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Data envelopment analysis with uncertain data: An application for Iranian electricity distribution companies

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  • Sadjadi, S.J.
  • Omrani, H.

Abstract

This paper presents Data Envelopment Analysis (DEA) model with uncertain data for performance assessment of electricity distribution companies. During the past two decades, DEA has been widely used for benchmarking the electricity distribution companies. However, there is no study among many existing DEA approaches where the uncertainty in data is allowed and, at the same time, the distribution of the random data is permitted to be unknown. The proposed method of this paper develops a new DEA method with the consideration of uncertainty on output parameters. The method is based on the adaptation of recently developed robust optimization approaches proposed by Ben-Tal and Nemirovski [2000. Robust solutions of linear programming problems contaminated with uncertain data. Mathematical Programming 88, 411-421] and Bertsimas et al. [2004. Robust linear optimization under general norms. Operations Research Letters 32, 510-516]. The results are compared with an existing parametric Stochastic Frontier Analysis (SFA) using data from 38 electricity distribution companies in Iran to show the effects of the data uncertainties on the performance of DEA outputs. The results indicate that the robust DEA approach can be a relatively more reliable method for efficiency estimating and ranking strategies.

Suggested Citation

  • Sadjadi, S.J. & Omrani, H., 2008. "Data envelopment analysis with uncertain data: An application for Iranian electricity distribution companies," Energy Policy, Elsevier, vol. 36(11), pages 4247-4254, November.
  • Handle: RePEc:eee:enepol:v:36:y:2008:i:11:p:4247-4254
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    References listed on IDEAS

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    Cited by:

    1. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    2. Shermeh, H. Ebrahimzadeh & Najafi, S.E. & Alavidoost, M.H., 2016. "A novel fuzzy network SBM model for data envelopment analysis: A case study in Iran regional power companies," Energy, Elsevier, vol. 112(C), pages 686-697.
    3. Yan, Huijie, 2015. "Provincial energy intensity in China: The role of urbanization," Energy Policy, Elsevier, vol. 86(C), pages 635-650.
    4. Mohsen Pourebadollahan Covich & Archana Aggarwal, 2010. "Reform and Efficiency: An Application to Iranian Regional Electricity Companies," Iranian Economic Review, Economics faculty of Tehran university, vol. 15(2), pages 83-104, spring.
    5. Zhang, Xing-Ping & Cheng, Xiao-Mei & Yuan, Jia-Hai & Gao, Xiao-Jun, 2011. "Total-factor energy efficiency in developing countries," Energy Policy, Elsevier, vol. 39(2), pages 644-650, February.
    6. San Cristóbal, José Ramón, 2011. "A multi criteria data envelopment analysis model to evaluate the efficiency of the Renewable Energy technologies," Renewable Energy, Elsevier, vol. 36(10), pages 2742-2746.
    7. Nazila Aghayi & Madjid Tavana & Mohammad Ali Raayatpanah, 2016. "Robust efficiency measurement with common set of weights under varying degrees of conservatism and data uncertainty," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 10(3), pages 385-405.
    8. Fazıl Gökgöz & Ercem Erkul, 2014. "Energy Efficiency Analysis For The European Countries," Economy & Business Journal, International Scientific Publications, Bulgaria, vol. 8(1), pages 124-140.
    9. Bian, Yiwen & He, Ping & Xu, Hao, 2013. "Estimation of potential energy saving and carbon dioxide emission reduction in China based on an extended non-radial DEA approach," Energy Policy, Elsevier, vol. 63(C), pages 962-971.
    10. HATAMI-MARBINI, Adel & AGRELL, Per & AGHAYI, Nazila, 2013. "Imprecise data envelopment analysis for the two-stage process," CORE Discussion Papers 2013004, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. repec:spr:joptap:v:166:y:2015:i:2:d:10.1007_s10957-014-0633-4 is not listed on IDEAS
    12. Leme, Rafael C. & Paiva, Anderson P. & Steele Santos, Paulo E. & Balestrassi, Pedro P. & Galvão, Leandro de Lima, 2014. "Design of experiments applied to environmental variables analysis in electricity utilities efficiency: The Brazilian case," Energy Economics, Elsevier, vol. 45(C), pages 111-119.
    13. Arcos-Vargas, A. & Núñez-Hernández, F. & Villa-Caro, Gabriel, 2017. "A DEA analysis of electricity distribution in Spain: An industrial policy recommendation," Energy Policy, Elsevier, vol. 102(C), pages 583-592.

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