Using independent component analysis and network DEA to improve bank performance evaluation

Given the importance of accurate performance evaluation for the banking industry, this paper uses data on Taiwanese domestic banks and investigates whether it is useful to construct an integrated performance model in order to address the problems of efficiency-analysis with the aid of an independent component analysis (ICA) and a network slacks-based measure (NSBM). ICA is related to the search for latent information; in it, independent components (ICs) from the observed data and selected statistically unrelated ICs are used as new input, intermediate, and output variables for the NSBM. The NSBM is then used in the investigation of multiple-dimension efficiencies, along with operating performance, in the Taiwanese domestic banking sector. The results show that the proposed ICA-NSBM model provides sufficient information to determine the main sources of inefficiency at the dimensional level and demonstrates excellent significant discriminative capability.