Hybrid Machine Learning Approach for predicting E-wallet Adoption among Higher Education Students in Malaysia
DOI:
https://doi.org/10.32890/jict2024.23.2.2Keywords:
E-wallet Adoption, Higher Education Students, Clustering, Decision Tree, Machine LearningAbstract
In today’s digitised world, e-wallets have been sprouting thick and fast in Malaysia as they contribute significantly to expediting online
transactions. The E-wallet system is not only a mechanism for businesses to acquire profit but is also one of the most secure payment
options for customers, particularly during the COVID-19 pandemic. However, the adoption of e-wallets among higher education students remains unfavourable, eliciting only minimal response. This study aims to analyse higher education students’ adoption of e-wallets using a hybrid machine learning method, combining clustering and decision trees. This approach provides deep insights into user behaviour, improving prediction accuracy and enabling personalised strategies for enhanced user experiences. It profiles and classifies students based on demographics and traits such as age, year of study, gender, frequency of use, future use intention, lifestyle compatibility, perceived trust, risk perception, convenience, and security factors. The analysis reveals the segmentation of the dataset into four distinct clusters, each characterised by shared attributes. These clusters are subsequently labelled descriptively and incorporated into the dataset. The dataset, now enriched with cluster information, serves as the foundation for constructing a decision tree model. The outcome of the decision tree indicates that Cluster 2 and Cluster 3 are hesitant towards e-payment. In contrast, Cluster 1 and Cluster 4 are more receptive despite security concerns, as e-wallets offer convenience despite lacking full trust, with security being a prominent concern amidst rising cyber threats. This study helps the Malaysian government and service providers promote cashless transactions and shape students’ financial independence based on their traits.
References
Abdul-Halim, N. A., Vafaei-Zadeh, A., Hanifah, H., et al. (2022). Understanding the determinants of e-wallet continuance usage intention in Malaysia. Quality & Quantity, 56(6), 3413–3439. https://doi.org/10.1007/s11135-021-01276-7 Journal of ICT, 23, No. 2 (April) 2024, pp: 177-
Abdul Rani, N. A. (2020, February 25). E-wallet promotes cashless community on campus. The Star. https://www.thestar.com.my/ metro/metro-news/2020/02/25/e-wallet-promotes-cashless-community-on-campus
Abdullah, N., Redzuan, F., & Daud, N. A. (2020). E-wallet: Factors influencing user acceptance towards cashless society in Malaysia among public universities. Indonesian Journal of Electrical Engineering and Computer Science, 20(1), 67–74. https://doi.org/10.11591/ijeecs.v20.i1
Ahmad, K., Khan, M. I., & Jan, M. T. (2010). Online banking acceptance in Malaysia: A students’ behaviour perspective. Malaysian Management Review, 45(2), 1-14
Alam, M. M., Awawdeh, A., & Muhamad, A. I. (2021). Using E-wallet for business process development: Challenges and prospects in Malaysia. Business Process Management Journal, 27(4), 1142-1162. https://doi.org/10.1108/BPMJ-11-2020-0528
Alashwal, H., El Halaby, M., Crouse, J. J., Abdalla, A., & Moustaf, A. A. (2019). The application of unsupervised clustering methods to Alzheimer’s disease. Frontiers in Computational Neuroscience 13(31). https://doi.org/10.3389/fncom.2019.00031
Ali, T. F., Sundra Raj, M. S., & Singh, J. S. K. (2021). A quantitative study on the factors influencing higher education institutions students’ acceptance of mobile payments in Klang Valley, Malaysia. Electronic Journal of Business and Management, 6(3), 15-43
Arbor Financial Credit Union. (2021, November 17). 5 Benefits of a Digital Wallet. Retrieved from https://www.arborfcu.org/ blog/5-benefits-of-a-digital-wallet
