Classifying Flexible Factors Using Fuzzy Concept

In Data Envelopment Analysis (DEA), it is assumed that the role of each factor is known asinput or output. However, in some cases, there are shared factors that their input versusoutput status is not clearly known. These are flexible measures. In such cases, determiningwhether a factor is input or output is ambiguous. Therefore, using fuzzy concept seems to benecessary.In this paper, a two phase procedure is proposed to fuzzy classification of flexible measures.In the first phase, applying the existing classification methods, an orientation of flexiblemeasures to aid in the definition of inputs and outputs is achieved. Through defining amembership function in second phase, the input versus output status of a factor is expressedby fuzzy notion. By the proposed method, the efficiency of a decision mating unit is defendedby a membership degree. We illustrate the proposed model in a practical problem setting.