Network DEA based on DEA-ratio

Dariush Akbarian ()
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Dariush Akbarian: Islamic Azad University

Financial Innovation, 2021, vol. 7, issue 1, 1-26

Abstract: Abstract Data envelopment analysis (DEA) is a technique to measure the performance of decision-making units (DMUs). Conventional DEA treats DMUs as black boxes and the internal structure of DMUs is ignored. Two-stage DEA models are special case network DEA models that explore the internal structures of DMUs. Most often, one output cannot be produced by certain input data and/or the data may be expressed as ratio output/input. In these cases, traditional two-stage DEA models can no longer be used. To deal with these situations, we applied DEA-Ratio (DEA-R) to evaluate two-stage DMUs instead of traditional DEA. To this end, we developed two novel DEA-R models, namely, range directional DEA-R (RDD-R) and (weighted) Tchebycheff norm DEA-R (TND-R). The validity and reliability of our proposed approaches are shown by some examples. The Taiwanese non-life insurance companies are revisited using these proposed approaches and the results from the proposed methods are compared with those from some other methods.

Keywords: Data envelopment analysis; DEA-R; Two-stage DEA (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1186/s40854-021-00278-6

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