As an important concept in data envelopment analysis (DEA), closest target has wide theoretical and practical applications. By considering the data of closest target and utilizing it appropriately, the decision making unit (DMU) under evaluation determines how to transf
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As an important concept in data envelopment analysis (DEA), closest target has wide theoretical and practical applications. By considering the data of closest target and utilizing it appropriately, the decision making unit (DMU) under evaluation determines how to transform its inputs and outputs to become efficient. Also, traditional DEA models only utilize the external inputs to produce the final outputs in evaluating the relative efficiency of decision making units (DMUs), and internal operations are not be considered. Therefore, traditional models can not accurately determine the source of inefficiency inside the structures. To overcome this problem, different authors proposed various network DEA models (NDEA). This paper is an attempt to find the closest target in various scenarios of network DEA. The study concerns about different existed scenarios in network DEA models and proposes specific models to find closest targets in each scenario. Also, an empirical example has been presented to illustrate the proposed models.
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