Abstract
Ranking the priorities of customers in selecting commercial banks is essential for the elaboration of bank development strategies. The purpose of this paper is to implement a fuzzy analytic hierarchy process (FAHP) multi-criteria decision model for commercial banks selection by customers. Six criteria and five Bahraini retail commercial banks are used to formulate a decision problem structured in three-level hierarchies. After structuring the hierarchies, the FAHP is applied to determine the relative weights of the evaluation criteria. The results show that most selected banks focus on pricing strategy more than bank facilities. Interest rates on credits and deposits as well as transaction costs are the main factors used to attract customers. The study provides several implications for decision makers to develop the appropriate strategies towards their customers’ preferences. An extensive numerical example for sensitivity analysis demonstrates the strength and plausibility of the FAHP approach.
Similar content being viewed by others
References
Afanasieff T, Lhacer P, Nakane M (2002) The determinants of bank interest spreads in Brazil. Central Bank of Brazil, working paper no 46
Alferos DB, Cristobal J (2017) Bank selection criteria by the students: input to the banking sector of the Philippines. Int J Manag Commer Innov 5(2):5–15
Astous A, Ahmed SA (1995) Comparison of country-of-origin effects on household and organizational buyers’ product perceptions. Eur J Mark 29(3):35–51
Belonax JJ, Aaby NE (1991) Credit union image variables-discriminating factors in the consumer’s financial institution choice process. J Prof Serv Mark 6(2):203–212
Blanchard RF, Galloway RL (1994) Quality in retail banking. Int J Serv Ind Manag 5(4):5–23
Bottani E, Rizzi A (2006) Strategic management of logistics service: a fuzzy-QFD approach. Int J Prod Econ 103(2):585–599
Boyd WL, Leonard M, White C (1994) Customer preferences for financial services: an analysis. Int J Bank Mark 12(1):9–15
Bozdag CE, Kahraman C, Ruan D (2003) Fuzzy group decision making for selection among computer integrated manufacturing systems. Comput Ind 51(1):13–29
Calabrese A, Costa R, Menichini T (2013) Using fuzzy AHP to manage intellectual capital assets: an application to the ICT service industry. Expert Syst Appl 40:3747–3755
Chan FTS, Kumar N (2007) Global supplier development considering risk factors using fuzzy extended AHP-based approach. Omega Int J Manag Sci 35(1):417–431
Chan APC, Chan DWM, Yeung JFY (2009) Overview of the application of “fuzzy techniques. J Constr Eng Manag 35(11):1241–1252
Chang DY (1996) Applications of the extent analysis method on FAHP. Eur J Oper Res 95(3):649–655
Chigamba C, Fatoki O (2011) Factors influencing the choice of commercial banks by university students in South Africa. Int J Bus Manag 6(6):66–76
Cicic M, Brkic N, Agic E (2003) Bank selection criteria employed by students in Southeastern European country: an empirical analysis of potential market segments preferences. Int J Bank Mark 27(2):1–18
Dhinaiyagovind M (2016) A study on determinants of preference and selection of bank. Int J Res Bus Manag 4(9):1–8
Dyer RF, Forman EH (1992) Group decision support with the analytic hierarchy process. Dec Support Syst 8(2):99–124
Freeman RE (1984) Strategic management: a stakeholder approach. Pitman, Boston
Frei FX, Harker PT (1999) Measuring aggregate process performance using AHP. Eur J Oper Res 116(2):436–442
Hosseini MH, Keshavarz E (2017) Using fuzzy AHP and fuzzy TOPSIS for strategic analysis measurement of service quality in banking industry. Int J Appl Manag Sci 9(1):55–80
Hun PT, Kar HY (2000) A study of bank selection decisions in Singapore using the analytical hierarchy process. Int J Bank Mark 18(4):170–180
Javalgi G, Armaco RL, Hosseini JC (1989) Using the analytical hierarchy process for bank management: analysis of consumer selection decisions. J Bus Res 19(1):33–49
Kahraman C, Ruan D, Dogan I (2003) Fuzzy group for facility location selection. Inf Sci 157:135–153
