Abstract
One of the main challenging issues in the conventional data envelopment analysis (DEA) is ranking efficient decision-making units (DMUs) when more than one DMU have the efficiency score equal to one. It must be mentioned that most of the DMUs have internal structures. In this regard, in order to measure the efficiency score of these DMUs, network DEA methods are applied. Most researches are focused on assessing the efficiency of these DMUs and just like the classic DEA, several DMUs are efficient. To identify the sources and estimate the amount of inefficiencies in DMUs with network structure and overcome some shortcomings in the previous ranking models, in this paper, a slack-based network model of super efficiency, considering the optimal value of intermediate measures in the objective function and right handset for ranking overall efficient DMUs, are suggested to have more accurate and comprehensive ranking DMUs with internal structures. Finally, two numerical and empirical examples are provided to verify the discriminative power of the proposed model.
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