A Slacks-base Measure of Super-efficiency for Dea with Negative Data

Data envelopment analysis (DEA) is a non-parametric method for measuring the efficiency of a set of decision making units (DMUs), such as companies or public sector agencies. The main DEA models are only used for positive data. In recent years, some models have been presented to deal with negative data in DEA models. However, these models do not discriminate between efficient DMUs and only evaluate them as being efficient. In this paper, we propose a model by which we discriminate between such DMUs. Then, using the slacks-based measures (SBM) of efficiency introduced by Tone in 2001, we extend the super-efficiency problem for DEA models with positive and negative inputs and outputs. We, then, discuss the model and its stability, and elaborate on the problem by a numerical example