A Fuzzy Topsis Approach for Selecting Mobile Banking Applications

The growing reliance on mobile banking applications has created challenges for users in selecting the most suitable option due to diverse features and services tailored to varying preferences. Similarly, banks and application developers struggle to successfully customize their applications to satisfy user needs effectively. This study aimed to rank mobile banking applications among UiTM Perlis students using the Fuzzy Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) approach. Additionally, it sought to identify and rank the criteria influencing the selection of mobile banking applications. Primary data were collected from 55 UiTM Perlis through an online questionnaire. This study focused on three mobile banking applications as the alternatives which were MAE by Maybank2u, GO by Bank Islam, and RHB Mobile Banking, and evaluated them based on four criteria which were design, efficiency, security, and customer support. The results of the Fuzzy TOPSIS analysis revealed that MAE by Maybank2u emerged as the top-ranked application, followed by RHB Mobile Banking and GO by Bank Islam. These findings are highly significant as they provide valuable insights for banks and developers to refine their applications by focusing on key user preferences, such as enhanced design, improved efficiency, robust security, and better customer support. Users benefit from improved mobile banking experiences that align with their expectations for convenience and functionality. Furthermore, this research highlights the importance of understanding user preferences as a strategic advantage in a competitive market. Future research should expand the sample size to include participants from diverse regions to ensure more generalizable results. Incorporating qualitative feedback can also offer deeper insights into user satisfaction, enriching the understanding of how mobile banking applications can be improved to meet evolving user demands effectively.

Fuzzy TOPSIS, Mobile Banking Application, Selection. Students

1. Alhejji, S., Albesher, A., Wahsheh, H., & Albarrak, A. (2022). Evaluating and comparing the usability of mobile banking applications in Saudi Arabia. Information (Switzerland). https://doi.org/10.3390/info13120559 [Google Scholar] [Crossref]

2. Aliyev, R., Temizkan, H., & Aliyev, R. (2020). Fuzzy analytic hierarchy process-based multi-criteria decision making for universities ranking. Symmetry. https://doi.org/10.3390/sym12081351 [Google Scholar] [Crossref]

3. Başar, M. S., & Kul, S. (2020). Evaluation of mobile banking apps in terms of usability with analytical hierarchy process. Bilgi Yönetimi, 3(1), 39–49. https://doi.org/10.33721/by.677976 [Google Scholar] [Crossref]

4. Chanu, A. M., & Singh, A. R. (2022). Examining factors affecting customers adoption towards e-banking services: An empirical investigation in Manipur. ISBR Management Journal, 6(2), 38–49. https://doi.org/10.52184/isbrmj.v6i02.118 [Google Scholar] [Crossref]

5. Esmaeili, A., Haghgoo, I., Davidaviciene, V., & Meidute-Kavaliauskiene, I. (2021). Customer loyalty in mobile banking: Evaluation of perceived risk, relative advantages, and usability factors. Engineering Economics. https://doi.org/10.5755/j01.ee.32.1.25286 [Google Scholar] [Crossref]

6. Harrison, R., Flood, D., & Duce, D. (2013). Usability of mobile applications: Literature review and rationale for a new usability model. Journal of Interaction Science. https://doi.org/10.1186/2194-0827-1-1 [Google Scholar] [Crossref]

7. Hussain, A., Abubakar, H. I., & Hashim, N. B. (2014). Evaluating mobile banking application: Usability dimensions and measurements. Conference Proceedings - 6th International Conference on Information Technology and Multimedia at UNITEN: Cultivating Creativity and Enabling Technology Through the Internet of Things, ICIMU 2014. https://doi.org/10.1109/ICIMU.2014.7066618 [Google Scholar] [Crossref]

8. Hwang, C.-L., & Yoon, K. (1981). Multiple attributes decision making methods and applications. Multiple Attribute Decision Making. [Google Scholar] [Crossref]

9. Islam, M. N., Islam, I., Munim, K. M., & Islam, A. K. M. N. (2020). A review on the mobile applications developed for COVID-19: An exploratory analysis. IEEE Access. https://doi.org/10.1109/ACCESS.2020.3015102 [Google Scholar] [Crossref]

10. Kannan, D., De Sousa Jabbour, A. B. L., & Jabbour, C. J. C. (2014). Selecting green suppliers based on GSCM practices: Using Fuzzy TOPSIS applied to a Brazilian electronics company. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2013.07.023 [Google Scholar] [Crossref]

11. Kanungo, R. P., & Gupta, S. (2021). Financial inclusion through digitalisation of services for well-being. Technological Forecasting and Social Change. https://doi.org/10.1016/j.techfore.2021.120721 [Google Scholar] [Crossref]

12. Kapoor, A. P., & Vij, M. (2020). How to boost your app store rating? An empirical assessment of ratings for mobile banking apps. Journal of Theoretical and Applied Electronic Commerce Research. https://doi.org/10.4067/S0718-18762020000100108 [Google Scholar] [Crossref]

13. Karim, M. M., Islam, M. N., Priyoti, A. T., Ruheen, W., Jahan, N., Pritu, P. L., Dewan, T., & Duti, Z. T. (2017). Mobile health applications in Bangladesh: A state-of-the-art. 2016 3rd International Conference on Electrical Engineering and Information and Communication Technology, ICEEiCT 2016. https://doi.org/10.1109/CEEICT.2016.7873148 [Google Scholar] [Crossref]

14. Khodamipour, A., Askari Shahamabad, M., & Askari Shahamabad, F. (2022). Fuzzy AHP-TOPSIS method for ranking the solutions of environmental taxes implementation to overcome its barriers under fuzzy environment. Journal of Applied Accounting Research. https://doi.org/10.1108/JAAR-03-2021-0076 [Google Scholar] [Crossref]

