Context-Dependent Data Envelopment Analysis-Measuring Attractiveness and Progress with Interval Data

Data envelopment analysis (DEA) is a method for recognizing the efficient frontier of decision making units (DMUs).This paper presents a Context-dependent DEA which uses the interval inputs and outputs. Context-dependent approach with interval inputs and outputs can consider a set of DMUs against the special context. Each context shows an efficient frontier including DMUs in particular levels. The Context-dependent DEA with interval inputs and outputs can measure (i) the attractiveness when DMUs showing weaker performance are selected as an appraisal context, and (ii) the interval progress when DMUs showing better performance are selected as the appraisal context.