Digitization adoption in developing countries: Investigating the factors affecting intention to use digital currency in Vietnam

Thi Thuy An Ngo, Thi Ngoc Thuy Tran, Thi Mai Xuan Bui, Nhat Quynh Le

Article ID: 5967
Vol 8, Issue 7, 2024

VIEWS - 249 (Abstract) 134 (PDF)

Abstract


In the contemporary landscape characterized by technological advancements and a progressive economic environment, the utilization of currency has undergone a paradigm shift. Despite the growing prevalence of digital currency, its adoption among the Vietnamese population faces several challenges, including limited financial literacy, concerns over security, and resistance to change from traditional cash-based transactions. This research aims to identify these challenges and propose solutions to encourage the widespread use of digital currency in Vietnam. This research adopts a quantitative approach, utilizing Likert scale questionnaires, with a dataset of 330 records. The interrelationships among variables are analyzed using partial least squares structural equation modeling (PLS-SEM). The analysis results substantiate the viability of the research model, confirming the hypotheses. The findings demonstrate a positive relationship and the significance impact of factors such as perceived usefulness (PU), perceived ease of use (PEOU), perceived trust (PT), social influence (SI), openness to innovation (OI), and financial knowledge (FK) to intention to use digital currency (IUDC). Thereby aiming to inform policymakers, industry stakeholders, and the wider community, fostering a deeper understanding of consumer behavior and providing solutions to enhance the adoption of digital currency in the evolving landscape of digital finance.


Keywords


digital currency; intention to use; technology acceptance model (tam); social influence

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References


Acharya, A. S., Prakash, A., Saxena, P., et al. (2013). Sampling: why and how of it? Indian Journal of Medical Specialities, 4(2). https://doi.org/10.7713/ijms.2013.0032

Alfansi, L., & Daulay, M. Y. I. (2021). Factor affecting the use of e-money in millennial generation: Research model UTAUT 2. Jurnal Manajemen Dan Pemasaran Jasa, 14(1), 109–122. https://doi.org/10.25105/jmpj.v14i1.8212

Alharbi, A., & Sohaib, O. (2021). Technology Readiness and Cryptocurrency Adoption: PLS-SEM and Deep Learning Neural Network Analysis. IEEE Access, 9, 21388–21394. https://doi.org/10.1109/access.2021.3055785

Al-Maroof, R. A. S., & Al-Emran, M. (2018). Students Acceptance of Google Classroom: An Exploratory Study using PLS-SEM Approach. International Journal of Emerging Technologies in Learning (IJET), 13(06), 112. https://doi.org/10.3991/ijet.v13i06.8275

Angosto, S., García-Fernández, J., Valantine, I., et al. (2020). The Intention to Use Fitness and Physical Activity Apps: A Systematic Review. Sustainability, 12(16), 6641. https://doi.org/10.3390/su12166641

Arias-Oliva, M., Pelegrín-Borondo, J., & Matías-Clavero, G. (2019). Variables Influencing Cryptocurrency Use: A Technology Acceptance Model in Spain. Frontiers in Psychology, 10. https://doi.org/10.3389/fpsyg.2019.00475

Barry, M., Jan, M. T. (2018). Factors Influencing the Use of M-Commerce: An Extended Technology Acceptance Model Perspective. International Journal of Economics, Management and Accounting, 26(1), 157-183. https://doi.org/10.31436/ijema.v26i1.502

Bloomenthal, A. (2023). What is electronic money or eMoney? Available online: https://www.investopedia.com/terms/e/electronic-money.asp (accessed on 6 January 2024).

Bregashtian, B., & S.E., M.M., et al. (2021). The Effect of Perceived Ease of Use, Usefulness and Risk on Intention to Use the Go-Food Application in Surabaya and Sidoarjo. KnE Social Sciences. https://doi.org/10.18502/kss.v5i5.8807

Çelik, Z., & Dülek, B. (2022). Investigation of consumers’ intentions to use digital currency for shopping. Dicle Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 12(23), 284–303. https://doi.org/10.53092/duiibfd.1029912

Cohen, J. (2013). Statistical Power Analysis for the Behavioral Sciences. Routledge. https://doi.org/10.4324/9780203771587

Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008

Do, N. H., Tham, J., Azam, S. M. F., et al. (2020). The effects of factors influencing on user behavior intention to use mobile payment: Evidence from Cambodia. International Journal of Data and Network Science, 213–224. https://doi.org/10.5267/j.ijdns.2019.12.004

Dodgson, M., Gann, D., Wladawsky-Berger, I., et al. (2015). Managing Digital Money. Academy of Management Journal, 58(2), 325–333. https://doi.org/10.5465/amj.2015.4002

Erwanti, N., & Prasetyani, H. (2023). Investigating Intention to Use Central Bank Digital Currency in Indonesia. Journal of Information Systems and Informatics, 5(4), 1461–1471. https://doi.org/10.51519/journalisi.v5i4.598

Fahiraningrum, T. O., & Richard, R. (2020). The Analysis of Factors That Influences People Intention to Use in Electronic Money. PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic, 8(2), 83–90. https://doi.org/10.33558/piksel.v8i2.2271

Fintech News Singapore. (2020). ABD: Low financial literacy hampering fintech adoption in Vietnam. Available online: https://fintechnews.sg/45609/vietnam/abd-low-financial-literacy-hampering-fintech-adoption-in-vietnam/ (accessed on 16 January 2024).

