Consumers' Intention to Continue Using Cryptocurrency Mobile Wallets in Malaysia DOI: https://doi.org/10.33093/ijomfa.2022.3.2.1
Article Sidebar
Main Article Content
Abstract
In Malaysia, over RM 800 million transactions were processed in one cryptocurrency platform. The central bank of Malaysia has made e-payment one of its top targets to execute a cashless payment system. However, an in-depth analysis of the literature shows a dearth of research focusing on the influencers of cryptocurrency mobile wallet acceptance, especially the intention to use them continuously. Therefore, this study uses the Post-Acceptance Model of IS Continuance to determine the elements influencing the continuance intention of cryptocurrency mobile wallets in Malaysia. This research also investigates the impact of perceived security, effort expectations, and social influence on the intention to continue the usage of cryptocurrency mobile wallets. The empirical evidence from 106 current cryptocurrency respondents shows that: (1) perceived security and satisfaction are significant factors of continuance intention, and (2) performance expectancy, effort expectancy, and social influence are insignificant factors of continuance intention. It reveals perceived security as one of the critical elements in continuance intention in the cryptocurrency field.
Article Details
References
Al-Emran, M., Arpaci, I., & Salloum, S. A. (2020). An empirical examination of continuous intention to use m-learning: An integrated model. Education and Information Technologies, 25(4), 2899–2918. https://doi.org/10.1007/s10639-019-10094-2
Ashraf, M., Ahmad, J., Hamyon, A. A., Sheikh, M. R., & Sharif, W. (2020). Effects of post-adoption beliefs on customers’ online product recommendation continuous usage: An extended expectation-confirmation model. Cogent Business and Management, 7(1). https://doi.org/10.1080/23311975.2020.1735693
Baabdullah, A. M., Alalwan, A. A., Rana, N. P., Patil, P., & Dwivedi, Y. K. (2019). An integrated model for m-banking adoption in Saudi Arabia. International Journal of Bank Marketing. https://doi.org/10.1108/IJBM-07-2018-0183
Bank Negara Malaysia (BNM). (2010). Financial Stability and Payment Systems Report 2009. In The Financial Stability and Payment Systems Report. https://doi.org/10.1111/j.1151-2916.1928.tb16483.x
Bank Negara Malaysia, & Securities Commission Malaysia. (2020). BNM and SC’s Joint Response on “Policy confusion over cryptocurrencies.” https://www.bnm.gov.my/-/bnm-and-sc-s-joint-response-on-policy-confusion-over-cryptocurrencies-
Barkhordari, M., Nourollah, Z., Mashayekhi, H., Mashayekhi, Y., & Ahangar, M. S. (2017). Factors Influencing Adoption of E-Payment Systems : An Empirical Study on Iranian Customers. Information Systems and E-Business Management, 15(1). https://doi.org/10.1007/s10257-016-0311-1
Baumgartner, H., & Weijters, B. (2017). Handbook of Marketing Decision Models. Springer. https://doi.org/10.1007/978-3-319-56941-3
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly: Management Information Systems, 25(3), 351–370. https://doi.org/10.2307/3250921
Bhattacherjee, A., & Premkumar, G. (2004). Understanding Changes in Belief and Attitude toward Information Technology Usage: A Theoretical Model and Longitudinal Test. MIS Quarterly, 28(2), 229–254.
Boomsma, A. (1982). The robustness of LISREL against small sample sizes in factor analysis models. In K. G. Jöreskog & H. Wold (Eds.), Systems under indirect observation: Causality, structure, prediction (Part 1). North-Holland.
Chau, P. Y. K., & Hu, P. J. H. (2001). Information technology acceptance by individual professionals: A model comparison approach. Decision Sciences, 32(4), 699–719. https://doi.org/10.1111/j.1540-5915.2001.tb00978.x
Chen, G., Xu, B., Lu, M., & Chen, N.-S. (2018). Exploring blockchain technology and its potential applications for education. Smart Learning Environments, 5(1), 1–10. https://doi.org/10.1186/s40561-017-0050-x
Cheong, A. (2020). Luno: Over RM827 Million Worth Of Transactions Processed In Malaysia Since 2019 Relaunch. RinggitPlus. https://ringgitplus.com/en/blog/personal-finance-news/luno-over-rm827-million-worth-of-transactions-processed-in-malaysia-since-2019-relaunch.html
Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (Issue April, pp. 295–336). Lawrence Erlbaum Associates.
