Why do people use a mobile wallet? The case of fintech companies in Jordan
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DOIhttp://dx.doi.org/10.21511/imfi.21(2).2024.07
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Article InfoVolume 21 2024, Issue #2, pp. 89-102
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Understanding consumer intentions regarding mobile wallet (m-wallet) adoption is paramount in the mobile commerce landscape, particularly in cash-centric economies like Jordan. Despite efforts to shift toward digital payments, cash transactions remain prevalent, highlighting the need to explore m-wallet service adoption dynamics in Jordan.
This study aims to identify the factors influencing Jordanian consumers’ adoption of m-wallet services, focusing on the motivations and barriers. Utilizing the Unified Theory of Acceptance and Use of Technology (UTAUT2) as a theoretical foundation, the research integrates various models to assess technology acceptance. A questionnaire distributed among m-wallet users from fintech companies in Jordan garnered 421 responses, analyzed using the Smart PLS 3 software.
The findings indicate a positive impact of all variables on the propensity for m-wallet adoption in Jordan. Notably, perceived usefulness, ease of use, and facilitating conditions significantly influenced user decisions, evidenced by R-square values of 0.78%, 0.758% and 0.684%, respectively. Meanwhile, perceived value, security, privacy, and social influence had a moderate effect. The attractiveness of alternatives and attitudes towards m-wallet usage showed lesser impact, with R-square values at 26.7% and 22.8%, respectively, illustrating varied influences on adoption rates in determining consumer adoption of m-wallet services in Jordan.
This paper enhances research on mobile commerce in developing economies, focusing on Jordan. It explores the adoption of m-wallet services by fintech users, presenting a detailed model. The study provides valuable insights for advancing digital payment systems in this region.
- Keywords
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JEL Classification (Paper profile tab)O33, O32, O31
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References47
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Tables6
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Figures1
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- Figure 1. Hypothetical framework model
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- Table 1. Measurement model results
- Table 2. Fornell-Larcker criterion
- Table 3. Participants’ demographic characteristics
- Table 4. Hypothesis testing results
- Table 5. F square results
- Table A1. Questionnaire
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- Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
- Alalwan, A., Dwivedi, Y., Rana, N., & Simintiras, A. (2016). Jordanian consumers’ adoption of telebanking: Influence of perceived usefulness, trust and self-efficacy. International Journal of Bank Marketing, 34(5), 690-709.
- Alalwan, A., Dwivedi, Y., & Rana, N. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37, 99-110.
- Alswaigh, N., & Aloud, M. (2021). Factors affecting user adoption of e-payment services available in mobile wallets in Saudi Arabia. International Journal of Computer Science and Network Security, 21(6), 222-230.
- Amoroso, D., & Magnier-Watanabe, R. (2012). Building a research model for mobile wallet consumer adoption: The case of Mobile Suica in Japan. Journal of Theoretical and Applied Electronic Commerce Research, 7(1), 94-110.
- Anouze, A., & Alamro, A. (2020). Factors affecting intention to use e-banking in Jordan. International Journal of Bank Marketing, 38(1), 86-112.
- Boßow-Thies, S., & Albers, S. (2010), Application of PLS in marketing: Content strategies on the internet. In V. Esposito Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of partial least squares: Concepts, methods and applications (pp. 589-604). Springer.
- Cheong, J., Park, M., & Hwang, J. (2004). Mobile payment adoption in Korea: Switching from credit card [Unpublished doctoral dissertation]. Information and Communications University.
- Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295-336). Lawrence Erlbaum Associates.
- Cigdem, H., & Topcu, A. (2015). Predictors of instructors’ behavioral intention to use learning management system: A Turkish vocational college example. Computers in Human Behavior, 52, 22-28.
- Cohen J. (1988). Statistical power analysis for the behavioral sciences. Routledge Academic.
- Compeau, D., Higgins, C., & Huff, A. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS Quarterly, 23(2), 145-158.
- Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
- De Sena Abrahão, R., Moriguchi, S., & Andrade, D. (2016). Intention of adoption of mobile payment: An analysis in the light of the Unified Theory of Acceptance and Use of Technology (UTAUT). RAI Revista de Administração e Inovação, 13(3), 221-230.
- Deutsche Gesellschaft für Internationale Zusammenarbeit, & Central Bank of Jordan. (2017). Financial inclusion diagnostic study in Jordan 2017 (Synthesis report).
- Duarte, P., Silva, S., & Ferreira, M. (2018). How convenient is it? Delivering online shopping convenience to enhance customer satisfaction and encourage e-WOM. Journal of Retailing and Consumer Services, 44, 161-169.
- Falk, R. F., & Miller, N. B. (1992). A primer for soft modeling. University of Akron Press.