15. Komulainen, H., & Saraniemi, S. (2019). Customer centricity in mobile banking: A customer experience perspective. International Journal of Bank Marketing. https://doi.org/10.1108/IJBM-11-2017-0245 [Google Scholar] [Crossref]

16. Mahmud, N., Jamaluddin, S. H., Omar, N. A., & Muhammat Pazil, N. S. (2018). Investigating the factors of committing crimes using fuzzy TOPSIS. Journal of Computing Research and Innovation, 3(1), 2600–8793. https://doi.org/10.24191/jcrinn.v3i1.77 [Google Scholar] [Crossref]

17. Majumdar, S., & Pujari, V. (2022). Exploring usage of mobile banking apps in the UAE: a categorical regression analysis. Journal of Financial Services Marketing. https://doi.org/10.1057/s41264-021-00112-1 [Google Scholar] [Crossref]

18. Memari, A., Dargi, A., Akbari Jokar, M. R., Ahmad, R., & Abdul Rahim, A. R. (2019). Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method. Journal of Manufacturing Systems. https://doi.org/10.1016/j.jmsy.2018.11.002 [Google Scholar] [Crossref]

19. NǍdǍban, S., Dzitac, S., & Dzitac, I. (2016). Fuzzy TOPSIS: A general view. Procedia Computer Science. https://doi.org/10.1016/j.procs.2016.07.088 [Google Scholar] [Crossref]

20. Nair, A. B., Prabhu, K. S., Aditya, B. R., Durgalashmi, C. V., & Prabhu, A. S. (2021). Study on the usage of mobile banking application during COVID-19 pandemic. Webology. https://doi.org/10.14704/WEB/V18SI02/WEB18066 [Google Scholar] [Crossref]

21. Oh, Y. K., & Kim, J. M. (2021). What improves customer satisfaction in mobile banking apps? an application of text mining analysis. Asia Marketing Journal. https://doi.org/10.53728/2765-6500.1581 [Google Scholar] [Crossref]

22. Prakash, C., & Barua, M. K. (2015). Integration of AHP-TOPSIS method for prioritizing the solutions of reverse logistics adoption to overcome its barriers under fuzzy environment. Journal of Manufacturing Systems. https://doi.org/10.1016/j.jmsy.2015.03.001 [Google Scholar] [Crossref]

23. Raza, S. A., Umer, A., & Shah, N. (2017). New determinants of ease of use and perceived usefulness for mobile banking adoption. International Journal of Electronic Customer Relationship Management. https://doi.org/10.1504/IJECRM.2017.086751 [Google Scholar] [Crossref]

24. Roy, P., & Shaw, K. (2023). A fuzzy MCDM decision-making model for m-banking evaluations: comparing several m-banking applications. Journal of Ambient Intelligence and Humanized Computing. https://doi.org/10.1007/s12652-022-03743-x [Google Scholar] [Crossref]

25. Sam, T. H., Wen, E. C. Y., Yanjing, Yan, W., Ruiteng, X., Jihu, L., & Vasudevan, A. (2023). Understanding the determinants of mobile banking app usage in Malaysia: A consumer behavior perspective. Gravida, 62(6), 1–24. https://doi.org/DOI 10.17605/OSF.IO/BF2NX [Google Scholar] [Crossref]

26. Saprikis, V., Avlogiaris, G., & Katarachia, A. (2022). A comparative study of users versus non-users’ behavioral intention towards m-banking apps’ adoption. Information (Switzerland). https://doi.org/10.3390/info13010030 [Google Scholar] [Crossref]

27. Thakuri, N., Dhakal, A., Danuwar, R. K., Baral, D. K., & Koirala, A. (2023). Factor affecting customer satisfaction of mobile banking services of commercial bank in Kathmandu Valley. Interdisciplinary Journal of Innovation in Nepalese Academia. https://doi.org/10.3126/idjina.v2i1.55964 [Google Scholar] [Crossref]

28. Thusi, P., & Maduku, D. K. (2020). South African millennials’ acceptance and use of retail mobile banking apps: An integrated perspective. Computers in Human Behavior. https://doi.org/10.1016/j.chb.2020.106405 [Google Scholar] [Crossref]

29. Turner, A. (2022). How Many People Have Smartphones Worldwide. In BankMyCell. [Google Scholar] [Crossref]

30. Ubam, E., Hipiny, I., & Ujir, H. (2021). User interface/user experience (UI/UX) analysis design of mobile banking app for senior citizens: A case study in Sarawak, Malaysia. Proceedings of the International Conference on Electrical Engineering and Informatics. https://doi.org/10.1109/ICEEI52609.2021.9611136 [Google Scholar] [Crossref]

31. Unvan, Y. A. (2020). Financial performance analysis of banks with topsis and fuzzy topsis approaches. Gazi University Journal of Science. https://doi.org/10.35378/gujs.730294 [Google Scholar] [Crossref]

32. Wang, Y., Huang, Y., Li, J., & Zhang, J. (2021). The effect of mobile applications’ initial loading pages on users’ mental state and behavior. Displays. https://doi.org/10.1016/j.displa.2021.102007 [Google Scholar] [Crossref]

33. Weichbroth, P. (2020). Usability of mobile applications: A systematic literature study. IEEE Access. https://doi.org/10.1109/ACCESS.2020.2981892 [Google Scholar] [Crossref]

34. Yu, C. S. (2002). A GP-AHP method for solving group decision-making fuzzy AHP problems. Computers and Operations Research. https://doi.org/10.1016/S0305-0548(01)00068-5 [Google Scholar] [Crossref]