Cho, J., & Lee, H. E. (2020). Post-adoption beliefs and continuance intention of smart device use among people with physical disabilities. Disability and Health Journal, 13(2), 100878. https://doi.org/10.1016/j.dhjo.2019.100878
Chong, A. Y. (2013). Predicting m-commerce adoption determinants: A neural network approach. Expert Systems With Applications, 40, 523–530. https://doi.org/10.1016/j.eswa.2012.07.068
Daneji, A. A., Khambari, M. N. M., Mohd Ayub, A. F., & Wan Jaafar, W. M. (2017). Influence of students’ perceived ease of use, perceived usefulness and time spent towards students’ continuance intention using mooc among public university students. 3rd International Conference on Education in Muslim Society (ICEMS 2017), 115. https://doi.org/10.2991/icems-17.2018.50
Darmawan, D., Mardikaningsih, R., & Hadi, S. (2017). The Effect of Service Quality, Customer Satisfaction and Corporate Image on Customer Loyalty in the banking sector in Indonesia. Journal of Business Management, 19(11), 46–51. https://doi.org/10.31219/osf.io/uxsfr
Das, P., Faust, S., & Loss, J. (2019). A Formal Treatment of Deterministic Wallets. 2019 ACM SIGSAC Conference on Computer and Communications Security.
Dattani, J., & Sheth, H. (2019). Overview of Blockchain Technology. Asian Journal of Convergence in Technology, 05(01), 1–4. https://doi.org/10.33130/ajct.2019v05i01.013
Eliasi, B., & Javdan, A. (2019). Comparison of blockchain e- wallet implementations.
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Analytics, 18(1).
Gao, S., Yang, X., Guo, H., & Jing, J. (2018). An Empirical Study on Users’ Continuous Usage Intention of QR Code Mobile Payment Services in China. International Journal of E-Adoption, 10(1), 18–33. https://doi.org/10.4018/ijea.2018010102
Garson, G. D. (2016). Partial Least Squares: Regression & Structural Equation Models. In Multi-Label Dimensionality Reduction. https://doi.org/10.1201/b16017-6
Gillies, F. I., Lye, C.-T., & Tay, L.-Y. (2020). Determinants of Behavioral Intention To Use Bitcoin in Malaysia. Journal of Information System and Technology Management, 5(19), 25–38. https://doi.org/10.35631/jistm.519003
Gupta, A., Dhiman, N., Yousaf, A., & Arora, N. (2020). Social comparison and continuance intention of smart fitness wearables: an extended expectation confirmation theory perspective. Behaviour & Information Technology. https://doi.org/10.1080/0144929X.2020.1748715
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., Black, W. C., & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage. https://doi.org/10.1002/9781119409137.ch4
Hair, J. F., Hult, G. T. M., & Ringle, C. M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). SAGE.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20, 277–319. https://doi.org/10.1108/S1474-7979(2009)0000020014
Hinton, P. R., McMurray, I., & Brownlow, C. (2014). SPSS Explained. In e-conversion - Proposal for a Cluster of Excellence (2nd ed.). Routledge.
