- Volume 14 Issue 4
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A Hybrid Approach Based on Multi-Criteria Satisfaction Analysis (MUSA) and a Network Data Envelopment Analysis (NDEA) to Evaluate Efficiency of Customer Services in Bank Branches
- Received : 2015.07.11
- Accepted : 2015.12.06
- Published : 2015.12.30
A hybrid procedure based on multi-Criteria Satisfaction Analysis (MUSA) and a Network Data Envelopment Analysis (NDEA) is proposed to evaluate the relative efficiency of customer services in bank branches. First, a three-stage process including sub-processes such as customer expectations, customer satisfaction, and customer loyalty, is defined to model the banking customer services. Then, fulfillment of customer expectations, customer loyalty level, and the customer satisfaction degree are measured and quantified through a multi-dimensional questionnaire based on customers' perceptions analysis and MUSA method, respectively. The customer services scores and the other criteria such as mean of employee evaluation score, operation costs, assets, deposits, loans, number of accounts are considered in network three-stage DEA model. The proposed NDEA model is formed based on multipliers perspective, output-oriented, and constant return to scale assumptions. The proposed NDEA model quantifies and assesses the total efficiency of main process and assigns the efficiency to customer expectations, customer satisfactions, and customer loyalties sub-processes in bank branches. The whole procedure is applied on 30 bank branches in IRAN. The proposed approach can be used in other organizations such as airports, airline agencies, urban transportation systems, railway organizations, chain stores, chain restaurants, public libraries, and entertainment centers.
Network Data Envelopment Analysis;Multi-Criteria Satisfaction Analysis;Performance Measurement;Customer Satisfaction Analysis;Bank Performance
- Abtahi, A. R. and Khalili-Damghani, K. (2011), Fuzzy data envelopment analysis for measuring agility performance of supply chains, International Journal of Modeling in Operations Management, 1(3), 263-288. https://doi.org/10.1504/IJMOM.2011.039530
- Banker, R. D., Charnes, A., and Cooper, W. W. (1984), Some models for the estimation of technical and scale inefficiencies in Data Envelopment Analysis, Management Science, 30, 1078-1092. https://doi.org/10.1287/mnsc.30.9.1078
- Charnes, A., Cooper, W. W., and Rhodes, E. (1978), Measuring the Efficiency of Decision Making Units, European Journal of Operational Research, 2(6), 429-444. https://doi.org/10.1016/0377-2217(78)90138-8
- Esmaeili, A. and Horri, M. (2014), Efficiency evaluation of customer satisfaction index in e-banking using the fuzzy data envelopment analysis, Management Science Letters, 4(1), 71-86.
- Fare, R. and Grosskopf, S. (2000), Network DEA, Socio-Economic Planning Sciences, 34 (1), 35-49. https://doi.org/10.1016/S0038-0121(99)00012-9
- Frei, F. X. and Harker, P. T. (1999), Measuring the Efficiency of Service Delivery Processes: an Application to Retail Banking, Journal of Service Research, 1(4), 300-312. https://doi.org/10.1177/109467059914002
- Gerson, R. F. (1993), Measuring Customer Satisfaction: A guide to Managing Quality Service, Menlo Park: Crisp Publications.
- Grigoroudis, E. and Siskos, Y. (2010), Customer Satisfaction Evaluation: Methods for Measuring and Implementing Service Quality, New York: Springer.
- Grigoroudis, E., Tsitsiridi, E., and Zopounidis, C. (2013), Linking Customer Satisfaction, Employee Appraisal, and Business Performance: an Evaluation Methodology in the Banking Sector, Annals of Operations Research, 205(1), 5-27. https://doi.org/10.1007/s10479-012-1206-2
- Holod, D. and Lewis, H. F. (2011), Resolving the Deposit Dilemma: a New DEA Bank Efficiency Model, Journal of Banking and Finance, 35(11), 2801-2810. https://doi.org/10.1016/j.jbankfin.2011.03.007
- Khalili-Damghani, K., Taghavifard, M., Olfat, L., and Feizi, K. (2011), A hybrid approach based on fuzzy DEA and simulation to measure the efficiency of agility in supply chain: real case of dairy industry, International Journal of Management Science and Engineering Management, 6, 163-172.
