Classifying Flexible Measures in Two-Stage Network DEA

Standard Data Envelopment Analysis (DEA) supposes that the performance measure status from the point of view of input or output is known. Nevertheless, in some situations, determining the status of a performance measure in two-stage network is not easy. Measures with unknown status of input/output are called exible measures. In all of the previous studies did not point to classify exible measures in two-stage network DEA. In this paper we propose FNDEA models based on the multiplier model under constant returns to scale (CRS) and variable returns to scale (VRS) in general two-stage network structures. Our models classify exible measures, in which each one of the exible measure is treated as either input or output to maximize the overall network effciency of the DMU under evaluation. The current paper develops an additive effciency decomposition approach wherein the overall effciency is expressed as a (weighted) sum of the effciencies of the individual stages. This approach can be applied under both CRS and (VRS) assumptions. Numerical examples are used to illustrate the procedures.