- Fornell, C., & Cha, J. (1994). Partial least squares. In R. Bagozzi (Ed.), Advanced methods of marketing research (pp. 52-87). Blackwell.
- Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Prentice Hall.
- Jaradat, M., & Mashaqba, A. (2014). Understanding the adoption and usage of mobile payment services by using TAM3. International Journal of Business Information Systems, 16(3), 271-296.
- Jayasingh, S., & Eze, U. C. (2009). An empirical analysis of consumer behavioral intention toward mobile coupons in Malaysia. International Journal of Business and Information, 4(2), 221-242.
- Jordan Payments and Clearing Company. (2024). About JoPACC.
- June, L., James, Y., & Chun-Sheng, Y. (2005). Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. Journal of Strategic Information Systems, 14(3), 245–268.
- Katebi, A., Homami, P., & Najmeddin, M. (2022). Acceptance model of precast concrete components in building construction based on Technology Acceptance Model (TAM) and Technology, Organization, and Environment (TOE) framework. Journal of Building Engineering, 45, Article 103518.
- Kaur, P., Dhir, A., Bodhi, R., Singh, T., & Almotairi, M. (2020). Why do people use and recommend m-wallets? Journal of Retailing and Consumer Services, 56, Article 102091.
- Keeney, R. L. (1999). The value of internet commerce to the customer. Management Science, 45(4), 533-542.
- Khalilzadeh, J., Ozturk, A., & Bilgihan, A. (2017). Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry. Computers in Human Behavior, 70, 460-474.
- Kim, H. W., Chan, H., & Gupta, S. (2007). Value-based adoption of mobile internet: An empirical investigation. Decision Support Systems, 43, 111-126.
- Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205-223.
- Kuo, Y.-F., Wu, C.-M., & Deng, W.-J. (2009). The relationships among service quality, perceived value, customer satisfaction, and post-purchase intention in mobile value-added services. Computers in Human Behavior, 25(4), 887-896.
- Lew, S., Tan, G. H., Loh, X.-M., Hew, J. J., & Ooi, K. B. (2020). The disruptive mobile wallet in the hospitality industry: An extended mobile technology acceptance model. Technology in Society, 63, Article 101430.
- Lu, J., Yao, J., & Yu, C.-S. (2005). Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. Journal of Strategic Information Systems, 14(3), 245-268.
- Luo, X., Li, H., Zhang, J., & Shim, J. (2010). Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: An empirical study of mobile banking services. Decision Support Systems, 49, 222-234.
- Madan, K., & Yadav, R. (2016). Behavioural intention to adopt mobile wallet: A developing country perspective. Journal of Indian Business Research, 8(3), 227-244.
- Pal, A., Herath, T., De, R., & Rao, H. (2021). Why do people use mobile payment technologies and why would they continue? An examination and implications from India. Research Policy, 50, Article 104228.
- Phonthanukitithaworn, C., Sellitto, C., & Fong, M. (2015). User intentions to adopt mobile payment services: A study of early adopters in Thailand. Journal of Internet Banking and Commerce, 20(1), 1-29.
- Shin, D. H. (2009). Towards an understanding of the consumer acceptance of mobile wallet. Computers in Human Behavior, 25(6), 1343-1354.
- Singh, N., & Sinha, N. (2020). How perceived trust mediates merchant’s intention to use a mobile wallet technology. Journal of Retailing and Consumer Services, 52, Article 101894.
- Singh, N., Sinha, N., & Liébana-Cabanillas, F. (2020). Determining factors in the adoption and recommendation of mobile wallet services in India: Analysis of the effect of innovativeness, stress to use and social influence. International Journal of Information Management, 50, 191-205.
- Tan, G. H., & Ooi, K. B. (2018). Gender and age: Do they really moderate mobile tourism shopping behavior? Telematics and Informatics, 35(6), 1617-1642.
- Venkatesh, V., & Davis, F. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186-204.
- Venkatesh, V., Morris, M., Davis, G., & Davis, F. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
- Venkatesh, V., Thong, J., & 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.
- Wang, J., & Gu, L. (2017). Why is WeChat Pay so popular? Issues in Information Systems, 18(4), 1-8.
- Wetzels, M., Odekerken-Schroder, G. & Van Oppen, C. (2009) Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Quarterly, 33(1), 177-195.
- Xu, F., & Du, J. (2018). Factors influencing users’ satisfaction and loyalty to digital libraries in Chinese universities. Computers in Human Behavior, 83, 64-72.
- Zhang, M. Y., & Dodgson, M. (2007). High-tech entrepreneurship in Asia: Innovation, industry and institutional dynamics in mobile payments. Edward Elgar Publishing.