Abstract
The paper proposes an iso-analysis framework for performance evaluation of decision-making units for use in two basic set-ups. First, for two criterial dimensions of performance applied simultaneously, it is shown how groups of decision-making units formed on the principle of comparability in terms of their performance can be identified and graphically displayed in an ‘iso-performance chart’. In such iso-analysis, individual decision-making units are separated into iso-performance zones according to their bidimensional performance captured by means of an artificially constructed performance indicator that may be easily accommodated so as to reflect possibly differing importance of the considered performance dimensions. Second, it is explained how typically utilized non-orientated and non-radial measures of technical efficiency can be broken down into two sources associated with both sides of production process (i.e. an input efficiency component and an output efficiency component) and further investigated graphically in the format of an ‘input–output efficiency chart’. The elements of the proposed methodology are demonstrated in a case study of a Slovak commercial bank with an extensive retail branch network.
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Notes
The construction of a comprehensive indicator considered here is greatly distinct from the construction of a comprehensive indicator originally proposed by Lovell (1995) and later made popular in assessments of macroeconomic policy, social inclusion or human development (see e.g. Cherchye et al. 2008).
One referee noted that the selection of inputs and outputs as declared here is questionable and unusual for a typical task of bank technical efficiency measurement. Indeed, there are theoretical discussions concerning the economic rationale of banks and the essence of their undertaking, and these discussions also pass on to their branches. In this respect, the existing approaches more or less reserve for the commercial bank either the role of a financial intermediary or the function of a producer of banking services, and this production role is more suited to bank branches (see Ahn and Le 2014, p. 15, or Paradi and Zhu 2013, p. 64). Under the production model, the bank branch is treated as a service factory that transmutes labour and physical capital into depository and creditory services. Each study tends to customize the production model to the particular conditions of technical efficiency assessment as is also clear from Table A1 in Paradi and Zhu (2013), and here the desideratum of controllability at the branch level is obeyed. A most similar configuration of inputs and outputs can be found e.g. in Parkan (1994), Hartman et al. (2001), Porembski et al. (2005), Portela and Thanassoulis (2005) and Camanho and Dyson (2008). The cited studies view labour force (possibly with other minor inputs) as an input and treat (monetary) volume of rendered banking services as an output (possibly with other minor outputs).
References
Agrell PJ, Bogetoft P, Tind J (2005) DEA and dynamic yardstick competition in Scandinavian electricity distribution. J Prod Anal 23(2):173–201
Ahn H, Le MH (2014) An insight into the specification of the input-output set for DEA-based bank efficiency measurement. Manag Rev Q 64(1):3–37
Andersen P, Petersen NC (1993) A procedure for ranking efficient units in data envelopment analysis. Manag Sci 39(10):1261–1264
Bolori F, Pourmahmoud J (2016) A modified SBM-NDEA approach for the efficiency measurement in branches. In Press, Oper Res Int J
Boussofiane A, Dyson RG, Thanassoulis E (1991) Applied data envelopment analysis. Eur J Oper Res 52(1):1–15
Camanho AS, Dyson RG (1999) Efficiency, size, benchmarks and targets for bank branches: an application of data envelopment analysis. J Oper Res Soc 50(9):903–915
Camanho AS, Dyson RG (2008) A generalization of the Farrell cost efficiency measure applicable to non-fully competitive settings. Omega Int J Manag Sci 36(1):147–162
Cherchye L (2001) Using data envelopment analysis to assess macroeconomic policy performance. Appl Econ 33(3):407–416
