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http://dx.doi.org/10.14400/JDC.2020.18.2.023

Determinants of Behavioral Intention and Usage of Mobile Money Services in Ethiopia  

Bereket, Tiru Beza (Communication and Information Technology (MCIT))
Hwang, Gee-Hyun (Office of International Affairs/Graduate School of Information Science, Soongsil University)
Publication Information
Journal of Digital Convergence / v.18, no.2, 2020 , pp. 23-35 More about this Journal
Abstract
Mobile Money is a key factor of financial inclusion that can revolutionize the financial service delivery and hence enhance access to finance in emerging economies, especially the East African countries. This study therefore aims to study the determinants of individual's behavioral intention and usage of Mobile Money services in Ethiopia by usiing the UTAUT2 model. The research model was tested by sampling 200 respondents from different areas of Ethiopia. The analysis results found that Government Support, Facilitating Conditions, Performance Expectancy, Trust and Effort Expectancy are the key factors that affect the usage of Mobile Money service, while Lower Transaction Cost factors and Social Influence were not statistically significant. The findings provide useful information that only government's active efforts and support to promote mobile money services, through appropriate policies and regulations rather than lower transaction cost, can facilitate the adoption and dissemination of such services in Ethiopia.
Keywords
Mobile Money Services; UTAUT2; Behavioral Intention; Usage Behavior; Ethiopia;
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Times Cited By KSCI : 10  (Citation Analysis)
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1 McKinsey Global Institute. (2016). Digital Finance For All: Powering Inclusive Growth in Emerging Economies. Full-report, September.
2 ITU. (2016). The Digital financial services ecosystem. Technical Report, ITU Focus Group. DIO: from:http://www.un.org/esa/ffd/wp-content/uploads/2016/01/Digital-Financial-Inclusion_ITU_IATF-Issue-Brief.pdf
3 P. K. Ozili. (2018). Impact of digital finance on financial inclusion and stability. Borsa Istanbul Review, 18(4), 329-340.   DOI
4 K. Donovan. (2012). Mobile money for financial inclusion. Information and Communications for Development, 61(1), 61-73.
5 J. K. Winn & L. D. Koker. (2013). Introduction to Mobile Money in Developing Countries: Financial Inclusion and Financial Integrity Conference Special Issue. Washington Journal of Law, Technology and Arts, 8(3), 155-164.
6 T. B. Bereket. (2018). A Study on Factors Affecting the Usage of Mobile Money - Focused on Ethiopia. Master Thesis, Soongsil University, Seoul.
7 J. Firpo. (2009). E-Money-Mobile Money- Mobile Banking -What's the Difference. Private Sector Development. DOI:http://blogs.worldbank.org/psd/e-money-mobile-money-mobile-banking-what-s-the-difference
8 GSMA. (2016). State of the Industry Report on Mobile Money. Decade Edition: 2006-2016. DID:https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2017/03/GSMA_State-of-the-Industry-Report-on-Mobile-Money_2016.pdf
9 V. Venkatesh, M. G. Morris, G. B. Davis, & F. D. Davis.(2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.   DOI
10 V. Venkatesh, J. Y. Thong & X. Xu. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178.   DOI
11 V. Bhatiasevi. (2016). An extended UTAUT model to explain the adoption of mobile banking. Information Development, 32(4), 799-814.   DOI
12 A. S. Yang. (2009). Exploring adoption difficulties in mobile banking services. Canadian Journal of Administrative Sciences, 26(2), 136-149.   DOI
13 T. Zhou, , Y. Lu, & B. Wang.(2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in human behavior, 26(4), 760-767.   DOI
14 P. J. Chogo, & E. Sedoyeka.(2014). Exploring Factors Affecting Mobile Money Adoption in Tanzania. International Journal of Computing &ICT Research, 8(2), 53-64.
15 L. Ismail, M. B. Moya, K. Bwiino, & K. Ismael.(2017). Examining determinants of behavioural intention in adoption of mobile money transfer services in Uganda. ICTACT Journal on Management Studies, 3(1), 433-439.   DOI
16 P. Tobbin. (2012). Towards a model of adoption in mobile banking by the unbanked: a qualitative study. Info, 14(5), 74-88.   DOI
17 P. J. Chogo & E. Sedoyeka. (2014). Exploring Factors Affecting Mobile Money Adoption in Tanzania. International Journal of Computing & ICT Research, 8(2), 53-64.
18 Chuchuen, C. (2016). The Perception of Mobile Banking Adoption: The Study of Behavioral, Security, and Trust in Thailand. International Journal of Social Science and Humanity, 6(7), 547-550.   DOI
19 E. Berger & C. Nakata. (2013). Implementing Technologies for Financial Service Innovations in Base of the Pyramid Markets: Implementing Technologies for Financial Service Innovations. Journal of Product Innovation Management, 30(6), 1199-1211.   DOI
20 E Berger, & C. Nakata.(2013). Implementing Technologies for Financial Service Innovations in Base of the Pyramid Markets: Implementing Technologies for Financial Service Innovations. Journal of Product Innovation Management, 30(6), 1199-1211.   DOI
21 J. Hair, W. Blake, B. Babin & R. Tatham.(2006). Multivariate Data Analysis. New Jersey: Prentice Hall.
22 K. B. Kim & J. Y. Yun. (2015). Comparison and Analysis on Mobile Payment in terms of Security : Survey. Journal of IT Convergence Society for SMB, 5(3), 15-20.
23 C. H. Jung, S. H. Namn. (2014). Cloud Computing Acceptance at Individual Level Based on Extended UTAUT. Journal of Digital Convergence, 12(1), 287-294.   DOI
24 C. Chuchuen. (2016). The Perception of Mobile Banking Adoption: The Study of Behavioral, Security, and Trust in Thailand. International Journal of Social Science and Humanity, 6(7), 547-550.   DOI
25 S. T. K., Myo & G. H. Hwang. (2017). Effect of Mobile Devices on the Use Intention and Use of Mobile Banking Service in Myanmar. Journal of digital convergence, 15(6), 71-82.   DOI
26 A. Y. L. Chong, F. T. Chan & K. B. Ooi. (2012). Predicting consumer decisions to adopt mobile commerce: Cross country empirical examination between China and Malaysia. Decision Support Systems, 53(1), 34-43.   DOI
27 A. Violaine & G. H. Hwang. (2019). Key Factors Affecting Students' Satisfaction and Intention to Use e-Learning in Rwanda's Higher Education. Journal of digital convergence, 17(5), 99-108.   DOI
28 S. H. Lee & D. W. Lee. (2015). FinTech-Conversions of Finance Industry based on ICT. Journal of the Korea Convergence Society, 6(3), 97-102.   DOI
29 C. H. Yoon & G. D. Choi. (2014). The Effects of National Culture on Ethical Decision-Making in the Internet Context : An Exploratory Analysis. Journal of digital convergence, 12(12), 23-36.   DOI
30 S. S. Shin, Y. S. Jeong & Y. J An. (2015). A Study of Analysis and Response and Plan for National and International Security Practices using Fin-Tech Technologies. Journal of IT Convergence Society for SMB, 5(3), 1-7.
31 H. J. Lee, O. C. Na, S. Y. Sung. & H. B. Chang. (2015). A Design on Security Governance Framework for Industry Convergence Environment. Journal of the Korea Convergence Society, 6(4), 33-40.   DOI
32 L. M. Aliyeva1 & G. H. Hwang. (2019). The Model to Implement the Cyber Security Policy and Strategy for Azerbaijan Information System. Journal of digital convergence, 17(5), 23-31.   DOI