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Evaluating Taiwanese Bank Efficiency Using the Two-Stage Range DEA Model

Author

Listed:
  • Wei-Hsin Kong

    (Agricultural Policy Research Center, Agricultural Technology Research Institute, 4F., No 14, Wenzhou St., Da’an Dist., Taipei 106, Taiwan)

  • Tsu-Tan Fu

    (Department of Economics, Soochow University, 56 Kueiyang Street, Section 1, Taipei 100, Taiwan)

  • Ming-Miin Yu

    (Department of Transportation Science, National Taiwan Ocean University, No. 2 Pei-Ning Road, Keelung 20224, Taiwan)

Abstract

This paper develops a range directional distance data envelopment analysis (DEA) model to simultaneously deal with the problems of negative data and undesirable outputs in the study of performance measurement with two-stage DEA. We report on the development of this model to handle both positive and negative data in a DEA framework and accommodate the problem of undesirable intermediate outputs in the first stage of operational processes. Unlike previous two-stage DEA models we allow for a nonuniform abatement factor imposing on stage 1’ production technology. Such a model is then applied to evaluate Taiwanese bank efficiencies both at the operational stage and profitability stage in banking activities based on a data set consisting of 35 domestic banks in Taiwan in the period 2007. The results indicate that, by the range directional two-stage data envelopment analysis model, the operational efficiency was smaller than the profitability efficiency. Many banks generated too many performing loans in which independent banks should reduce more performing loans than financial holding company subsidiary banks. Both the ratio of investments to loans and the ratio of nonperforming loans to performing loans did not have significant contributions to the efficiency. This paper is able to provide information for bank operators and researchers on the managerial and strategic implications of how negative data and undesirable outputs affect efficiency and how to measure efficiency appropriately.

Suggested Citation

  • Wei-Hsin Kong & Tsu-Tan Fu & Ming-Miin Yu, 2017. "Evaluating Taiwanese Bank Efficiency Using the Two-Stage Range DEA Model," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 1043-1068, July.
  • Handle: RePEc:wsi:ijitdm:v:16:y:2017:i:04:n:s0219622017500031
    DOI: 10.1142/S0219622017500031
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    References listed on IDEAS

