Uncertain Super-Efficiency Data Envelopment Analysis

Pejman Peykani (), Jafar Gheidar-Kheljani (), Donya Rahmani (), Mohammad Hossein Karimi Gavareshki () and Armin Jabbarzadeh ()
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Pejman Peykani: Iran University of Science and Technology
Jafar Gheidar-Kheljani: Malek Ashtar University of Technology
Donya Rahmani: K. N. Toosi University of Technology
Mohammad Hossein Karimi Gavareshki: Malek Ashtar University of Technology
Armin Jabbarzadeh: École de Technologie Supérieure (ETS)

A chapter in Advances in Econometrics, Operational Research, Data Science and Actuarial Studies, 2022, pp 311-320 from Springer

Abstract: Abstract The main goal of the current study is to propose a new method for ranking homogeneous decision-making units in the presence of uncertain inputs and/or outputs. To reach this goal, data envelopment analysis approach, super-efficiency technique, and uncertainty theory are applied. Accordingly, in this study, a novel uncertain super-efficiency data envelopment analysis approach is presented that is capable to be used under data uncertainty. Notably, the super-efficiency data envelopment analysis approach is proposed under constant returns to scale assumption and multiplier form. Additionally, to show the efficacy and applicability of the proposed method, a numerical example related to five decision-making units with two uncertain inputs and two uncertain outputs is utilized. The results indicate that the proposed uncertain super-efficiency data envelopment analysis approach is an effective and applicable method for performance evaluation and ranking of decision-making units under uncertainty environment.

Keywords: Ranking approach; Super-efficiency; Data envelopment analysis; Uncertain data; Uncertainty theory (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:conchp:978-3-030-85254-2_19

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DOI: 10.1007/978-3-030-85254-2_19

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