y:2012:i:1:p:117-128
    DOI: 10.1007/s10898-011-9745-7
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    References listed on IDEAS

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    1. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    2. David Hawdon, 2003. "Efficiency and Performance in the Gas Industry," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 106, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    4. Lins, Marcos P. Estellita & Gomes, Eliane G. & Soares de Mello, Joao Carlos C. B. & Soares de Mello, Adelino Jose R., 2003. "Olympic ranking based on a zero sum gains DEA model," European Journal of Operational Research, Elsevier, vol. 148(2), pages 312-322, July.
    5. Banker, Rajiv D. & Chang, Hsihui, 2006. "The super-efficiency procedure for outlier identification, not for ranking efficient units," European Journal of Operational Research, Elsevier, vol. 175(2), pages 1311-1320, December.
    6. Chen, Yao, 2005. "Measuring super-efficiency in DEA in the presence of infeasibility," European Journal of Operational Research, Elsevier, vol. 161(2), pages 545-551, March.
    7. Jahanshahloo, Gholam Reza & Junior, Helcio Vieira & Lotfi, Farhad Hosseinzadeh & Akbarian, Darush, 2007. "A new DEA ranking system based on changing the reference set," European Journal of Operational Research, Elsevier, vol. 181(1), pages 331-337, August.
    8. Hawdon, David, 2003. "Efficiency, performance and regulation of the international gas industry--a bootstrap DEA approach," Energy Policy, Elsevier, vol. 31(11), pages 1167-1178, September.
    9. Chen, Yao, 2004. "Ranking efficient units in DEA," Omega, Elsevier, vol. 32(3), pages 213-219, June.
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    Cited by:

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    3. Alexander P. Afanasiev & Vladimir E. Krivonozhko & Andrey V. Lychev & Oleg V. Sukhoroslov, 2020. "Multidimensional frontier visualization based on optimization methods using parallel computations," Journal of Global Optimization, Springer, vol. 76(3), pages 563-574, March.
    4. Capece, Guendalina & Costa, Roberta & Di Pillo, Francesca, 2021. "Benchmarking the efficiency of natural gas distribution utilities in Italy considering size, ownership, and maturity," Utilities Policy, Elsevier, vol. 72(C).

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