    as
    1. Matthews, Kent, 2013. "Risk management and managerial efficiency in Chinese banks: A network DEA framework," Omega, Elsevier, vol. 41(2), pages 207-215.
    2. Chien Wang & Ram Gopal & Stanley Zionts, 1997. "Use of Data Envelopment Analysis in assessing Information Technology impact on firm performance," Annals of Operations Research, Springer, vol. 73(0), pages 191-213, October.
    3. Zhongsheng Hua & Yiwen Bian, 2008. "Performance measurement for network DEA with undesirable factors," International Journal of Management and Decision Making, Inderscience Enterprises Ltd, vol. 9(2), pages 141-153.
    4. Sherman, H. David & Gold, Franklin, 1985. "Bank branch operating efficiency : Evaluation with Data Envelopment Analysis," Journal of Banking & Finance, Elsevier, vol. 9(2), pages 297-315, June.
    5. Holod, Dmytro & Lewis, Herbert F., 2011. "Resolving the deposit dilemma: A new DEA bank efficiency model," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2801-2810, November.
    6. Fukuyama, Hirofumi & Weber, William L., 2010. "A slacks-based inefficiency measure for a two-stage system with bad outputs," Omega, Elsevier, vol. 38(5), pages 398-409, October.
    7. Berger, Allen N. & Humphrey, David B., 1997. "Efficiency of financial institutions: International survey and directions for future research," European Journal of Operational Research, Elsevier, vol. 98(2), pages 175-212, April.
    8. Portela, Maria C.A.S. & Thanassoulis, Emmanuel, 2010. "Malmquist-type indices in the presence of negative data: An application to bank branches," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1472-1483, July.
    9. Rolf Färe & Shawna Grosskopf, 2003. "Nonparametric Productivity Analysis with Undesirable Outputs: Comment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 1070-1074.
    10. M C A Silva Portela & E Thanassoulis & G Simpson, 2004. "Negative data in DEA: a directional distance approach applied to bank branches," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1111-1121, October.
    11. Oral, Muhittin & Yolalan, Reha, 1990. "An empirical study on measuring operating efficiency and profitability of bank branches," European Journal of Operational Research, Elsevier, vol. 46(3), pages 282-294, June.
    12. Chen, Yao & Cook, Wade D. & Li, Ning & Zhu, Joe, 2009. "Additive efficiency decomposition in two-stage DEA," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1170-1176, August.
    13. Portela, Maria Conceicao A. Silva & Thanassoulis, Emmanuel, 2007. "Comparative efficiency analysis of Portuguese bank branches," European Journal of Operational Research, Elsevier, vol. 177(2), pages 1275-1288, March.
    14. Tser-Yieth Chen & TSER-LIEN YEH, 2000. "A Measurement of Bank Efficiency, Ownership and Productivity Changes in Taiwan," The Service Industries Journal, Taylor & Francis Journals, vol. 20(1), pages 95-109, January.
    15. Sahoo, Biresh K. & Luptacik, Mikulas & Mahlberg, Bernhard, 2011. "Alternative measures of environmental technology structure in DEA: An application," European Journal of Operational Research, Elsevier, vol. 215(3), pages 750-762, December.
    16. Liang Liang & Feng Yang & Wade Cook & Joe Zhu, 2006. "DEA models for supply chain efficiency evaluation," Annals of Operations Research, Springer, vol. 145(1), pages 35-49, July.
    17. Kou, Gang & Ergu, Daji & Shang, Jennifer, 2014. "Enhancing data consistency in decision matrix: Adapting Hadamard model to mitigate judgment contradiction," European Journal of Operational Research, Elsevier, vol. 236(1), pages 261-271.
    18. Leightner, Jonathan E. & Lovell, C. A. Knox, 1998. "The Impact of Financial Liberalization on the Performance of Thai Banks," Journal of Economics and Business, Elsevier, vol. 50(2), pages 115-131, March.
    19. Lawrence M. Seiford & Joe Zhu, 1999. "Profitability and Marketability of the Top 55 U.S. Commercial Banks," Management Science, INFORMS, vol. 45(9), pages 1270-1288, September.
    20. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    21. Kou, Gang & Lin, Changsheng, 2014. "A cosine maximization method for the priority vector derivation in AHP," European Journal of Operational Research, Elsevier, vol. 235(1), pages 225-232.
    22. Kao, Chiang & Hwang, Shiuh-Nan, 2008. "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 185(1), pages 418-429, February.
    23. Luo, Xueming, 2003. "Evaluating the profitability and marketability efficiency of large banks: An application of data envelopment analysis," Journal of Business Research, Elsevier, vol. 56(8), pages 627-635, August.
    24. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    25. Lewis, Herbert F. & Mallikarjun, Sreekanth & Sexton, Thomas R., 2013. "Unoriented two-stage DEA: The case of the oscillating intermediate products," European Journal of Operational Research, Elsevier, vol. 229(2), pages 529-539.
    26. Wang, Ke & Huang, Wei & Wu, Jie & Liu, Ying-Nan, 2014. "Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA," Omega, Elsevier, vol. 44(C), pages 5-20.
    27. Seiford, Lawrence M. & Zhu, Joe, 2005. "A response to comments on modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 161(2), pages 579-581, March.
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    2. Zhou, Xiaoyang & Xu, Zhongwen & Chai, Jian & Yao, Liming & Wang, Shouyang & Lev, Benjamin, 2019. "Efficiency evaluation for banking systems under uncertainty: A multi-period three-stage DEA model," Omega, Elsevier, vol. 85(C), pages 68-82.
    3. Mohammad Amirkhan & Hosein Didehkhani & Kaveh Khalili-Damghani & Ashkan Hafezalkotob, 2018. "Measuring Performance of a Three-Stage Network Structure Using Data Envelopment Analysis and Nash Bargaining Game: A Supply Chain Application," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(05), pages 1429-1467, September.

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