Abstract
Incorporating decision makers’ (DMs’) judgments and preferences into DEA models is very important in some real-world problems. This paper presents an integrated data envelopment analysis (DEA)—best–worst method (BWM)—for considering DMs’ preferences in DEA and reducing flexibility in weights of inputs and outputs. First, the preferences vectors are designed using BWM, and then, a multi-objective DEA-BWM model is introduced. The proposed DEA-BWM model simultaneously maximizes the efficiency scores of DMUs and considers DMs’ preferences about weights of inputs and outputs. Finally, a goal programming model is suggested for extending the DEA-BWM model and finding common weights of inputs and outputs based on the DMs’ judgments. The proposed common weight DEA-BWM (CWDEA-BWM) model maximizes the efficiencies of DMUs, considers DMs’ preferences and uses a set of common weights. In order to illustrate the capability of proposed models, a numerical example is solved. Moreover, the proposed DEA-BWM and common weight DEA-BWM models are applied to evaluate 39 Iranian electricity distribution companies, and the results are analyzed and compared. The results indicate that the proposed DEA-BWM and CWDEA-BWM models are suitable for incorporating DMs’ preferences into DEA and fully ranking of DMUs.
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The authors would like to thank Professor Antonio Di Nola, The Editor-in-Chief of journal of Soft Computing, and the anonymous reviewers for their insightful comments and suggestions. As a result, this paper has been improved substantially.
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Omrani, H., Alizadeh, A. & Naghizadeh, F. Incorporating decision makers’ preferences into DEA and common weight DEA models based on the best–worst method (BWM). Soft Comput 24, 3989–4002 (2020). https://doi.org/10.1007/s00500-019-04168-z
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DOI: https://doi.org/10.1007/s00500-019-04168-z