Bashir, I., & Madhavaiah, C. (2015). Consumer attitude and behavioral intention towards internet banking adoption in India. Journal of Indian Business Research, 7(1), 67–102. https://doi.org/10.1108/JIBR-02-2014-0013
Bauer, R. A. (1960). Consumer behavior as risk taking. In AMA Proceedings (Vol. 123, pp. 389-398). Chicago
Berton, A., Longo, U. G., Candela, V., Fioravanti, S., Giannone, L., Arcangeli, V., Alciati, V., Berton, C., Facchinetti, G., Marchetti, A., Schena, E., De Marinis, M. G., & Denaro, V. (2020). Virtual reality, augmented reality, gamification, and telerehabilitation: Psychological impact on orthopedic patients’ rehabilitation. Journal of Clinical Medicine, 9(8), 2567. https://doi.org/10.3390/jcm9082567 Journal of ICT, 23, No. 2 (April) 2024, pp: 177-
Birruntha, S. (2021, October 18). Pandemic pushes more than 80% growth for e-wallet players. The Malaysian Reserve. Retrieved from https://themalaysianreserve.com/2021/10/18/pandemic-pushes-more-than-80-growth-for-e-wallet-players/
Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984). Classification and Regression Trees. Monterey, CA: Wadsworth and Brooks
Chawla, D., & Joshi, H. (2023). Role of mediator in examining the influence of antecedents of mobile wallet adoption on attitude and intention. Global Business Review, 24(4), 609-625. https://doi.org/10.1177/0972150920924506
Chelvarayan, A., Yeo, S. F., Han, H. Y., & Hashim, H. (2022). E-wallet: A study on cashless transactions among university students. F1000Research, 11, 1-13. https://doi.org/10.12688/ f1000research.73545.1
Chen, S., Chang, X., Sun, G., Zhang, T., Xu, Y., Wang, Y., Pei, J., & Gong, J. (2021). Propane dehydrogenation: Catalyst development, new chemistry, and emerging technologies. Chemical Society Reviews, 50(5), 3315-3354. https://doi.org/10.1039/D0CS00814A
Ch’ng, C. K., & Mahat, N. (2014). Winsorised Gini Impurity: A resistant to outliers splitting metric for classification Tree. AIP Conference Proceedings, 716-723
Ch’ng, C. K., & Mahat, N. I. (2020). Winsorize tree algorithm for handling outlier in classification problem. International Journal of Operational Research, 38(2), 278-293. https://doi.org/10.1504/IJOR.2020.107073
Digital News Asia. (2019, July 1). Nielsen sees security concerns as main barrier to e-wallet adoption. Digital News Asia. Retrieved from https://www.digitalnewsasia.com/digital-economy/nielsen-sees-security-concerns-main-barrier-e-wallet-adoption
Duradoni, M., Spadoni, V., Gursesli, M. C., & Guazzini, A. (2023). Development and validation of the need for online social feedback (NfOSF) Scale. Human Behavior and Emerging Technologies, 2023, 1-11. https://doi.org/10.1155/2023/5581492
England, J. (2023, April 25). Unfolding e-wallets and the evolution of the payments sector. FinTech Magazine. Retrieved from https://fintechmagazine.com/articles/unfolding-e-wallets-and-the-evolution-of-the-payments-sector
Ester, M. (2009). Density-based clustering. In L. Liu & M. T. Özsu (Eds.), Encyclopedia of Database Systems. Springer. https://doi.org/10.1007/978-0-387-39940-9_605 Journal of ICT, 23, No. 2 (April) 2024, pp: 177-
Ezeudu, M. (2023, March 28). Risks and benefits of a digital wallet for everyday transactions. Payswix. https://payswix.com/risks- and-benefits-of-a-digital-wallet-for-everyday-transactions/
Gitau, L., & Nzuki, D. (2014). Analysis of determinants of m-commerce adoption by online consumers. International Journal of Business, Humanities and Technology, 4(3), 88-94
Glen, S. (2019, March 18). K-nn clustering explained in one picture. Data Science Central. Retrieved from https://www. datasciencecentral.com/author/stephanieglen/page/14/
Gomes, V. (2022). E-wallet: Digital payments pivotal to Malaysia’s financial services industry. The Edge Markets. Retrieved from https://www.theedgemarkets.com/article/ewallet-digital-payments-pivotal-malaysias-financial-services-industry