Fenwick, M., Van Uytsel, S., & Ying, B. (2020). Regulating FinTech in Asia. In: Perspectives in Law, Business and Innovation. Springer Singapore. https://doi.org/10.1007/978-981-15-5819-1

Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39. https://doi.org/10.2307/3151312

Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101–107. https://doi.org/10.1093/biomet/61.1.101

Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge Management: An Organizational Capabilities Perspective. Journal of Management Information Systems, 18(1), 185–214. https://doi.org/10.1080/07421222.2001.11045669

Hair, J. F., & Sarstedt, M. (2019). Factors versus Composites: Guidelines for Choosing the Right Structural Equation Modeling Method. Project Management Journal, 50(6), 619–624. https://doi.org/10.1177/8756972819882132

Hair, J. F., Hult, G. T. M., Ringle, C. M., et al. (2017). Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods. Journal of the Academy of Marketing Science, 45(5), 616–632. https://doi.org/10.1007/s11747-017-0517-x

Hair, J. F., Hult, G. T. M., Ringle, C. M., et al. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R. In Classroom Companion: Business. Springer International Publishing. https://doi.org/10.1007/978-3-030-80519-7

Hair, J. F., Risher, J. J., Sarstedt, M., et al. (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

Hermawan, A., Gunardi, A., & Sari, L. M. (2022). Intention to Use Digital Finance MSMEs: The Impact of Financial Literacy and Financial Inclusion. Jurnal Ilmiah Akuntansi Dan Bisnis, 17(1). https://doi.org/10.24843/jiab.2022.v17.i01.p12

Hong, C., Choi, H., Choi, E.-K., & Joung, H.-W. (2021). Factors affecting customer intention to use online food delivery services before and during the COVID-19 pandemic. Journal of Hospitality and Tourism Management, 48, 509–518. https://doi.org/10.1016/j.jhtm.2021.08.012

Karim, M., Haque, A., Ulfy, M. A., et al. (2020). Factors influencing the use of e-wallet as a payment method among Malaysian young adults. International Journal of Business and Management, 3, 1-12. https://doi.org/10.37227/jibm-2020-2-21

Kasilingam, D. L. (2020). Understanding the attitude and intention to use smartphone chatbots for shopping. Technology in Society, 62, 101280. https://doi.org/10.1016/j.techsoc.2020.101280

Kemarauwana, M., & Darmawan, D. (2020). Perceived ease of use contribution to behavioral intention in digital payment. Journal of Science, Technology and Society (SICO), 1(1), 1-4.

Kock, N., & Hadaya, P. (2016). Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods. Information Systems Journal, 28(1), 227–261. Portico. https://doi.org/10.1111/isj.12131

Kumar, S., & Karlina, L. (2020). Intention to Use Credit Card among College Students in Greater Jakarta. Journal of Applied Accounting and Finance, 4(1), 49. https://doi.org/10.33021/jaaf.v4i1.1227

Kumari, V., Bala, P. K., & Chakraborty, S. (2023). An Empirical Study of User Adoption of Cryptocurrency Using Blockchain Technology: Analysing Role of Success Factors like Technology Awareness and Financial Literacy. Journal of Theoretical and Applied Electronic Commerce Research, 18(3), 1580–1600. https://doi.org/10.3390/jtaer18030080

Ma, C., Jin, Z., Mei, Z., et al. (2022). Internet of Things Background: An Empirical Study on the Payment Intention of Central Bank Digital Currency Design. Mobile Information Systems, 2022, 1–12. https://doi.org/10.1155/2022/4846372

Mailizar, M., Almanthari, A., & Maulina, S. (2021). Examining Teachers’ Behavioral Intention to Use E-learning in Teaching of Mathematics: An Extended TAM Model. Contemporary Educational Technology, 13(2), ep298. https://doi.org/10.30935/cedtech/9709

Maulana, A., Dasa Putri, A., & Yulia. (2019). Development of digital currency technology. Journal of Physics: Conference Series, 1175, 012205. https://doi.org/10.1088/1742-6596/1175/1/012205

Mullan, P. C. (2014). The Digital Currency Challenge. Palgrave Macmillan US. https://doi.org/10.1057/9781137382559

Musleh Al-Sartawi, A. M. A., Abd Wahab, M. H., Hussainey, K. (2024). Global Economic Revolutions: Big Data Governance and Business Analytics for Sustainability. In: Communications in Computer and Information Science. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-50518-8