Höck, M., & Ringle, C. M. (2010). Local strategic networks in the software industry: An empirical analysis of the value continuum. International Journal of Knowledge Management Studies, 4(2), 132–151. https://doi.org/10.1504/IJKMS.2010.030789
Huarng, K. H., & Yu, M. F. (2019). Customer satisfaction and repurchase intention theory for the online sharing economy. Review of Managerial Science, 13(3), 635–647. https://doi.org/10.1007/s11846-018-0321-0
Hutabarat, Z., Suryawan, I. N., Andrew, R., & Akwila, F. P. (2021). Effect Of Performance Expectancy And Social Influence On Continuance Intention In OVO. Jurnal Manajemen, 25(1), 125. https://doi.org/10.24912/jm.v25i1.707
Jansen, D.-J., Mosch, R. H. J., & van der Cruijsen, C. A. B. (2015). When Does the General Public Lose Trust in Banks? Journal of Financial Services Research, 48, 127–141. https://doi.org/10.1007/s10693-014-0201-y
Jin, C. C., Seong, L. C., & Khin, A. A. (2019). Investigating of factors affecting the consumers’ adoption of m-wallet in Malaysia. UPM 2019 National Seminar on Digitalizaton, Sustainability & Globalization.
Jo, D. (2018). Exploring the determinants of MOOCs continuance intention. KSII Transactions on Internet and Information Systems, 12(8), 3992–4005. https://doi.org/10.3837/tiis.2018.08.024
Jokic, S., Cvetkovic, A., Adamovic, S., Ristic, N., & Spalevic, P. (2019). Comparative analysis of cryptocurrency wallets vs traditional wallets. Ekonomika, 65(3), 65–75. https://doi.org/10.5937/ekonomika1903065j
Jonker, N. (2019). What drives the adoption of crypto-payments by online retailers? Electronic Commerce Research and Applications, 35(April), 100848. https://doi.org/10.1016/j.elerap.2019.100848
Joo, Y. J., Park, S., & Shin, E. K. (2017). Students’ expectation, satisfaction, and continuance intention to use digital textbooks. Computers in Human Behavior, 69, 83–90. https://doi.org/10.1016/j.chb.2016.12.025
Junadi, & Sfenrianto. (2015). A Model of Factors Influencing Consumer’s Intention to Use E-payment System in Indonesia. Procedia Computer Science, 59(Iccsci), 214–220. https://doi.org/10.1016/j.procs.2015.07.557
Khan, A. G., Zahid, A. H., Hussain, M., & Riaz, U. (2019). Security Of Cryptocurrency Using Hardware Wallet And QR Code. 2019 International Conference on Innovative Computing (ICIC).
Kim, S. H., Bae, J. H., & Jeon, H. M. (2019). Continuous intention on accommodation apps: Integrated value-based adoption and expectation-confirmation model analysis. Sustainability (Switzerland), 11(6), 1–17. https://doi.org/10.3390/su11061578
Lee, S. W., Sung, H. J., & Jeon, H. M. (2019). Determinants of continuous intention on food delivery apps: Extending UTAUT2 with information quality. Sustainability (Switzerland), 11(11). https://doi.org/10.3390/su11113141
Lee, Y. P., Tsai, H. Y., & Ruangkanjanases, A. (2020). The determinants for food safety push notifications on continuance intention in an e-appointment system for public health medical services: The perspectives of utaut and information system quality. International Journal of Environmental Research and Public Health, 17(21), 1–15. https://doi.org/10.3390/ijerph17218287
Li, C. Y., & Fang, Y. H. (2019). Predicting continuance intention toward mobile branded apps through satisfaction and attachment. Telematics and Informatics. https://doi.org/10.1016/j.tele.2019.101248
Lim, S. H., Kim, D. J., Hur, Y., & Park, K. (2018). An Empirical Study of the Impacts of Perceived Security and Knowledge on Continuous Intention to Use Mobile Fintech Payment Services. International Journal of Human-Computer Interaction, 35(10), 886–898. https://doi.org/10.1080/10447318.2018.1507132
Linardi, K., & Anggono, A. H. (2019). An Empirical Study On User’s Continuous Usage Intention Of Mobile Payment Services Among Generation Z In Bandung City. The 4th ICMEM 2019 and The 11th IICIES 2019.
