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Bank branch efficiency evaluation by means of least absolute deviations and DEA

Listed author(s):
  • Ioannis E. Tsolas
Registered author(s):

    Purpose - The purpose of this paper is to assess the efficiency of individual branches of a large Greek bank through the application of both goal programming (GP) and data envelopment analysis (DEA). Design/methodology/approach - The paper employs a particular least absolute deviations (LAD) technique (i.e. a special case of GP/constrained regression) and DEA as two performance measurement methods. The performance evaluation by means of GP is assessed utilizing two alternative conceptual (parametric functional form-loglinear) models: one focusing on transaction and one on production efficiency. The DEA assessment using the transaction efficiency model is performed under the specifications of constant or variable returns to scale. Findings - The two methods do provide confirmation of each other's findings. The results support the main claim that there is a strong relationship between the rankings obtained by GP and DEA. Moreover, the GP results indicate that there is a relationship between bank branch transaction and production efficiency. Practical implications - The results may be of interest to stakeholder groups such as bank shareholders, managers, and regulatory authorities. Originality/value - The paper is believed to be the first to examine the application of GP and DEA to measure the efficient use of resources of bank branches in Greece in terms of location (urban-rural).

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    File URL: http://www.emeraldinsight.com/10.1108/03074351211239397?utm_campaign=RePEc&WT.mc_id=RePEc
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    Article provided by Emerald Group Publishing in its journal Managerial Finance.

    Volume (Year): 38 (2012)
    Issue (Month): 8 (June)
    Pages: 768-785

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    Handle: RePEc:eme:mfipps:v:38:y:2012:i:8:p:768-785
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    1. Sueyoshi, Toshiyuki, 1999. "DEA-discriminant analysis in the view of goal programming," European Journal of Operational Research, Elsevier, vol. 115(3), pages 564-582, June.
    2. Cook, Wade D. & Bala, Kamel, 2007. "Performance measurement and classification data in DEA: Input-oriented model," Omega, Elsevier, vol. 35(1), pages 39-52, February.
    3. Charnes, Abraham & Gallegos, Armando & Li, Hongyu, 1996. "Robustly efficient parametric frontiers via Multiplicative DEA for domestic and international operations of the Latin American airline industry," European Journal of Operational Research, Elsevier, vol. 88(3), pages 525-536, February.
    4. Charnes, A. & Cooper, W. W. & Sueyoshi, T., 1986. "Least squares/ridge regression and goal programming/constrained regression alternatives," European Journal of Operational Research, Elsevier, vol. 27(2), pages 146-157, October.
    5. 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.
    6. A. Charnes & W. W. Cooper & R. O. Ferguson, 1955. "Optimal Estimation of Executive Compensation by Linear Programming," Management Science, INFORMS, vol. 1(2), pages 138-151, January.
    7. Sueyoshi, Toshiyuki, 1994. "Stochastic frontier production analysis: Measuring performance of public telecommunications in 24 OECD countries," European Journal of Operational Research, Elsevier, vol. 74(3), pages 466-478, May.
    8. Cook, Wade D. & Hababou, Moez, 2001. "Sales performance measurement in bank branches," Omega, Elsevier, vol. 29(4), pages 299-307, August.
    9. 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.
    10. 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.
    11. Giokas, D. I. & Pentzaropoulos, G. C., 2000. "Efficient storage allocation for processing in backlog-controlled queueing networks using multicriteria techniques," European Journal of Operational Research, Elsevier, vol. 124(3), pages 539-549, August.
    12. 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.
    13. Giokas, Dimitris I., 2008. "Assessing the efficiency in operations of a large Greek bank branch network adopting different economic behaviors," Economic Modelling, Elsevier, vol. 25(3), pages 559-574, May.
    14. Houshmand Ziari & Azzeddine Azzam, 1999. "Parametrizing nonparametric translog models: A goal programming/constrained regression study of U.S. manufacturing," Empirical Economics, Springer, vol. 24(2), pages 331-339.
    15. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    16. Post, Thierry & Spronk, Jaap, 1999. "Performance benchmarking using interactive data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 115(3), pages 472-487, June.
    17. Giokas, DI, 1991. "Bank branch operating efficiency: A comparative application of DEA and the loglinear model," Omega, Elsevier, vol. 19(6), pages 549-557.
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