Gorunescu, F. (2011). Classification and decision trees. In Data Mining (Intelligent Systems Reference Library, Vol. 12). Springer. https://doi.org/10.1007/978-3-642-19721-5_
Gudmundsson, J. T. (2020). Physics and technology of magnetron sputtering discharges. Plasma Sources Science and Technology, 29(11), 113001. https://doi.org/10.1088/1361-6595/abb7bd
Hamid, A. A., Razak, F. Z. A., Bakar, A. A., & Abdullah, W. S. W. (2016). The effects of perceived usefulness and perceived ease of use on continuance intention to use E-government. Procedia Economics and Finance, 35, 644-649. https://doi.org/10.1016/ S2212-5671(16)00079-4
Haga, S., & Omote, K. (2021). IoT-based autonomous Pay-As-You-Go payment system with the contract wallet. Security and Communication Networks, 2021. 1-10. https://doi.org/10.1155/2021/8937448
Hong, C. M., Ch’ng, C. K., & Roslan, T. R. N. (2023). Predicting students’ inclination to TVET enrolment using various classifiers. Pertanika Journal of Science & Technology, 31(1), 475–493. https://doi.org/10.47836/pjst.31.1.28
Karim, M. W., Haque, A., Ulfy, M. A., Hossain, M. A., & Anis, M. Z. (2020). Factors influencing the use of e-wallet as a payment method among Malaysian young adults. Journal of International Business and Management, 3(2), 1-12. https://doi.org/10.37227/jibm-2020-2-21
Kaur, R., Li, Y., Iqbal, J., Gonzalez, H., & Stakhanova, N. (2018). A Security Assessment of HCE-NFC Enabled e-wallet Banking Android Apps. In 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC) (pp. 492-497). IEEE Journal of ICT, 23, No. 2 (April) 2024, pp: 177-
Kee, M. H., Lai, K. H., Lee, J. C., Lee, K. J., Lee, J. L., Yosanti, I., & Aryani, D. N. (2022). Do you have a digital wallet? A study of e-wallet during the COVID-19 pandemic. International Journal of Accounting and Finance in Asia Pacific, 5(1), 24-38. https://doi.org/10.32535/ijafap.v5i1.1413
Krisnawati, M., Wienadi, J., & Wiradinata, T. (2021). The effect of consumer trust and perceived risk on e-wallet adoption: Consideration for technology startup entrepreneurs. Jurnal Entrepreneur dan Entrepreneurship, 10(2), 111–118. https://doi.org/10.37715/jee.v10i2.221
Lee, Y. Y., Gan, C. L., & Liew, T. W. (2022). The impacts of mobile wallet app characteristics on online impulse buying: A moderated mediation model. Human Behavior and Emerging Technologies, 2022, 1-15. https://doi.org/10.1155/2022/2767735
Liébana-Cabanillas, F. J., Sánchez-Fernández, J., & Muñoz-Leiva, F. (2014). Role of gender on acceptance of mobile payment. Industrial Management and Data Systems, 114(2), 220–240. https://doi.org/10.1108/IMDS-03-2013-0137
Loh, M. (2020). MCO: CIMB says Touch ‘n Go eWallet continues to see healthy volumes for essential services, online-based transactions. The Edge Markets. Retrieved from https://www. theedgemarkets.com/article/touch-n-go-digital-sees-more-cashless-payments-postcovid-19
Malik, P., Pathania, M., & Rathaur, V. K. (2019). Overview of artificial intelligence in medicine. Journal of Family Medicine and Primary Care, 8(7), 2328. https://doi.org/10.4103/jfmpc. jfmpc_440_19
Marimuthu, M., & Roseline, A. (2020). A study on consumer perception towards e-wallet. OurHeritage, 68(17), 283-288
Martucci, A., Gursesli, M. C., Duradoni, M., & Guazzini, A. (2023). Overviewing gaming motivation and its associated psychological and sociodemographic variables: A PRISMA systematic review. Human Behavior and Emerging Technologies, 2023, 1–156. https://doi.org/10.1155/2023/5640258
Milberg, S. J., Smith, H. J., & Bruke, S. J. (2000). Information privacy: Corporate management and national regulation. Organization Science, 11(1), 35-57. http://www.jstor.org/stable/2640404
Mohammad Anuar, N. I., Nik Mahdi, N. M., Nik Hashim, N. A., Mohamad, S. R., Zainuddin, S. A., Azmi, N. F., & Wan Zulkiffli, W. F. (2020). The barriers towards the adoption of e-wallet payment system. International Journal of Engineering Journal of ICT, 23, No. 2 (April) 2024, pp: 177-
