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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Information and Decision Sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
