Estimating Most Productive Scale Size with Double Frontiers in Data Envelopment Analysis using Negative Data

Subject Areas : International Journal of Data Envelopment Analysis

F. Roozbeh ¹ ()
R. Eslami ² ()
M. Ahadzadeh Namin ³ ()

Received: 2016-06-15 Accepted : 2016-06-15 Published : 2015-11-01

Keywords: Data Envelopment Analysis, Most Productive Scale Size, Optimistic efficiency, Pessimistic efficiency, double frontiers, Negative data,

Abstract :

In this paper, it is assumed that the “Decision Making Units“( ) are consist of positive and negative input and output. Firstly, the optimistic and pessimistic models have been suggested by using negative data and then units with most productive scale size are measured in optimistic and pessimistic models. These productive values are compared with double frontiers and Hurwicz’s Criterion to obtain DMU with MPSS.