A Method for Identifying Congestion Using Non-Radial Models in Data Envelopment Analysis

Data envelopment analysis (dea) is a nonparametric method that aims to use scientific methods in order to investigate the performance of decision making unit (dmu). one of the interesting subjects in dea is estimation of congestion of dmus. congestion problem has an important role in economy because the congestion mostly occurs in the input which is itself cost based, thus by eliminating congestion, the cost reduces as well. therefore, detecting and reducing congestion both have many benefits. many methods have been proposed to detect congestion in dea. in this paper, we are going to present a new method to identify congestion based on the definition of congestion. the proposed method in this paper has the following advantages compare with other methods; firstly, it is less complicated than other methods. secondly, our method is able to identify the congestion and its degree correctly. thirdly the new model identities the congestion of all units. finally, the proposed method in this paper has non-radial movement.