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Data Envelopment Analysis and Its Use in Banking

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  • Emmanuel Thanassoulis

    (Aston Business School, University of Aston, Birmingham B4 7ET, United Kingdom)

Abstract

Data envelopment analysis (DEA) is a linear-programming-based method for assessing the performance of homogeneous organizational units and is increasingly being used in banking. The unit of assessment is normally the bank branch. Studies are mostly centered on deriving a summary measure of the efficiency of each unit, on estimating targets of performance for the unit, and on identifying role-model units of good operating practice. Additional uses for DEA in banking include the measurement of efficiency in light of resource and output prices, the estimation of operating budgets that are conducive to efficiency, the assessment of financial risk at bank-branch level, and the measurement of the impact of managerial change initiatives on productivity.

Suggested Citation

  • Emmanuel Thanassoulis, 1999. "Data Envelopment Analysis and Its Use in Banking," Interfaces, INFORMS, vol. 29(3), pages 1-13, June.
    • Handle: RePEc:inm:orinte:v:29:y:1999:i:3:p:1-13
    DOI: 10.1287/inte.29.3.1
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    References listed on IDEAS

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    Cited by:

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    3. A. Ghazi & F. Hosseinzadeh Lotfi, 2023. "Marginal rates in DEA using defining hyperplanes of PPS with CRS technology," Operational Research, Springer, vol. 23(1), pages 1-37, March.
    4. Hooy, Chee-Wooi & Chan, Sok-Gee, 2014. "Technological Innovation in Services and the Efficiency of Malaysian Commercial Banks," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 48(2), pages 111-125.
    5. Atici, Kazim Baris & Podinovski, Victor V., 2015. "Using data envelopment analysis for the assessment of technical efficiency of units with different specialisations: An application to agriculture," Omega, Elsevier, vol. 54(C), pages 72-83.
    6. Wagner A. Kamakura & Vikas Mittal & Fernando de Rosa & José Afonso Mazzon, 2002. "Assessing the Service-Profit Chain," Marketing Science, INFORMS, vol. 21(3), pages 294-317, February.
    7. Eskelinen, Juha & Halme, Merja & Kallio, Markku, 2014. "Bank branch sales evaluation using extended value efficiency analysis," European Journal of Operational Research, Elsevier, vol. 232(3), pages 654-663.
    8. Hokey Min & Hyesung Min & Seong Jong Joo, 2007. "A data envelopment analysis on assessing the competitiveness of Korean hotels," The Service Industries Journal, Taylor & Francis Journals, vol. 29(3), pages 367-385, November.
    9. Sepideh Kaffash & Marianna Marra, 2017. "Data envelopment analysis in financial services: a citations network analysis of banks, insurance companies and money market funds," Annals of Operations Research, Springer, vol. 253(1), pages 307-344, June.
    10. Mariusz Pyra & Mieczyslaw Adamowicz, 2021. "Assessment of the Sector of Public Vocational Universities in Poland from the Point of View of their Efficiency," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 21-43.
    11. Anna Domagała, 2007. "Data Envelopment Analysis – a method for measuring the relative technical efficiency," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 17(3-4), pages 21-34.
    12. Saleh, Ali Salman & Moradi-Motlagh, Amir & Zeitun, Rami, 2020. "What are the drivers of inefficiency in the Gulf Cooperation Council banking industry? A comparison between conventional and Islamic banks," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    13. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "A survey of DEA applications," Omega, Elsevier, vol. 41(5), pages 893-902.
    14. Cabello, Julia García, 2019. "A decision model for bank branch site selection: Define branch success and do not deviate," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    15. Akber Aman Shah & Desheng Wu & Vladmir Korotkov, 2019. "Are Sustainable Banks Efficient and Productive? A Data Envelopment Analysis and the Malmquist Productivity Index Analysis," Sustainability, MDPI, vol. 11(8), pages 1-19, April.
    16. Shuji Yao & Zhongwei Han & Dan Luo, 2010. "Performance of the Chinese Insurance Industry under Economic Reforms," Books, Edward Elgar Publishing, number 12788.
    17. Wu, Yueh-Cheng & Wei Kiong Ting, Irene & Lu, Wen-Min & Nourani, Mohammad & Kweh, Qian Long, 2016. "The impact of earnings management on the performance of ASEAN banks," Economic Modelling, Elsevier, vol. 53(C), pages 156-165.
    18. Anna Domagała, 2007. "Evaluating the efficiency of decision making units using panel Data Envelopment Analysis – empirical example for Polish commercial banks," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 17(3-4), pages 35-56.
    19. González Bravo, M. Isabel & Mariaca Daza, René, 2010. "Fracaso de bancos comerciales. Un estudio de eficiencia y productividad," Revista Latinoamericana de Desarrollo Economico, Carrera de Economía de la Universidad Católica Boliviana (UCB) "San Pablo", issue 13, pages 137-162.
    20. Thomas Bournaris & George Vlontzos & Christina Moulogianni, 2019. "Efficiency of Vegetables Produced in Glasshouses: The Impact of Data Envelopment Analysis (DEA) in Land Management Decision Making," Land, MDPI, vol. 8(1), pages 1-11, January.
    21. Vlontzos, G. & Pardalos, P.M., 2017. "Assess and prognosticate green house gas emissions from agricultural production of EU countries, by implementing, DEA Window analysis and artificial neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 155-162.
    22. Amir Moradi-Motlagh & Ali Salman Saleh, 2014. "Re-Examining the Technical Efficiency of Australian Banks: A Bootstrap DEA Approach," Australian Economic Papers, Wiley Blackwell, vol. 53(1-2), pages 112-128, June.

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