caa a22 4500 605470030 CHVBK 20210128100325.0 cr unu---uuuuu 210128e20150401xx s 000 0 eng 10.1007/s00500-014-1413-7 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1413-7 A decision rule-based soft computing model for supporting financial performance improvement of the banking industry [Elektronische Daten] [Kao-Yi Shen, Gwo-Hshiung Tzeng] This study attempts to diagnose the financial performance improvement of commercial banks by integrating suitable soft computing methods. The diagnosis of financial performance improvement comprises of three parts: prediction, selection and improvement. The performance prediction problem involves many criteria, and the complexity among the interrelated variables impedes researchers to discover patterns by conventional statistical methods. Therefore, this study adopts a dominance-based rough set approach to solve the prediction problem, and the core attributes in the obtained decision rules are further processed by an integrated multiple criteria decision-making method to make selection and to devise improvement plans. By using VIKOR method and the influential weights of DANP, decision maker may plan to reduce gap of each criterion for achieving aspired level. The retrieved attributes (i.e., criteria) are used to collect the knowledge of domain experts for selection and improvement. This study uses the data (from 2008 to 2011) from the central bank of Taiwan for obtaining decision rules and forming an evaluation model; furthermore, the data of five commercial banks in 2011 and 2012 are chosen to evaluate and improve the real cases. In the result, we found the top-ranking bank outperformed the other four banks, and its performance gaps for improvements were also identified, which indicates the effectiveness of the proposed model. Springer-Verlag Berlin Heidelberg, 2014 Rough set approach (RSA) nationallicence Dominance-based rough set approach (DRSA) nationallicence DEMATEL-based ANP (DANP) nationallicence VIKOR nationallicence Multiple criteria decision making (MCDM) nationallicence Shen Kao-Yi Department of Banking and Finance, Chinese Culture University (SCE), Taipei, Taiwan aut Tzeng Gwo-Hshiung Graduate Institute of Urban Planning, College of Public Affairs, National Taipei University, 151, University Rd., San Shia District, 23741, New Taipei, Taiwan aut Soft Computing Springer Berlin Heidelberg 19/4(2015-04-01), 859-874 1432-7643 19:4<859 2015 19 500 https://doi.org/10.1007/s00500-014-1413-7 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1413-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Shen Kao-Yi Department of Banking and Finance, Chinese Culture University (SCE), Taipei, Taiwan aut NATIONALLICENCE 700 1- Tzeng Gwo-Hshiung Graduate Institute of Urban Planning, College of Public Affairs, National Taipei University, 151, University Rd., San Shia District, 23741, New Taipei, Taiwan aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/4(2015-04-01), 859-874 1432-7643 19:4<859 2015 19 500