Kasperczyk N, Knickel K (2006) The analytic hierarchy process (AHP). ODPM. www.ivm.vu.nl/en/Images/MCA3_tcm53-161529.pdf
Kaya T, Kahraman C (2011) An integrated fuzzy AHP-ELECTRE methodology for environmental impact assessment. Expert Syst Appl 38(7):8553–8562
Khaitbaeva S, Ahmed AA, Enyinda CI (2014) An empirical analysis of attributes influencing bank selection choices by customers in the UAE: the Dubai context. In: Proceedings of the first middle east conference on global business, economics, finance and banking (ME14 Dubai conference) Dubai, 10–12 October 2014. ISBN: 978-1-941505-16-8. Paper ID_D4115 1
Khazeh K, Decker WH (1992) How customers choose banks. J Retail Bank 14(4):41–44
Laroche M, Rosenblatt JA, Manaing T (1986) Services used, and factors considered important in selecting a bank: an investigation across diverse demographic segments. Int J Bank Mark 4(1):35–55
Lee J, Marlowe J (2003) How consumers choose a financial institution: decision-making criteria and heuristics. Int J Bank Markt 21(2):53–71
Lee A, Chen W-C, Chang C-J (2008) A FAHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Taiwan. Expert Syst Appl 34:96–107
Ltifi M, Hikkerova L, Aliouat B, Gharbi J (2016) The determinants of the choice of Islamic banks in Tunisia. Int J Bank Mark 34(5):710–730
Lunt P (1994) What Asians like and dislike about banks. ABA Bank J 86(7):62
Mandic K, Delibasic B, Knezevic S, Benkovic S (2014) Analysis of the financial parameters of Serbian banks through the application of the fuzzy AHP and TOPSIS methods. Econ Model 43(1):30–37
Martenson R (1985) Consumer choice criteria in retail bank selection. Int J Bank Mark 3(2):64–75
Mikhailov L (2004) A fuzzy approach to deriving priorities from interval pairwise comparison judgements. Eur J Oper Res 159(3):687–704
Munda G, Nijkamp P, Rietveld P (1995) Qualitative multicriteria methods for fuzzy evaluation problems: an illustration of economic-ecological evaluation. Eur J Oper Res 82(1):79–97
Paksoy T, Pehlivan N, Kahraman C (2012) Organizational strategy development in distribution channel management using FAHP and hierarchical fuzzy TOPSIS. Expert Syst Appl 39:2822–2841
Rehman H, Ahmed S (2008) An empirical analysis of the determinants of bank selection in Pakistan a customer view. Pak Econ Soc Rev 46(2):147–160
Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New York
Saunders A, Schumacher L (2000) The determinants of bank interest rate margins: an international study. J Int Money Finance 19(6):813–832
Sinkula JL, Lawtor L (1988) Bank characteristics and customer bank choice: how important are importance measures. J Prof Serv Mark 3(3):131–141
Srouji A, Halim M, Lubis Z, Hamdallah M (2015) Determinants of bank selection criteria’s in relation to Jordanian Islamic and conventional banks. Int J Econ Commer Manag 3(10):294–306
Stafford MR (1994) How customers perceive service quality. J Retail Bank 17(2):29–38
Ta HP, Har KY (2000) A study of bank selection decision in Singapore using the analytic hierarchy process. Int J Bank Mark 18(1):170–180
Tootelian DH, Gaedeke RM (1996) Targeting the college market for banking services. J Prof Serv Mark 14(2):161–172
van Laarhoven PJM, Pedrycz W (1983) A fuzzy extension of Saaty’s priority theory. Fuzzy Sets Syst 11(1):229–241
Voinov A, Bousquet F (2010) Modeling with stakeholders. Environ Model Softw 25:1268–1281
Wang YM, Luo Y, Hua Z (2008) On the extent analysis method for FAHP and its applications. Eur J Oper Res 186:735–747
Zeydan M, Çolpan C, Çobanoğlu C (2011) A combined methodology for supplier selection and performance evaluation. Expert Syst Appl 38:2741–2751
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Al-Shammari, M., Mili, M. A fuzzy analytic hierarchy process model for customers’ bank selection decision in the Kingdom of Bahrain. Oper Res Int J 21, 1429–1446 (2021). https://doi.org/10.1007/s12351-019-00496-y
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12351-019-00496-y