IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v32y2013icp608-616.html
   My bibliography  Save this article

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

Author

Listed:
  • Lin, Tzu-Yu
  • Chiu, Sheng-Hsiung

Abstract

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.

Suggested Citation

  • Lin, Tzu-Yu & Chiu, Sheng-Hsiung, 2013. "Using independent component analysis and network DEA to improve bank performance evaluation," Economic Modelling, Elsevier, vol. 32(C), pages 608-616.
    • Handle: RePEc:eee:ecmode:v:32:y:2013:i:c:p:608-616
    DOI: 10.1016/j.econmod.2013.03.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999313001077
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econmod.2013.03.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Amado, Carla A.F. & Santos, Sérgio P. & Marques, Pedro M., 2012. "Integrating the Data Envelopment Analysis and the Balanced Scorecard approaches for enhanced performance assessment," Omega, Elsevier, vol. 40(3), pages 390-403.
    2. Lo, Shih-Fang & Lu, Wen-Min, 2009. "An integrated performance evaluation of financial holding companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 198(1), pages 341-350, October.
    3. Rolf Färe & Shawna Grosskopf & Gerald Whittaker, 2014. "Network DEA II," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 307-327, Springer.
    4. Avkiran, Necmi K., 2006. "Developing foreign bank efficiency models for DEA grounded in finance theory," Socio-Economic Planning Sciences, Elsevier, vol. 40(4), pages 275-296, December.
    5. Adler, Nicole & Golany, Boaz, 2001. "Evaluation of deregulated airline networks using data envelopment analysis combined with principal component analysis with an application to Western Europe," European Journal of Operational Research, Elsevier, vol. 132(2), pages 260-273, July.
    6. C Serrano Cinca & C Mar Molinero, 2004. "Selecting DEA specifications and ranking units via PCA," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(5), pages 521-528, May.
    7. Fama, Eugene F., 1980. "Banking in the theory of finance," Journal of Monetary Economics, Elsevier, vol. 6(1), pages 39-57, January.
    8. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    9. Tsutsui, Miki & Goto, Mika, 2009. "A multi-division efficiency evaluation of U.S. electric power companies using a weighted slacks-based measure," Socio-Economic Planning Sciences, Elsevier, vol. 43(3), pages 201-208, September.
    10. Adler, Nicole & Yazhemsky, Ekaterina, 2010. "Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction," European Journal of Operational Research, Elsevier, vol. 202(1), pages 273-284, April.
    11. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    12. Barros, Carlos Pestana & Managi, Shunsuke & Matousek, Roman, 2012. "The technical efficiency of the Japanese banks: Non-radial directional performance measurement with undesirable output," Omega, Elsevier, vol. 40(1), pages 1-8, January.
    13. 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.
    14. Fare, Rolf & Knox Lovell, C. A., 1978. "Measuring the technical efficiency of production," Journal of Economic Theory, Elsevier, vol. 19(1), pages 150-162, October.
    15. F Pedraja-Chaparro & J Salinas-Jiménez & P Smith, 1999. "On the quality of the data envelopment analysis model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(6), pages 636-644, June.
    16. Kao, Ling-Jing & Lu, Chi-Jie & Chiu, Chih-Chou, 2011. "Efficiency measurement using independent component analysis and data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 210(2), pages 310-317, April.
    17. Drake, Leigh & Hall, Maximilian J.B. & Simper, Richard, 2006. "The impact of macroeconomic and regulatory factors on bank efficiency: A non-parametric analysis of Hong Kong's banking system," Journal of Banking & Finance, Elsevier, vol. 30(5), pages 1443-1466, May.
    18. N Adler & B Golany, 2002. "Including principal component weights to improve discrimination in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(9), pages 985-991, September.
    19. Fukuyama, Hirofumi & Matousek, Roman, 2011. "Efficiency of Turkish banking: Two-stage network system. Variable returns to scale model," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(1), pages 75-91, February.
    20. Avkiran, Necmi K., 2009. "Opening the black box of efficiency analysis: An illustration with UAE banks," Omega, Elsevier, vol. 37(4), pages 930-941, August.
    21. Paradi, Joseph C. & Rouatt, Stephen & Zhu, Haiyan, 2011. "Two-stage evaluation of bank branch efficiency using data envelopment analysis," Omega, Elsevier, vol. 39(1), pages 99-109, January.