Cherchye L, Moesen W, van Puyenbroeck T (2004) Legitimately diverse, yet comparable: on synthesizing social inclusion performance in the EU. J Common Mark Stud 42(5):919–955
Cherchye L, Moesen W, Rogge N et al (2008) Creating composite indicators with DEA and robustness analysis: the case of the Technology Achievement Index. J Oper Res Soc 59(2):239–251
Cooper WW, Park KS, Pastor JT (1999) RAM: a range adjusted measure of inefficiency of use with additive models and relations to other models and measures in DEA. J Prod Anal 11(1):5–42
Färe R, Grosskopf S, Lovell CAK (1985) The measurement of efficiency of production. Kluwer, Boston
Fox KJ, Hill RJ, Diewert WE (2004) Identifying outliers in multi-output models. J Prod Anal 22(1):76–94
Giokas D (2008) Assessing the efficiency in operations of a large Greek bank branch network adopting different economic behaviours. Econ Model 25(3):559–574
Grönroos C, Ojasalo K (2004) Service productivity—towards a conceptualization of the transformation of inputs into economic results in services. J Bus Res 57(4):414–423
Hartman TE, Storbeck JE, Byrnes P (2001) Allocative efficiency in branch banking. Eur J Oper Res 134(2):232–242
Kumbhakar SC, Lovell CAK (2000) Stochastic frontier analysis. Cambridge University Press, Cambridge
Lovell CAK (1995) Measuring the macroeconomic performance of the Taiwanesse economy. Int J Prod Econ 39(1–2):165–178
Oh D-H, Suh D (2013) Nonparaeff: nonparametric methods for measuring efficiency and productivity. R package version 0.5-8: https://cran.r-project.org/web/packages/nonparaeff
Paradi JC, Zhu H (2013) A survey on bank branch efficiency and performance research with data envelopment analysis. Omega Int J Manag Sci 41(1):61–79
Parkan C (1994) Operational competitivness ratings of production units. Man Decis Econ 15(3):201–221
Porembski M, Breitenstein K, Alpar P (2005) Visualizing efficiency and reference relations in data envelopent analysis with an application to the branches of a German bank. J Prod Anal 23(2):203–221
Portela MCAS, Thanassoulis E (2005) Profitability of a sample of Portutuese bank branches and its decomposition into technical and allocative component. Eur J Oper Res 162(3):1275–1288
Portela MCAS, Thanassoulis E (2007) Comparative efficiency analysis of Portuguese bank branches. Eur J Oper Res 177(2):1275–1288
R Core Team (2013) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. http://www.r-project.org
Ševčovič D, Halická M, Brunovský P (2001) DEA analysis for a large structured bank branch network. Cent Eur J Oper Res 9(4):329–342
Simar L (2003) Detecting outliers in frontier models: a simple approach. J Prod Anal 20(3):391–424
Thanassoulis E (1995) Assessing police forces in England and Wales using data envelopment analysis. Eur J Oper Res 87(3):641–657
Tone K (2001) A slacks-based measure of efficiency in data envelopment analysis. Eur J Oper Res 130(3):498–509
Wilson PW (1993) Detecting outliers in deterministic nonparametric frontier models with multiple outputs. J Bus Econ Stat 11(3):319–323
Yang C, Liu H-M (2012) Managerial efficiency in Taiwan bank branches: a network DEA. Econ Mod 29(2):450–461
Youn J-W, Park K (2014) Development of assessment model for research efficiency of universities. In: Emrouznejad A, Cabanda E (eds) Managing service productivity. Springer, Berlin, pp 19–36
Acknowledgments
The authors owe their gratitude to the managers of a Slovak commercial bank who provided the data on its branches for research purposes and who wish that the name of the bank remain in anonymity. The paper originated in fulfilment of the obligations concerning the grant scheme VEGA No. 1/0757/15 Augmentation of the theoretical construct of the SCP paradigm and of the efficient structure hypothesis in banking and insurance by the aspect of risk and their empirical validation in the conditions of the Slovak Republic.
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Bod′a, M., Zimková, E. Iso-analysis for knowing the sources of technical efficiency and performance. Oper Res Int J 18, 421–449 (2018). https://doi.org/10.1007/s12351-016-0271-8
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DOI: https://doi.org/10.1007/s12351-016-0271-8