FINTECH ADOPTION IN ACCOUNTING: A STUDY OF MILLENNIALS’ AND GEN-ZS’ READINESS IN MALAYSIA
DOI:
https://doi.org/10.55197/qjssh.v4i3.227Keywords:
fintech, UTAUT, fintech adoption, financial technologyAbstract
The objective of this study is to examine the readiness of Malaysian millennials and Gen-Zs for fintech adoption in accounting. This study developed the conceptual framework based on the Unified Theory of Acceptance and Use of Technology (UTAUT)’s four key fundamental constructs: performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC). The research utilized a quantitative method using an online survey to gather data from 108 respondents across Malaysia. The findings indicate that PE and FC are found to be key predictors of users’ fintech adoption intention (AI). It was also discovered that EE and SI have no significance on users’ fintech adoption intention (AI). Also, AI has a significant impact on users’ loyalty to keep using Fintech services. It is observed that PE is the strongest predictor of fintech adoption intention followed by FC, and AI does have a positive influence on consumers’ fintech loyalty due to the positive correlation between them. The result also demonstrates that adoption intention has a direct effect on users’ fintech loyalty. To encourage consumers to further continue using fintech services in the future, it is necessary to build a consumer loyalty base. The presence of one may attract new users to adopt the fintech services hence forming loyalty. Overall, this study may help gauge a portion of Malaysian millennials and Gen-Z’s awareness, adaptability, and acceptance of fintech in accounting.
References
Abdennadher, S., Grassa, R., Abdulla, H., Alfalasi, A. (2022): The effects of blockchain technology on the accounting and assurance profession in the UAE: an exploratory study. – Journal of Financial Reporting and Accounting 20(1): 53-71.
Alkhwaldi, A.F., Alharasis, E.E., Shehadeh, M., Abu-AlSondos, I.A., Oudat, M.S., Bani Atta, A.A. (2022): Towards an Understanding of FinTech Users’ Adoption: Intention and e-Loyalty Post-COVID-19 from a Developing Country Perspective. – Sustainability 14(19): 23p.
Al-Okaily, M., Alqudah, H., Al-Qudah, A.A., Al-Qadi, N.S., Elrehail, H., Al-Okaily, A. (2022): Does financial awareness increase the acceptance rate for financial inclusion? An empirical examination in the era of digital transformation. – Kybernetes 21p.
Alvesson, M., Kärreman, D. (2007): Constructing mystery: Empirical matters in theory development. – Academy of Management Review 32(4): 1265-1281.
Andrade, C. (2020): The limitations of online surveys. – Indian Journal of Psychological Medicine 42(6): 575-576.
Bonyuet, D. (2020): Overview and impact of blockchain on auditing. – International Journal of Digital Accounting Research 20: 31-43.
Cai, C.W. (2021): Triple‐entry accounting with blockchain: How far have we come? – Accounting & Finance 61(1): 71-93.
Desplebin, O., Lux, G., Petit, N. (2021): To be or not to be: blockchain and the future of accounting and auditing. – Accounting Perspectives 20(4): 743-769.
Faccia, A., Petratos, P. (2021): Blockchain, enterprise resource planning (ERP) and accounting information systems (AIS): Research on e-procurement and system integration. – Applied Sciences 11(15): 17p.
George, D., Mallery, P. (2019): IBM SPSS Statistics 26 step by step. – Routledge 402p.
Ghozali, I. (2013): Applikasi analisis multivariate dengan program IBM SPSS 21 Update PLS regresi. – Yogyakarta Badan Penerbit Undip 465p.
Hair Jr, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M. (2021): A primer on partial least squares structural equation modeling (PLS-SEM). – SAGE Publications 384p.
Herath, S.K., Woods, D. (2021): Impacts of big data on accounting. – The Business and Management Review 12(2): 195-203.
Khotinskay, G. (2019): Fin Tech: Fundamental theory and empirical features. – The European Proceedings of Social & Behavioural Sciences 8p.
Lu, Y., Yang, S., Chau, P.Y., Cao, Y. (2011): Dynamics between the trust transfer process and intention to use mobile payment services: A cross-environment perspective. – Information & Management 48(8): 393-403.
Matondang, Z. (2009): Validitas dan reliabilitas suatu instrumen penelitian. – Jurnal Tabularasa 6(1): 87-97.
Moreira-Santos, D., Au-Yong-Oliveira, M., Palma-Moreira, A. (2022): Fintech Services and the Drivers of Their Implementation in Small and Medium Enterprises. – Information 13(9): 25p.
Senyo, P.K., Osabutey, E.L. (2020): Unearthing antecedents to financial inclusion through FinTech innovations. – Technovation 98: 14p.
Shahzad, A., Zahrullail, N., Akbar, A., Mohelska, H., Hussain, A. (2022): COVID-19’s Impact on Fintech Adoption: Behavioral Intention to Use the Financial Portal. – Journal of Risk and Financial Management 15(10): 18p.
Tun-Pin, C., Keng-Soon, W.C., Yen-San, Y., Pui-Yee, C., Hong-Leong, J.T., Shwu-Shing, N. (2019): An adoption of fintech service in Malaysia. – South East Asia Journal of Contemporary Business 18(5): 134-147.
United Overseas Bank (2019): FinTech in ASEAN 2019: From start-up to scale-up. – United Overseas Bank Official Portal. Retrieved from:
https://www.uobgroup.com/techecosystem/news-insights-fintech-in-asean-2019.html
Venkatesh, V., Thong, J.Y., Xu, X. (2012): Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. – MIS Quarterly 36(1): 157-178.
Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D. (2003): User acceptance of information technology: Toward a unified view. – MIS Quarterly 425-478.
Wang, Y. (2021): The application of Fintech in accounting. – 2nd International Conference on World Economy and Project Management (WEPM 2021) 6p.
Williams, B., Halloin, C., Löbel, W., Finklea, F., Lipke, E., Zweigerdt, R., Cremaschi, S. (2020): Data-driven model development for cardiomyocyte production experimental failure prediction. – In Computer Aided Chemical Engineering, Elsevier 48: 1639-1644.
Xie, J., Ye, L., Huang, W., Ye, M. (2021): Understanding FinTech platform adoption: impacts of perceived value and perceived risk. – Journal of Theoretical and Applied Electronic Commerce Research 16(5): 1893-1911.
Yohanes, K., Junius, K., Saputra, Y., Sari, R., Lisanti, Y., Luhukay, D. (2020): Unified Theory of Acceptance and Use of Technology (UTAUT) model perspective to enhance user acceptance of fintech application. – In 2020 International Conference on Information Management and Technology (ICIMTech), IEEE 6p.
Zhang, Y., Xiong, F., Xie, Y., Fan, X., Gu, H. (2020): The impact of artificial intelligence and blockchain on the accounting profession. – IEEE Access 8: 110461-110477.
Zheng, A.H.Y., Ab-Rahim, R., Jing, A.H.Y. (2022): Examining the Fintech Ecosystem of ASEAN-6 Countries. – Asia-Pacific Social Science Review 22(2): 13p.