- Khalili-Damghani, K. and Taghavifard, M. (2012), A fuzzy two-stage DEA approach for performance measurement: real case of agility performance in dairy supply chains, International Journal of Applied Decision Sciences, 5(4), 293-317. https://doi.org/10.1504/IJADS.2012.050019
- Khalili-Damghani, K., Taghavifard, M., Olfat, L., and Feizi, K. (2012), Measuring agility performance in fresh food supply chains: an ordinal two-stage data envelopment analysis, International Journal of Business Performance and Supply Chain Modeling, 4(3/4), 206-231. https://doi.org/10.1504/IJBPSCM.2012.050390
- Khalili-Damghani, K. and Taghavifard, M. (2013), Sensitivity and stability analysis in two-stage DEA models with fuzzy data, International Journal of Operational Research, 17(1), 1-37. https://doi.org/10.1504/IJOR.2013.053186
- Khalili-Damghani, K. and Tavana, M. (2013), A new fuzzy network data envelopment analysis model for measuring the performance of agility in supply chains, International Journal of Advanced Manufacturing Technology, doi: 10.1007/s00170-013-5021-y. https://doi.org/10.1007/s00170-013-5021-y
- Khalili-Damghani, K., Tavana, M., and Santos-Arteaga, F. J. (2016), A comprehensive fuzzy DEA model for emerging market assessment and selection decisions, Applied Soft Computing, 38, 676-702. https://doi.org/10.1016/j.asoc.2015.09.048
- Kwon, H.-B. and Lee, J. (2015), Two-stage production modeling of large U.S. banks: A DEA-neural network approach, Expert Systems with Applications, 42(19), 6758-6766. https://doi.org/10.1016/j.eswa.2015.04.062
- McNair, C. J., Lynch, R. L., and Cross, K. F. (1990), Do Financial and Non-financial Performance Measures Have to Agree?, Management Accounting, 72(5), 28-36.
- Mihelis, G., Grigoroudis, E., Siskos, Y., Politis, Y., and Malandrakis, Y. (2001), Customer Satisfaction Measurement in Private Bank Sector, European Journal of Operational Research, 130(2), 347-360. https://doi.org/10.1016/S0377-2217(00)00036-9
- Puri, J. and Yadav, S. P. (2013), A concept of fuzzy input mix-efficiency in fuzzy DEA and its application in banking sector, Expert Systems with Applications, 40(5), 1437-1450. https://doi.org/10.1016/j.eswa.2012.08.047
- Puri, J. and Yadav, S. P. (2015), Intuitionistic fuzzy data envelopment analysis: An application to the banking sector in India, Expert Systems with Applications, 42(11), 4982-4998. https://doi.org/10.1016/j.eswa.2015.02.014
- Shyu, J. and Chiang, T. (2012), Measuring the true managerial efficiency of bank branches in Taiwan: A three-stage DEA analysis, Expert Systems with Applications, 39, 11494-11502. https://doi.org/10.1016/j.eswa.2012.04.005
- Soteriou, A. and Stavrinides, Y. (1997), An Internal Customer Service Quality Data Envelopment Analysis Model for Bank Branches, International Journal of Operations and Production Management, 17(8), 780-789. https://doi.org/10.1108/01443579710175556
- Stewart, C., Matousek, R., and Nguyen, T. N. (2016), Efficiency in the Vietnamese banking system: A DEA double bootstrap approach, Research in International Business and Finance, 36, 96-111. https://doi.org/10.1016/j.ribaf.2015.09.006
- Stoica, O., Mehdian, S., and Sargu, A. (2015), The Impact of Internet Banking on the Performance of Romanian Banks: DEA and PCA Approach, Procedia Economics and Finance, 20, 610-622. https://doi.org/10.1016/S2212-5671(15)00115-X
- Tavana, M. and Khalili-Damghani, K. (2014), A new two-stage Stackelberg fuzzy data envelopment analysis model, Measurement, 53, 277-296. https://doi.org/10.1016/j.measurement.2014.03.030
- Tavana, M., Khalili-Damghani, K., and Sadi-Nezhad, S. (2013), A fuzzy group data envelopment analysis model for high-technology project selection: A case study at NASA, Computers and Industrial Engineering, 66, 10-23. https://doi.org/10.1016/j.cie.2013.06.002
- Tsolas, I. E. and Charles, V. (2015), Incorporating risk into bank efficiency: A satisficing DEA approach to assess the Greek banking crisis, Expert Systems with Applications, 42(7), 3491-3500. https://doi.org/10.1016/j.eswa.2014.12.033
- Vavra, T. G. (1997), Improving Your Measurement of Customer Satisfaction: A Guide to Creating, Conducting and Reporting Customer Satisfaction Measurement Programs, Milwaukee: ASQ Quality Press.
- Wang, W.-K., Lu, W.-M., and Liu, P.-Y. (2014), A fuzzy multi-objective two-stage DEA model for evaluating the performance of US bank holding companies, Expert Systems with Applications, 41(9), 4290-4297. https://doi.org/10.1016/j.eswa.2014.01.004
- Wanke, P. and Barros, C. (2014), Two-stage DEA: An application to major Brazilian banks, Expert Systems with Applications, 41(5), 2337-2344. https://doi.org/10.1016/j.eswa.2013.09.031
- Wanke, P., Barros, C. P., and Emrouznejad, A. (2016), Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping: A case of Mozambican banks, European Journal of Operational Research, 249, 378-389. https://doi.org/10.1016/j.ejor.2015.10.018
- Yadav, S. P. and Puri, J. (2014), A fuzzy DEA model with undesirable fuzzy outputs and its application to the banking sector in India, Expert Systems with Applications, 41(14), 6419-6432. https://doi.org/10.1016/j.eswa.2014.04.013
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Supported by : Islamic Azad University