An integrated Fuzzy AHP and ARAS model to evaluate mobile banking services
Abstract
Mobile banking (M-banking) which integrates software, hardware, and human is a new platform for banks. Determining the performance of M-banking services helps bank practitioners identify better policy to improve their positions. The aim of this study is to develop an integrated model for evaluating M-banking services by two methods, namely the Fuzzy Analytic Hierarchy Process (FAHP) with an extent analysis approach and ARAS (Additive Ratio ASsessment). In this study, the priority weights obtained through the FAHP are combined with the ARAS method to assess and rank the M-banking services. Moreover, in order to verify the applicability of this proposed model, a case study in Turkey is offered. The findings indicate that facilitating conditions play the most determining role in the adoption of the M-banking, followed by self-efficacy, privacy risk, and security risk. Consequently, the proposed model helps to overcome difficulties in M-banking service evaluation process and increases the efficiency of the M-banking service activities. Besides, the case study validates that the proposed model is an effective and efficient decision making tool for the evaluation of M-banking services under fuzzy environments.
First published online: 23 Apr 2017
Keyword : M-banking services, M-banking adoption, Fuzzy AHP, ARAS
How to Cite
Ecer, F. (2018). An integrated Fuzzy AHP and ARAS model to evaluate mobile banking services. Technological and Economic Development of Economy, 24(2), 670–695. https://doi.org/10.3846/20294913.2016.1255275
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Crabbe, M.; Standing, C.; Standing, S.; Karjaluoto, H. 2009. An adoption model for mobile banking in Ghana, International Journal of Mobile Communications 7(5): 515–543. https://doi.org/10.1504/IJMC.2009.024391
Cruz, P.; Neto, L. N. F.; Munoz-Gallego, P.; Laukkanen, T. 2010. Mobile banking rollout in emerging markets: evidence from Brazil, International Journal of Bank Marketing 28(5): 342–371. https://doi.org/10.1108/02652321011064881
Dadelo, S.; Turskis, Z.; Zavadskas, E. K.; Dadeliene, R. 2012. Multiple criteria assessment of elite security personal on the basis of ARAS and expert methods, Economic Computation and Economic Cybernetics Studies and Research 46(4): 65–88.
Das, M. C.; Sarkar, B.; Ray, S. 2012. A framework to measure relative performance of Indian technical institutions using integrated fuzzy AHP and COPRAS methodology, Socio-Economic Planning Sciences 46(3): 230–241. https://doi.org/10.1016/j.seps.2011.12.001
Davis, F. D. 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly 13(3): 319–340. https://doi.org/10.2307/249008
DeLone, W. H.; McLean, E. R. 2003. The DeLone and McLean model of information systems success: a ten-year update, Journal of Management Information Systems 19(4): 9–30.
Ecer, F. 2014. A hybrid banking websites quality evaluation model using AHP and COPRAS-G: a Turkey case, Technological and Economic Development of Economy 20(4): 758–782. https://doi.org/10.3846/20294913.2014.915596
Ecer, F. 2015. Performance evaluation of internet banking branches via a hybrid MCDM model under fuzzy environment, Economic Computation and Economic Cybernetics Studies and Research 49(2): 211–230.
Ecer, F. 2016. ARAS Yöntemi Kullanılarak Kurumsal Kaynak Planlaması Yazılımı Seçimi, Uluslararası Alanya İşletme Fakültesi Dergisi 8(1): 89–98.
Fishbein, M.; Ajzen, I. 1975. Attitude, intention and behavior: An introduction to theory and research. Washington: Addison-Wesley, 578 p.
Gu, J. C.; Lee, S. C.; Suh, Y. H. 2009. Determinants of behavioral intention to mobile banking, Expert Systems with Applications 36(9): 11605–11616. https://doi.org/10.1016/j.eswa.2009.03.024
Hanafizadeh, P.; Behboudi, M.; Abedini Koshksaray, A.; Jalilvand Shirkhani Tabar, M. 2014. Mobile-banking adoption by Iranian bank clients, Telematics and Informatics 31(1): 62–78. https://doi.org/10.1016/j.tele.2012.11.001
Hoehle, H.; Scornavacca, E.; Huff, S. 2012. Three decades of research on consumer adoption and utilization of electronic banking channels: a literature analysis, Decision Support Systems 54(1): 122–132. https://doi.org/10.1016/j.dss.2012.04.010
Kahraman, C.; Cebeci, U.; Ruan, D. 2004. Multi-attribute comparison of catering service companies using fuzzy AHP: the case of Turkey, International Journal of Production Economics 87: 171–184. https://doi.org/10.1016/S0925-5273(03)00099-9
Kim, G.; Shin, B.; Lee, H. G. 2009. Understanding dynamics between initial trust and usage intentions of mobile banking, Information Systems Journal 19(3): 283–311. https://doi.org/10.1111/j.1365-2575.2007.00269.x
Koenig-Lewis, N.; Palmer, A.; Moll, A. 2010. Predicting young consumers’ take up of mobile banking services, International Journal of Bank Marketing 28 (5): 410–432. https://doi.org/10.1108/02652321011064917
Korsgaard, M. A.; Schweiger, D. M.; Sapienza, H. J. 1995. Building commitment, attachment, and trust in strategic decision-making teams: the role of procedural justice, Academy of Management Journal 38(1): 60–84. https://doi.org/10.2307/256728
Kutut, V.; Zavadskas, E. K.; Lazauskas, M. 2013. Assessment of priority options for preservation of historic city centre buildings using MCDM (ARAS), Procedia Engineering 57: 657–661. https://doi.org/10.1016/j.proeng.2013.04.083
Laarhoven, P. J. M.; Pedrycz, W. 1983. A fuzzy extension of Saaty’s priority theory, Fuzzy Sets and Systems 11: 229–241. https://doi.org/10.1016/S0165-0114(83)80082-7
Laukkanen, T.; Cruz, P. 2008. Barriers to mobile banking adoption: a cross-national study, Proceedings of the International Conference on E-Business – Volume 1: ICE-B, 26–29 July 2008, Porto, Portugal, 300–306.
Laukkanen, T. 2007. Internet vs mobile banking comparing customer value perceptions, Business Process Management Journal 13(6): 788–797. https://doi.org/10.1108/14637150710834550
Lee, K. C.; N. Chung. 2009. Understanding factors affecting trust in and satisfaction with mobile banking in Korea: a modified Delone and Mclean’s Model perspective, Interacting with Computers 21: 385–392. https://doi.org/10.1016/j.intcom.2009.06.004
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