Measuring efficiency in Chinese commercial banks using a DEA model with undesirable output

Abstract

Data envelopment analysis (DEA) approaches are widely utilised to measure the performance of commercial banks with considering multiple input and output variables. In order to attain accurate efficiency score, undesirable outputs such as bad loan are taken into consideration when evaluating the efficiency of commercial banks. However, the same problem arises within all the existing undesirable DEA approaches which have been utilised to measure the performance of commercial banks: the commercial banks can get higher efficiency scores if undesirable outputs are considered. This paper constructs a new undesirable DEA model for overcoming this dilemma. We also applied the new proposed models to investigate 15 main Chinese commercial banks from the year 2007 to 2010 for illustrating the use and advantages of it.