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Evaluation of Two-Stage Networks Based on Average Efficiency Using DEA and DEA-R with Fuzzy Data

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Abstract

The present paper proposes a number of models for calculating the average efficiency of two-stage networks using DEA and DEA-R with fuzzy data. If the input, intermediate, and output parameters are available in a two-stage network, DEA and DEA-R models can be used to compute the efficiency. When evaluating decision-making units (DMUs) in two-stage network DEA, the respective programming models are fractional. Meanwhile, in DEA-R, the proposed programming models are linear. Although, it is necessary that the output-to-input ratios (output-orientation) or vice versa (input orientation) be defined and available. Furthermore, DEA-R models can also evaluate DMUs with a network structure when only ratio data are available. Generally, using fuzzy data is necessary for an accurate evaluation of organizations with a two-stage network structure. Therefore, in the present article, using the α-cut approach, an average efficiency model is proposed for the first and second stages of a network structure. At the end, a comparison is made between the mean efficiency scores of a number of airlines by considering fuzzy data in two-stage network DEA and DEA-R.

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Notes

  1. The data used in this study can be observed at the web address https://www.cao.ir/statistical-yearbook, which is the official website of the Iranian Civil Aviation Organization.

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Authors and Affiliations

  1. Department of Mathematics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran

    S. Ostovan & A. Jamshidi

  2. Department of Mathematics, Shiraz Branch, Islamic Azad University, Shiraz, Iran

    M. R. Mozaffari & J. Gerami

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  1. S. Ostovan
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  2. M. R. Mozaffari
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  3. A. Jamshidi
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  4. J. Gerami
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Correspondence to M. R. Mozaffari.

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Ostovan, S., Mozaffari, M.R., Jamshidi, A. et al. Evaluation of Two-Stage Networks Based on Average Efficiency Using DEA and DEA-R with Fuzzy Data. Int. J. Fuzzy Syst. 22, 1665–1678 (2020). https://doi.org/10.1007/s40815-020-00896-9

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  • DOI: https://doi.org/10.1007/s40815-020-00896-9

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