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Performance-Net: A Decision Support System for Reconfiguring a Bank's Branch Network

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  • Ioannou, George
  • Mavri, Maria

Abstract

This paper presents a Decision Support System (DSS) that enables the management of a retail bank to evaluate and reconfigure its branch network. The DSS uses computational methods and knowledge that arises from information about the bank's operational and fixed costs, as well as demographic characteristics from the geographical area where branches are located. The DSS that we call Performance-Net estimates the performance of a branch network and determines the optimum number of branches and the optimum mix of services that each one should provide in order to maximize the bank's revenue- generating measures. Its computational engine is based on a linear programming optimization model and its implementation is developed using the standard MS Excel program. Performance-Net provides efficient solutions, is particularly user-friendly and can reach excellent answers for a wide variety of "what if" parametric scenarios.

Suggested Citation

  • Ioannou, George & Mavri, Maria, 2007. "Performance-Net: A Decision Support System for Reconfiguring a Bank's Branch Network," Omega, Elsevier, vol. 35(2), pages 190-201, April.
    • Handle: RePEc:eee:jomega:v:35:y:2007:i:2:p:190-201
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    References listed on IDEAS

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    1. Boufounou, Paraskevi V., 1995. "Evaluating bank branch location and performance: A case study," European Journal of Operational Research, Elsevier, vol. 87(2), pages 389-402, December.
    2. Schaffnit, Claire & Rosen, Dan & Paradi, Joseph C., 1997. "Best practice analysis of bank branches: An application of DEA in a large Canadian bank," European Journal of Operational Research, Elsevier, vol. 98(2), pages 269-289, April.
    3. 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.
    4. Frances X. Frei & Ravi Kalakota & Andrew J. Leone & Leslie M. Marx, 1999. "Process Variation as a Determinant of Bank Performance: Evidence from the Retail Banking Study," Management Science, INFORMS, vol. 45(9), pages 1210-1220, September.
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    Cited by:

    1. F A F Ferreira & S P Santos & P M M Rodrigues, 2011. "Adding value to bank branch performance evaluation using cognitive maps and MCDA: a case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1320-1333, July.
    2. Ray, Subhash, 2016. "Cost efficiency in an Indian bank branch network: A centralized resource allocation model," Omega, Elsevier, vol. 65(C), pages 69-81.
    3. Wei-Kang Wang & Wen-Min Lu & Yu-Han Wang, 2013. "The relationship between bank performance and intellectual capital in East Asia," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(2), pages 1041-1062, February.
    4. Tang, Lixin & Wang, Gongshu, 2008. "Decision support system for the batching problems of steelmaking and continuous-casting production," Omega, Elsevier, vol. 36(6), pages 976-991, December.
    5. Das, Abhiman & Ray, Subhash C. & Nag, Ashok, 2009. "Labor-use efficiency in Indian banking: A branch-level analysis," Omega, Elsevier, vol. 37(2), pages 411-425, April.
    6. Lawson, Barry R. & Baker, Kenneth R. & Powell, Stephen G. & Foster-Johnson, Lynn, 2009. "A comparison of spreadsheet users with different levels of experience," Omega, Elsevier, vol. 37(3), pages 579-590, June.

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