Cryptocurrency as a Gateway for Cross-Border Mobile Money Services: Evidence from Soft Deal Trading Ltd, Buea, Cameroon

This study examines the implications of three major cryptocurrencies (Bitcoin, Ethereum, and Tether) for cross-border mobile money services, using primary data from 69 staff and active cryptocurrency users at Soft Deal Trading Ltd in Buea, Cameroon. Structured questionnaires were administered and a multiple linear regression model was estimated. The model explains 29.2% of the adjusted variance in mobile money service outcomes (adjusted R² = 0.292; F = 10.344; p < 0.001). Bitcoin exerts a significant positive effect (β = 0.515; p < 0.001), consistent with its deep market penetration and user recognition. Tether likewise has a significant positive effect (β = 0.412; p = 0.001), driven by its price stability, minimal inter-wallet transfer charges, and broad cross-border acceptability. Ethereum, by contrast, carries a significant negative effect (β = −0.436; p = 0.002), attributable to low user familiarity and prohibitively high network gas fees. The findings suggest that Bitcoin and Tether represent viable complements to conventional mobile money for cross-border payments in the Cameroonian context, while Ethereum's adoption barriers must be addressed before it can contribute positively to such services.

Cross-border transactions; Bitcoin; Ethereum; Tether; Cameroon

1. Baek, C., & Elbeck, M. (2015). Bitcoins as an investment or speculative vehicle? A first look. Applied Economics Letters, 22(1), 30–34. [Google Scholar] [Crossref]

2. CGAP. (2012). Mobile money in Côte d'Ivoire: An overview. Consultative Group to Assist the Poor. [Google Scholar] [Crossref]

3. Cheah, E.-T., & Fry, J. (2015). Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin. Economics Letters, 130, 32–36. [Google Scholar] [Crossref]

4. Chu, J., Nadarajah, S., & Chan, S. (2015). Statistical analysis of the exchange rate of Bitcoin. PLOS ONE, 10(7), e0133678. [Google Scholar] [Crossref]

5. Chu, J., Chan, S., Nadarajah, S., & Osterrieder, J. (2017). GARCH modelling of cryptocurrencies. Journal of Risk and Financial Management, 10(4), 17. [Google Scholar] [Crossref]

6. Communications Commission of Kenya. (2013). Annual report 2012–2013. CCK. [Google Scholar] [Crossref]

7. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. [Google Scholar] [Crossref]

8. Dyhrberg, A. H. (2016). Bitcoin, gold and the dollar , A GARCH volatility analysis. Finance Research Letters, 16, 85–92. [Google Scholar] [Crossref]

9. Feng, W., Wang, Y., & Zhang, Z. (2018). Can cryptocurrencies be a safe haven? A tail risk perspective analysis. Applied Economics, 50(44), 4745–4762. [Google Scholar] [Crossref]

10. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley. [Google Scholar] [Crossref]

11. GSMA. (2014). State of the industry: Mobile financial services for the unbanked. GSMA Intelligence. [Google Scholar] [Crossref]

12. Jani, S. (2018). The growth of cryptocurrency in India: Its challenges and potential impacts on legislation. ResearchGate. [Google Scholar] [Crossref]

13. Kashyap, S., & Chand, K. (2018). Impact of cryptocurrency in India. International Journal of Law, Management & Humanities, 2(1), 1–10. [Google Scholar] [Crossref]

14. Katsiampa, P. (2017). Volatility estimation for Bitcoin: A comparison of GARCH models. Economics Letters, 158, 3–6. [Google Scholar] [Crossref]

15. Katsiampa, P., Corbet, S., & Lucey, B. (2018). Volatility spillover effects in leading cryptocurrencies: A BEKK-MGARCH analysis. Finance Research Letters, 29, 68–74. [Google Scholar] [Crossref]

16. Klein, T., Thu, H. P., & Walther, T. (2018). Bitcoin is not the new gold , A comparison of volatility, correlation, and portfolio performance. International Review of Financial Analysis, 59, 105–116. [Google Scholar] [Crossref]

17. Li, X., & Wang, C. A. (2016). The technology and economic determinants of cryptocurrency exchange rates: The case of Bitcoin. Decision Support Systems, 95, 49–60. [Google Scholar] [Crossref]

18. Mukhopadhyay, U., Skjellum, A., Hambolu, O., Oakley, J., Yu, L., & Brooks, R. (2016). A brief survey of cryptocurrency systems. In Proceedings of the 14th Annual Conference on Privacy, Security and Trust (PST) (pp. 745–752). IEEE. [Google Scholar] [Crossref]

19. Ngimanang, A. V. (2019). Microfinance services and the growth of small and medium size enterprises: Evidence from the Community Credit Company in the Douala Municipality, Cameroon. International Journal of Business Strategies, 5(1), 27–50. [Google Scholar] [Crossref]

20. Osterrieder, J., & Lorenz, J. (2017). A statistical risk assessment of Bitcoin and its extreme tail behaviour. Annals of Financial Economics, 12(1), 1750003. [Google Scholar] [Crossref]

21. Phillip, A., Chan, J., & Peiris, S. (2018). A new look at cryptocurrencies. Economics Letters, 163, 6–9. [Google Scholar] [Crossref]

22. Singh, A. K., & Singh, K. V. (2018). Cryptocurrency in India , Its effect and future on the economy with special reference to Bitcoin. Journal of Advance Management Research, 6(2), 262–274. [Google Scholar] [Crossref]

23. Sogbodjor, A. (2015). The effect of technology on the performance of MTN in West Africa. Journal of African Business and Economics, 3(1), 45–58. [Google Scholar] [Crossref]

24. Vejacka, M. (2014). Basic aspects of cryptocurrencies. Journal of Economy, Business and Financing, 2(2), 75–83. [Google Scholar] [Crossref]

25. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204. [Google Scholar] [Crossref]

26. Yamane, T. (1973). Statistics: An introductory analysis (3rd ed.). Harper & Row. [Google Scholar] [Crossref]

27. Zhang, W., Wang, P., Li, X., & Shen, D. (2018). The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average. Physica A: Statistical Mechanics and its Applications, 510, 658–670. [Google Scholar] [Crossref]