Dealing with Interval Scale Data in Data Envelopment Analysis

Halme, M., Joro, T., & Koivu, M. (1998). Dealing with Interval Scale Data in Data Envelopment Analysis. IIASA Interim Report. IIASA, Laxenburg, Austria: IR-98-112

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Abstract

This papaer considers the problem of interval scale data in the most widely used models of Data Envelopment Analysis (DEA), the CCR, and the BCC models. Radial models require inputs and outputs measured on the ratio scale. Our focus is on how to deal with interval scale variables especially when the interval scale variable is a difference of two ratio scale variables like profit or the decrease/increase in bank accounts. Using these ratio scale variables as variables in the DEA model we suggest radial models. An approach to how to deal with interval scale variables when we relax the radiality assumption is also discussed.

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