Input/output indicator selection for DEA efficiency evaluation: An empirical study of Chinese commercial banks
One of the interesting research subjects in DEA is to choose appropriate input and output indicators. In the process, one may encounter many problems, such as the selection tools, correlation analysis, and the classification of input versus output status. In this paper, we propose a new method for choosing DEA variables. Unlike previous research, it is based on the conception of cash value added (CVA), and can make a selection according to the statistic results. This new method has some advantages: first, it is more objective, avoiding the influence of subjective factors on the subsequent calculation; second and most important is that it provides managers and researchers with measurement variables and exact classifications of these factors; third, all variables under discussion come from financial statements which are easily available. This variable selection method has been applied to 14 Chinese commercial banks, and both regression and statistic test results are satisfactory. (C) 2011 Elsevier Ltd. All rights reserved.
classification cash value added variables selection regression data envelopment analysis (dea)