    22. Yu, Ming-Miin, 2010. "Assessment of airport performance using the SBM-NDEA model," Omega, Elsevier, vol. 38(6), pages 440-452, December.
    23. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    24. Jenkins, Larry & Anderson, Murray, 2003. "A multivariate statistical approach to reducing the number of variables in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 147(1), pages 51-61, May.
    25. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    2. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    3. Akther, Syed & Fukuyama, Hirofumi & Weber, William L., 2013. "Estimating two-stage network Slacks-based inefficiency: An application to Bangladesh banking," Omega, Elsevier, vol. 41(1), pages 88-96.
    4. Fukuyama, Hirofumi & Matousek, Roman, 2018. "Nerlovian revenue inefficiency in a bank production context: Evidence from Shinkin banks," European Journal of Operational Research, Elsevier, vol. 271(1), pages 317-330.
    5. Adler, Nicole & Liebert, Vanessa & Yazhemsky, Ekaterina, 2013. "Benchmarking airports from a managerial perspective," Omega, Elsevier, vol. 41(2), pages 442-458.
    6. Vaneet Bhatia & Sankarshan Basu & Subrata Kumar Mitra & Pradyumna Dash, 2018. "A review of bank efficiency and productivity," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 557-600, November.
    7. Jamal Ouenniche & Skarleth Carrales, 2018. "Assessing efficiency profiles of UK commercial banks: a DEA analysis with regression-based feedback," Annals of Operations Research, Springer, vol. 266(1), pages 551-587, July.
    8. Lozano, Sebastián, 2016. "Slacks-based inefficiency approach for general networks with bad outputs: An application to the banking sector," Omega, Elsevier, vol. 60(C), pages 73-84.
    9. Qiwei Xie & Yuanyuan Li & Lizheng Wang & Chao Liu, 2018. "Improving discrimination in data envelopment analysis without losing information based on Renyi’s entropy," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(4), pages 1053-1068, December.
    10. Edelstein, Barak & Paradi, Joseph C., 2013. "Ensuring units invariant slack selection in radial data envelopment analysis models, and incorporating slacks into an overall efficiency score," Omega, Elsevier, vol. 41(1), pages 31-40.
    11. Huang, Tai-Hsin & Chen, Kuan-Chen & Lin, Chung-I, 2018. "An extension from network DEA to copula-based network SFA: Evidence from the U.S. commercial banks in 2009," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 51-62.
    12. Mohamed Dia & Amirmohsen Golmohammadi & Pawoumodom M. Takouda, 2020. "Relative Efficiency of Canadian Banks: A Three-Stage Network Bootstrap DEA," JRFM, MDPI, vol. 13(4), pages 1-25, April.
    13. Tatiana Bencova & Andrea Bohacikova, 2022. "DEA in Performance Measurement of Two-Stage Processes: Comparative Overview of the Literature," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 5, pages 111-129.
    14. Victor John M. Cantor & Kim Leng Poh, 2020. "Efficiency measurement for general network systems: a slacks-based measure model," Journal of Productivity Analysis, Springer, vol. 54(1), pages 43-57, August.
    15. Anna Łozowicka & Bartłomiej Lach, 2022. "CI-DEA: A Way to Improve the Discriminatory Power of DEA—Using the Example of the Efficiency Assessment of the Digitalization in the Life of the Generation 50+," Sustainability, MDPI, vol. 14(6), pages 1-22, March.
    16. Zha, Yong & Liang, Nannan & Wu, Maoguo & Bian, Yiwen, 2016. "Efficiency evaluation of banks in China: A dynamic two-stage slacks-based measure approach," Omega, Elsevier, vol. 60(C), pages 60-72.
    17. Chiu, Ching-Ren & Chiu, Yung-Ho & Chen, Yu-Chuan & Fang, Chen-Ling, 2016. "Exploring the source of metafrontier inefficiency for various bank types in the two-stage network system with undesirable output," Pacific-Basin Finance Journal, Elsevier, vol. 36(C), pages 1-13.
    18. Varmaz, Armin & Varwig, Andreas & Poddig, Thorsten, 2013. "Centralized resource planning and Yardstick competition," Omega, Elsevier, vol. 41(1), pages 112-118.
    19. Ming-Fu Hsu & Ying-Shao Hsin & Fu-Jiing Shiue, 2022. "Business analytics for corporate risk management and performance improvement," Annals of Operations Research, Springer, vol. 315(2), pages 629-669, August.
    20. Liu, John S. & Lu, Wen-Min, 2010. "DEA and ranking with the network-based approach: a case of R&D performance," Omega, Elsevier, vol. 38(6), pages 453-464, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecmode:v:32:y:2013:i:c:p:608-616. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30411 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.