Research and Technology, 13(11), 3772-3777. https://dx.doi. org/10.37624/IJERT/13.11.2020.3772-3777
Mohamad Shafi, R., & Misman, F. (2019). The perceived benefit and risk framework of e-wallet adoption among the early adopters in Malaysia. In Proceedings of the 2nd Economics and Business International Conference (pp. 579-584)
Mohd Razif, N. N., Misiran, M., Sapiri, H., & Md Yusof, Z. (2020). Perceived risk for acceptance of e-wallet platform in Malaysia among youth: SEM approach. Management Research Journal, 9, 1–24. https://doi.org/10.37134/mrj.vol9.sp.1.2020
Mohd Zahari, M. F., Ahmad, S., Hambali, M. A., & Pisol, M. I. M. (2021). The effects of COVID-19 pandemic and cashless society. In Proceedings of the 5th National Pre-University Seminar 2021 (5th NPreUS 2021) (pp. 138-142)
Murtagh, F. (2011). Hierarchical Clustering. In M. Lovric (Ed.), International Encyclopedia of Statistical Science. Springer. https://doi.org/10.1007/978-3-642-04898-2_288
Navanwita, S. (2019). The evolution of e-wallets: History, benefits, and withdrawals. Retrieved from https://sociable.co/mobile/ evolution-ewallets-history-benefits-withdrawals
Nizam, F., Hwang, H. J., & Valaei, N. (2018). Measuring the effectiveness of e-wallet in Malaysia. In 3rd IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science Engineering (pp. 59-69). Springer
Noordin, K. A. (2017). Fintech: Mobile payments for more secure transactions. Retrieved from http://www.theedgemarkets.com/ article/fintech-mobile-payments-moresecure-transactions
Omran, M., Engelbrecht, A., & Salman, A. (2007). An overview of clustering methods. Intelligent Data Analysis, 11(6), 583–605. https://doi.org/10.3233/IDA-2007-11602
Ong, H. B., & Chong, L. L. (2023). The effect of cashless payments on the internet and mobile banking. Journal of Financial Services Marketing, 28(2), 178–188. https://doi.org/10.1057/ s41264-022-00145-0
Oppotus (2022). Share of people who used digital wallets in Malaysia from 1st quarter 2019 to 1st quarter 2022. Statista. Retrieved from https://www.statista.com/statistics/1327192/malaysia-e-wallet-usage-rate/
Osakwe, C. N., & Okeke, T. C. (2016). Facilitating mCommerce growth in Nigeria through mMoney usage: A preliminary analysis. Interdisciplinary Journal of Information, Knowledge, and Management, 11, 115-139. https://doi.org/10.28945/3456 Journal of ICT, 23, No. 2 (April) 2024, pp: 177-
Prasetyadi, A., Nugroho, B., & Tohari, A. (2022). A hybrid K-means hierarchical algorithm for natural disaster mitigation clustering. Journal of Information and Communication Technology, 21(2), 175-200. https://doi.org/10.32890/jict2022.21.2.2
PricewaterhouseCoopers (2018). Banking on the e-wallet in Malaysia. Retrieved from https://www.pwc.com/my/en/perspective/deal-strategy/181003-banking-on-the-e-wallet-in-malaysia.html
Punwatkar, S., & Verghese, M. (2018). Adaptation of e-wallet payment: An empirical study on consumers’ adoption behavior in Central India. International Journal of Advances in Management, Technology, and Engineering Sciences, 8(3), 1147–1156
Rajni, A., Zareen, & Chaddha, P. (2021). Awareness and use of mobile money among college students in university. Proceedings of the International Conference on Advances in Management Practices (ICAMP 2021). Available at SSRN: https://ssrn.com/ abstract=3993107
Ray, A. (2017). What are the different types of e-commerce payment systems? Amazon Services. Retrieved from https://services.amazon.in/resources/seller-blog/different-types-of-e-commerce-payment-systems.html
Ridzaimi (2023). PM: All Malaysian university students will get RM200 eWallet aid regardless of age. TechNave. Retrieved from https://technave.com/gadget/PM-All-Malaysian
Rosnidah, I., Muna, A., Musyaffi, A. M., & Siregar, N. F. (2019). Critical factor of mobile payment acceptance in millennial generation: Study on the UTAUT model. In International Symposium on Social Sciences, Education, and Humanities (ISSEH 2018). Atlantis Press. 10.2991/isseh-18.2019.30
