Abstract
Data Envelopment Analysis (DEA) is well known as evaluation method to measure the efficiencies of decision making units (DMUs) relatively with multiple inputs and outputs items. One of the features of DEA is that DMUs are evaluated based on the Pareto optimal line composed of efficient DMUs (this line is called as “Efficiency Frontier” in DEA). As the efficiency value of the target DMU is calculated by the relative comparison between the current DMU and the point on the efficiency frontier which is the easiest to achieve, the compared points differ for every DMU. Therefore, it is possible to evaluate the efficiency of DMUs relatively considering features of them. On the other hand, there are many cases that a certain adjustment about the data is necessary to make some decisions from the objective results of DEA. To analyze the DEA results continuously, this paper proposed the DEA framework. A proposed framework consists of two following steps: (1) extracting subjectivity information based on a paired comparison, (2) extending the traditional DEA model. The proposed model does not add restrictions to a variable directly and it is formulated in the form where it corrects the search direction, “No solution” does not come out of it. Since the proposed model is correcting the search direction, an analyst’s intention is incorporated without taking out an execution impossible solution.
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