Maduku, D. K. (2017). Understanding E-Book Continuance Intention: Empirical Evidence from E-Book Users in a Developing Country. Cyberpsychology, Behavior, and Social Networking, 20(1), 30–36. https://doi.org/10.1089/cyber.2016.0287
Malaysian Communications And Multimedia Commission. (2020). Internet Users Survey 2020. https://www.mcmc.gov.my/skmmgovmy/media/General/pdf/IUS-2020-Infographic.pdf
Mandal, D., & McQueen, R. J. (2012). Extending UTAUT to Explain Social Media Adoption by Microbusinesses. International Journal of Managing Information Technology. https://doi.org/10.5121/ijmit.2012.4401
Miraz, M. H., Hassan, M. G., & Mohd Sharif, K. I. (2020). Factors affecting implementation of blockchain in retail market in Malaysia. International Journal of Supply Chain Management, 9(1), 385–391.
Mohania, S., & Singh, S. (2020). An analysis of cryptocurrency and its challenges. EPRA International Journal of Multidisciplinary Research (IJMR), 6(4), 104.
Mombeuil, C., & Uhde, H. (2021). Relative convenience, relative advantage, perceived security, perceived privacy, and continuous use intention of China’s WeChat Pay: A mixed-method two-phase design study. Journal of Retailing and Consumer Services, 59(November 2020), 102384. https://doi.org/10.1016/j.jretconser.2020.102384
Mutiso, D. A., & Maguru, B. (2020). An Assessment of the Adoption of Cryptocurrency As a Mode of Payment By Smes in Kiambu County, Kenya. International Journal of Social Science and Economic Research, 5(7), 2000–2013. https://doi.org/10.46609/ijsser.2020.v05i07.023
Nabavi, A., Taghavi-Fard, M. T., Hanafizadeh, P., & Taghva, M. R. (2016). Information Technology Continuance Intention: A Systematic Literature Review. International Journal of E-Business Research, 12(1), 58–95. https://doi.org/10.4018/IJEBR.2016010104
Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System. https://bitcoin.org/bitcoin.pdf
Odoom, R., & Kosiba, J. P. (2020). Mobile money usage and continuance intention among micro enterprises in an emerging market – the mediating role of agent credibility. Journal of Systems and Information Technology, April. https://doi.org/10.1108/JSIT-03-2019-0062
Oliver, R. L. (1980). A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions. Journal of Marketing Research, 17(4), 460–469. https://doi.org/10.1177/002224378001700405
Onaolapo, S., & Oyewole, O. (2018). Performance expectancy, effort expectancy, and facilitating conditions as factors influencing smart phones use for mobile learning by postgraduate students of the University of Ibadan, Nigeria. Interdisciplinary Journal of E-Skills and Lifelong Learning, 14, 095–115.
Ooi, S. K., Ooi, C. A., Yeap, J. A. L., & Goh, T. H. (2020). Embracing Bitcoin: users’ perceived security and trust. Quality and Quantity, October. https://doi.org/10.1007/s11135-020-01055-w
Perkins, D. W. (2020). Cryptocurrency: The Economics of Money and Selected Policy Issues. https://crsreports.congress.gov
Rehman, M. H. ur, Salah, K., Damiani, E., & Svetinovic, D. (2019). Trust in Blockchain Cryptocurrency Ecosystem. IEEE Transactions on Engineering Management, 67(4), 1196–1212. https://doi.org/10.1109/tem.2019.2948861
Roos, C. (2015). The motivation and factors driving crypto-currency adoption in SMEs. Master Thesis, Gordon Institute of Business Science, University of Pretoria, November, 1–114.
Saadon, M. S. I., & Long, C. S. (2020). E-Wallet Acceptance among Undergraduates in Malaysia. TEST Engineering & Management. https://www.researchgate.net/publication/341895171
Shang, D., & Wu, W. (2017). Understanding mobile shopping consumers’ continuance intention. Industrial Management and Data Systems, 117(1), 213–227. https://doi.org/10.1108/IMDS-02-2016-0052
Singh, S. (2020). An integrated model combining ECM and UTAUT to explain users’ post-adoption behaviour towards mobile payment systems. Australasian Journal of Information Systems, 24(October), 0–27. https://doi.org/10.3127/ajis.v24i0.2695
Straub, D., & Gefen, D. (2004). Validation Guidelines for IS Positivist Research. Communications of the Association for Information Systems, 13(March). https://doi.org/10.17705/1cais.01324