Sangma, J. W., Sarkar, M., & Pal, V. (2022). Hierarchical clustering for multiple nominal data streams with evolving behavior. Complex and Intelligent Systems, 8, 1737–1761. https://doi.org/10.1007/s40747-021-00634-0
Seng, N. D., Ibrahim, N. F., Yin, L. S., & Maiyus, M. B. (2023). An empirical study on acceptance of e-wallet among Malaysian university students. International Journal of Academic Research in Business and Social Sciences, 13(1), 1099–1112. http://dx.doi.org/10.6007/IJARBSS/v13-i1/15728
Singh, M. N. (2021). Inroad of digital technology in education: Age of digital classroom. Higher Education for the Future, 8(1), 20–30. https://doi.org/10.1177/2347631120980
Szmrecsanyi, B. (2012). Grammatical Variation in British English Dialects: A Study in Corpus-Based Dialectometry. Cambridge University Press Journal of ICT, 23, No. 2 (April) 2024, pp: 177-
Tan, J. Y. (2019). Nielsen sees security concerns as the main barrier to e-wallet adoption. Digital News Asia. Retrieved from https://www.digitalnewsasia.com/digital-economy/nielsen-sees-security-concerns-main-barrier-e-wallet-adoption
Tan, Z. Y. (2022). e-wallet: Cybersecurity: How much cash would you keep in your e-wallet? The Edge Markets. Retrieved from https://www.theedgemarkets.com/article/ewallet-cybersecurity-how-much-cash-would-you-keep-your-ewallet
Teng, S. S., & Khong, K. W. (2021). Examining actual consumer usage of e-wallet: A case study of big data analytics. Computers in Human Behavior, 121, 1–12. https://doi.org/10.1016/j. chb.2021.106778
Trust Payment. (2023, September 12). The rise of mobile wallets in 2023.
Uddin, M. S., & Akhi, A. Y. (2014). E-wallet system for Bangladesh: An electronic payment system. International Journal of Modeling and Optimization, 4(3), 216–226. 10.7763/IJMO.2014.V4.376
Uduji, J. I., Okolo-Obasi, E. N., & Asongu, S. A. (2019). The impact of e-wallet on informal farm entrepreneurship development in rural Nigeria. The Electronic Journal of Information Systems in Developing Countries, 85(3), 1-27. https://doi.org/10.1002/ isd2.12066
Undale, S., Kulkarni, A., & Patil, H. (2021). Perceived eWallet security: Impact of COVID-19 pandemic. Vilakshan - XIMB Journal of Management, 18(1), 89–104. https://doi.org/10.1108/XJM-07-2020-0022
Uppada, S. K. (2014). Centroid-based clustering algorithms: A clarion study. International Journal of Computer Science and Information Technologies, 5(6), 7309–7313
Widodo, M., Irawan, M. I., & Sukmono, R. A. (2019). Extending UTAUT2 to explore digital wallet adoption in Indonesia. In International Conference on Information and Communications Technology (pp. 878–883). https://doi.org/10.1109/ icoiact46704.2019.8938415
Xu, X. W., Ester, M., Kriegel, H. P., & Sander, J. (1998). A distribution-based clustering algorithm for mining in large spatial databases. In Proceedings 14th International Conference on Data Engineering (pp. 324–331). https://doi.org/10.1109/ ICDE.1998.655795
Yang, M., Al Mamun, A., Mohiuddin, M., Nawi, N. C., & Zainol, N. R. (2021). Cashless transactions: A study on intention and adoption of e-wallet. Sustainability, 13(2), 831. https://doi.org/10.3390/su13020831 Journal of ICT, 23, No. 2 (April) 2024, pp: 177-
Yang, T., Chan, T. J., Mohd Suki, N., & Mohd Ariff, K. (2023). Moderating role of perceived trust and perceived service quality on consumers’ use behavior of Alipay e-wallet system: The perspectives of technology acceptance model and theory of planned behavior. Human Behavior and Emerging Technologies, 2023. https://doi.org/10.1155/2023/5276406
Yong, I. I., Wong, T. K., & Lim, P. Y. (2021). Intention to use e-wallet amongst the university students in Klang Valley. International Journal of Business and Economy, 3(1), 75–84. https://myjms. mohe.gov.my/index.php/ijbec/article/view/12747
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