An Inverse DEA-based Model for Interval Scale Data

Abstract

Data Envelopment Analysis (DEA) is a mathematical programming technique for evaluating a set of homogeneous Decision Making Units. When applying basic DEA models, it is necessary that input(s) and output(s) of all units are semi-positive and measured on a ratio scale. In case that some data are negative or measured on an interval scale, the basic DEA models are useless, and it is necessary to develop new models that can be applied for interval-scale data. In this paper, the subject of inverse DEA is discussed for a DEA-based efficiency model for interval scale data and an inverse model is developed. We also investigate validity of the proposed inverse model by means of presenting a relevant theorem.