Nguyen, H. Y. (2020). Fintech in Vietnam and Its Regulatory Approach. In: Fenwick, M., Van Uytsel, S., Ying, B. (editors). Regulating FinTech in Asia. Perspectives in Law, Business and Innovation. Springer. https://doi.org/10.1007/978-981-15-5819-1_7

Nugroho, A., Najib, M., & Simanjuntak, M. (2018). Factors Affecting Consumer Interest In Electronic Money Usage With Theory Of Planned Behavior (TPB). Journal of Consumer Sciences, 3(1), 15. https://doi.org/10.29244/jcs.3.1.15-27

Park, J., Amendah, E., Lee, Y., et al. (2018). M‐payment service: Interplay of perceived risk, benefit, and trust in service adoption. Human Factors and Ergonomics in Manufacturing & Service Industries, 29(1), 31–43. Portico. https://doi.org/10.1002/hfm.20750

Prayidyaningrum, S., & Djamaludin, M. D. (2016). Theory of Planned Behavior to Analyze the Intention to Use the Electronic Money. Journal of Consumer Sciences, 1(2), 1. https://doi.org/10.29244/jcs.1.2.1-12

Saif Almuraqab, N. A. (2020). Predicting determinants of the intention to use digital currency in the UAE: An empirical study. The electronic journal of information systems in developing countries, 86(3). Portico. https://doi.org/10.1002/isd2.12125

Sarstedt, M., Ringle, C. M., Smith, D., et al. (2014). Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers. Journal of Family Business Strategy, 5(1), 105–115. https://doi.org/10.1016/j.jfbs.2014.01.002

Sasongko, D. T., Handayani, P. W., & Satria, R. (2022). Analysis of factors affecting continuance use intention of the electronic money application in Indonesia. Procedia Computer Science, 197, 42–50. https://doi.org/10.1016/j.procs.2021.12.116

Shahzad, F., Xiu, G., Wang, J., et al. (2018). An empirical investigation on the adoption of cryptocurrencies among the people of mainland China. Technology in Society, 55, 33–40. https://doi.org/10.1016/j.techsoc.2018.05.006

Shanmugam, M., Sun, S., Amidi, A., et al. (2016). The applications of social commerce constructs. International Journal of Information Management, 36(3), 425–432. https://doi.org/10.1016/j.ijinfomgt.2016.01.007

Shetu, S. N., Islam, Md. M., & Promi, S. I. (2022). An Empirical Investigation of the Continued Usage Intention of Digital Wallets: The Moderating Role of Perceived Technological Innovativeness. Future Business Journal, 8(1). https://doi.org/10.1186/s43093-022-00158-0

Simarmata, M. T. A., & Hia, I. J. (2020). The role of personal innovativeness on behavioral intention of information technology. Journal of Economics and Business, 1(2), 18–29. https://doi.org/10.36655/jeb.v1i2.169

Stolper, O. A., & Walter, A. (2017). Financial literacy, financial advice, and financial behavior. Journal of Business Economics, 87(5), 581–643. https://doi.org/10.1007/s11573-017-0853-9

Tronnier, F., & Kakkar, S. (2021). Would You Pay with a Digital Euro? Investigating Usage Intention in Central Bank Digital Currency. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4194173

Vietnam News. (2023). Banking sector invests big in digital transformation. Available online: https://vietnamnews.vn/economy/1537695/banking-sector-invests-big-in-digital-transformation.html (accessed on 11 January 2024).

Viñuela, C., Sapena, J., & Wandosell, G. (2020). The Future of Money and the Central Bank Digital Currency Dilemma. Sustainability, 12(22), 9697. https://doi.org/10.3390/su12229697

We Are Social. (2022). Digital 2022: Another year of bumper growth. Available online: https://wearesocial.com/uk/blog/2022/01/digital-2022-another-year-of-bumper-growth-2/ (accessed on 9 January 2024).

Wong, K. K. (2013). Partial least square structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24, 1-32.

Wu, G., Yang, J., & Hu, Q. (2022). Research on factors affecting people’s intention to use digital currency: Empirical evidence from China. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.928735

Yang, M., Mamun, A. A., Mohiuddin, M., et al. (2021). Cashless Transactions: A Study on Intention and Adoption of e-Wallets. Sustainability, 13(2), 831. https://doi.org/10.3390/su13020831

Yizhen, W., Jamal, A. A. A. (2022). The adoption of digital currency electronic payment in China. Malaysian Journal of Business and Economics, 9(2). https://doi.org/10.51200/mjbe.v9i2.3929

Yuen, K. F., Cai, L., Qi, G., et al. (2020). Factors influencing autonomous vehicle adoption: an application of the technology acceptance model and innovation diffusion theory. Technology Analysis & Strategic Management, 33(5), 505–519. https://doi.org/10.1080/09537325.2020.1826423




DOI: https://doi.org/10.24294/jipd.v8i7.5967

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