Finding Target in the Two-Stage Networks based on the CRA Model in DEA-RA

Considering intermediate data, two-stage networks eliminate the possibility of evaluating the performance of decision-making units in Black box mode. In this article, based on the structure of two-stage networks, Central Resource Allocation (CRA) models with fuzzy data are proposed. Then, two-stage network models are proposed in the form of combining data envelopment analysis and Raito analysis. In general, the models of this article using the CRA structure, Target introduce the decision-making units under the assumption of constant return to scale. CRA models in the two-stage network structure in DEA-R provide the possibility of finding suitable targets for decision-making units by solving a linear programming model instead of solving n linear programming problems (for n decision-making units). In conclusion, the models are proposed based on a practical study on 16 Iranian airlines.