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An integrated data envelopment analysis and simulation method for group consensus ranking

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  • Ebrahimnejad, Ali
  • Tavana, Madjid
  • Santos-Arteaga, Francisco J.

Abstract

Group consensus ranking is an important topic in performance evaluation and selection research. Data envelopment analysis (DEA) has been used for obtaining an efficiency score (preference score) for each candidate. We propose an integrated DEA and simulation method for group consensus ranking. The ranking method proposed in this study has several unique features. In contrast to most voting methods that assume equal voting power to voters, the proposed method classifies voters into different groups and allows for assigning a different voting power to each group. In spite of its effectiveness, though similarly to the competing methods in the literature, the proposed method may lead to more than one efficient candidate. Several ranking models are extended and used to discriminate among the efficient candidates. Despite the wealth of information provided to the decision maker(s), different extended ranking models may produce different rankings. Simulation is used to analyze these rankings and synthesize them into one overall group ranking. A case study is used to demonstrate the applicability and exhibit the efficacy of the proposed method.

Suggested Citation

  • Ebrahimnejad, Ali & Tavana, Madjid & Santos-Arteaga, Francisco J., 2016. "An integrated data envelopment analysis and simulation method for group consensus ranking," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 119(C), pages 1-17.
    • Handle: RePEc:eee:matcom:v:119:y:2016:i:c:p:1-17
    DOI: 10.1016/j.matcom.2015.08.022
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    Cited by:

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    2. Georgios Tsaples & Jason Papathanasiou & Andreas C. Georgiou, 2022. "An Exploratory DEA and Machine Learning Framework for the Evaluation and Analysis of Sustainability Composite Indicators in the EU," Mathematics, MDPI, vol. 10(13), pages 1-27, June.
    3. Chaofan Xian & Shuo Yang & Yupeng Fan & Haotong Wu & Cheng Gong, 2022. "Coupling Efficiency Assessment of Food–Energy–Water (FEW) Nexus Based on Urban Resource Consumption towards Economic Development: The Case of Shenzhen Megacity, China," Land, MDPI, vol. 11(10), pages 1-25, October.
    4. Kao, Chiang & Liu, Shiang-Tai, 2022. "Group decision making in data envelopment analysis: A robot selection application," European Journal of Operational Research, Elsevier, vol. 297(2), pages 592-599.
    5. Mehdi Toloo & Madjid Tavana & Francisco J. Santos-Arteaga, 2019. "An integrated data envelopment analysis and mixed integer non-linear programming model for linearizing the common set of weights," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(4), pages 887-904, December.
    6. K. Kounetas & G. Androulakis & M. Kaisari & G. Manousakis, 2023. "Educational reforms and secondary school's efficiency performance in Greece: a bootstrap DEA and multilevel approach," Operational Research, Springer, vol. 23(1), pages 1-29, March.
    7. Mohammad Izadikhah & Reza Farzipoor Saen, 2019. "Solving voting system by data envelopment analysis for assessing sustainability of suppliers," Group Decision and Negotiation, Springer, vol. 28(3), pages 641-669, June.

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