Efficiency improvement from multiple perspectives: An application to Japanese banking industry

Omega (United Kingdom)

Volumn 41, Issue 3, 2013, Pages 501-509

  Yang, Xiaopeng ^a   Morita, Hiroshi ^a  

^a OSAKA UNIVERSITY   (Japan)

Author keywords

Data envelopment analysis (DEA); Multiple perspectives; Nash bargaining game (NBG)

Indexed keywords

DECISION MAKING; EFFICIENCY; GAME THEORY; ONLINE SYSTEMS; PARETO PRINCIPLE;

'CURRENT; BANKING INDUSTRY; BANKING SYSTEMS; BARGAINING GAME THEORIES; DATA ENVELOPMENT ANALYSE; EFFICIENCY IMPROVEMENT; INPUT-OUTPUT; MULTIPLE PERSPECTIVES; NASH BARGAINING GAME;

DATA ENVELOPMENT ANALYSIS;

EID: 84866654455     PISSN: 03050483     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.omega.2012.06.007     Document Type: Article

References (31)

1. Farrell M.J. The measurement of productive efficiency. Journal of the Royal Statistical Society Series A 1957, 120:253-290.
2. Charnes A., Cooper W.W., Rhodes E. Measuring the efficiency of decision making units. European Journal of Operational Research 1978, 2:429-444.
3. Avkiran N.K., Morita H. Benchmarking firm performance from a multiple-stakeholder perspective with an application to Chinese banking. OMEGA, The International Journal of Management Science 2010, 38:501-508.
4. Cooper WW, Seiford LM, Tone K. Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software. 2 ed. New York; 2007.
5. Nash J.F. The Bargaining problem. Econometrica 1950, 18:155-162.
6. Nash J.F. Two-person cooperative games. Econometrica 1953, 21:128-140.
7. Malhotra R., Malhotra D.K., Lafond C.A. Analysing financial services industry using data envelopment analysis. International Journal of Applied Management Science 2009, 1:217-246.
8. Sufian F. Evolution in the efficiency of the Indonesian banking sector: a DEA approach. International Journal of Applied Management Science 2010, 2:388-414.
9. Halkos G.E., Salamouris D.S. Efficiency measurement of the Greek commercial banks with the use of financial ratios: a data envelopment analysis approach. Management Accounting Research 2004, 15:201-204.
10. Paradi C.J., Schaffnit C. Commercial branch performance evaluation and results communication in a Canadian bank-a DEA application. European Journal of Operational Research 2004, 156:719-735.
11. Mavi R.K., Makui A., Fazli S., Alinezhad A. A forecasting method in data envelopment analysis with group decision making. International Journal of Applied Management Science 2010, 2:152-168.
12. Bergendahl G., Lindblom T. Evaluating the performance of Swedish savings banks according to service efficiency. European Journal of Operational Research 2008, 185:1663-1673.
13. Cook W.D., Zhu J. Modeling performance measurement: applications and implementation issues in DEA 2005, Springer, New York.
14. Avkiran N.K. Association of DEA super-efficiency estimates with financial ratios: investigating the case for Chinese banks. OMEGA, The International Journal of Management Science 2011, 39:323-334.
15. Paradi J.C., Rouatt S., Zhu H. Two-stage evaluation of bank branch efficiency using data envelopment analysis. OMEGA, The International Journal of Management Science 2011, 39:99-109.
16. Premachandra I.M., Chen Y., Watson J. DEA as a tool for predicting corporate failure and success: a case of bankruptcy assessment. OMEGA, The International Journal of Management Science 2011, 39:620-626.
17. Juo J.-C., Fu T.-T., Yu M.-M. Non-oriented slack-based decompositions of profit change with an application to Taiwanese banking. OMEGA, The International Journal of Management Science 2012, 40:550-561.
18. Sarrico S.C., Hogan S.M., Dyson R.G., Athanassopoulos A.D. Data envelopment analysis and university selection. Journal of the Operational Research Society 1997, 48:1163-1177.
19. Dyson R.G., Allen R., Camanho A.S., Podinovski V.V., Sarrico C.S., Shale E.A. Pitfalls and protocols in DEA. European Journal of Operational Research 2001, 132:245-259.
20. Scheel H. Undesirable outputs in efficiency valuations. European Journal of Operational Research 2001, 132:400-410.
21. Lewis H.F., Sexton T.R. Data envelopment analysis with reverse inputs and outputs. Journal of Productivity Analysis 2004, 21:113-132.
22. Zhu J. Quantitative models for performance evaluation and benchmarking: data envelopment analysis with spread sheets 2009, Springer, New York. 2nd ed.
23. Bougnol M.-L., Dula J.H., Retzlaff-Roberts D., Womer N.K. Non-parametric frontier analysis with multiple constituencies. Journal of the Operational Research Society 2005, 56:252-266.
24. Garcia-Cestona M., Surroca J. Multiple goals and ownership structure: effects on the performance of Spanish savings banks. European Journal of Operational Research 2008, 187:582-599.
25. Du J., Liang L., Chen Y., Cook W.D., Zhu J. A bargaining game model for measuring performance of two-stage network structures. European Journal of Operational Research 2011, 210:390-397.
26. Liang L., Cook W.D., Zhu J. DEA models for two-stage processes: game approach and efficiency decomposition. Naval Research Logistics 2008, 55:643-653.
27. Avkiran N.K., Morita H. Predicting Japanese bank stock performance with a composite relative efficiency metric: a new investment tool. Pacific-Basin Finance Journal 2009, 18:254-271.
28. Modigliani F., Miller M. The cost of capital, corporation finance and the theory of investment. American Economic Review 1958, 48:261-297.
29. Miller M.H. Debt and taxes. The Journal of Finance 1977, 32:261-275.
30. Hutchison D.E., Cox R.A.K. The causal relationship between bank capital and profitability. Annals of Financial Economics 2006, 3:40-54.
31. Nissim D., Penman S.H. Financial statement snalysis of leverage and how it informs about profitability and price-to-book ratios. Review of Accounting Studies 2003, 8:531-560.