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

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 alpha-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.