Behavioral intentions towards the use of digital wallets

Authors: 
Jonathan C Gano-an, Xueting Pan
DOI Number: 
http://doi.org/10.31039/jomeino.2024.8.2.1
Abstract: 
The global financial ecosystem has been continuously transformed by digital transactions in today's technologically advanced world and electronic wallets have become essential to the lives of the increasing population. This study used a structured questionnaire and surveyed 606 bank customers in Yunnan, China, in order to examine the behavioral intentions on the use digital wallet. This study used partial-least square structural equation modeling to test five structural relationships. Findings showed that the respondent’s perception on perceived ease of use, perceived usefulness, awareness of digital wallets, and behavioral intentions on the use of digitals wallets were described as high. In terms of correlational statistics, all constructs are correlated, however, it was noted that digital wallet awareness and perceived usefulness have the lowest correlation. Furthermore, in terms of regression model test, all paths (PEU>IU, PU>IU, PR>IUU, AW>IU, and IU > BI) were found to be statistically significant. This indicates that perceived ease of use, perceived usefulness, perceived ease of use, perceived risks, awareness, and intention to use significantly influence behavioral intention. Hence, all hypotheses set were significant and supported. Findings also suggest that Fintech companies may continue invest to making sure that e-wallets are less risky and finally, leveraging the continuous popularity on the use of digital wallets is a way to promote financial inclusity among the population of this region.
Keywords: 
E-wallet; Digital Payments; Behavioral Intentions; Fintech
Full Text: 
File download
References: 

Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control: From cognition to behavior (pp. 11-39). Berlin, Heidelberg: Springer Berlin Heidelberg. Anshari, M., Arine, M. A., Nurhidayah, N., Aziyah, H., & Salleh, M. H. A. (2021). Factors influencing individual in adopting eWallet. Journal of Financial Services Marketing, 26, 10-23. Carrero, I., & Valor, C. (2012). CSR‐labelled products in retailers' assortment: A comparative study of British and Spanish retailers. International Journal of Retail & Distribution Management, 40(8), 629-652. Chawla, D., & Joshi, H. (2019). Consumer attitude and intention to adopt mobile wallet in India–An empirical study. International Journal of Bank Marketing, 37(7), 1590-1618. Chen, Z., Zhu, L., Jiang, P., Zhang, C., Gao, F., He, J., ... & Zhang, Y. (2022). Blockchain meets covert communication: A survey. IEEE Communications Surveys & Tutorials, 24(4), 2163-2192. Chin, W. W. (2009). How to write up and report PLS analyses. In Handbook of partial least squares: Concepts, Methods and Applications (pp. 655-690). Berlin, Heidelberg: Springer Berlin Heidelberg. CoinMarketCap. (2018). Digital Currencies in the World. Retrieved from https://coinmarketcap.com/historical/ Coolidge, F. L. (2006). Statistics: A gentle introduction (2nd ed.). Thousand Oaks, CA: Sage. Creswell, J. W., & Plano Clark, V. L. (2007). Designing and conducting mixed methods research. SAGE Publications. Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Doctoral dissertation). MIT Sloan School of Management. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. Fang, C. C., Liou, J. J., Huang, S. W., Wang, Y. C., Huang, H. H., & Tzeng, G. H. (2021). A hybrid, data-driven causality exploration method for exploring the key factors affecting mobile payment usage intention. Mathematics, 9(11), 1185. Field, A. (2005). Discovering statistics using SPSS (2nd ed.). London: Sage. Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (8th ed.). McGraw-Hill. Guo, H., & Yu, X. (2022). A survey on blockchain technology and its security. Blockchain: research and applications, 3(2), 100067. Hau, H. T., Nhung, D. T. H., & Trang, P. H. (2021). An empirical analysis of factors affecting the intention of using digital wallets in Vietnam. Journal of International Economics and Management, 21(1), 86-107. He, X., Lin, J., Li, K., & Chen, X. (2019). A novel cryptocurrency wallet management scheme based on decentralized multi-constrained derangement. IEEE Access, 7, 185250-185263. Humbani, M., & Wiese, M. (2019). An integrated framework for the adoption and continuance intention to use mobile payment apps. International Journal of Bank Marketing, 37(2), 646-664. IDC. (2021). The Rise of Digital Assets. Retrieved from https://www.idc.com/getdoc.jsp?containerId=lcUS50852323 Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310-322. Li, G., Liang, Y., Wang, H., Chen, J., & Chang, X. (2022). Factors influencing users’ willingness to adopt connected and autonomous vehicles: Net and configurational effects analysis using PLS-SEM and FsQCA. Journal of Advanced Transportation, 2022. Liu, Y., Li, Y., Lin, S. W., & Zhao, R. (2020, November). Towards automated verification of smart contract fairness. In Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (pp. 666-677). Mertler, C. A. (2014). Introduction to educational research: A critical thinking approach. SAGE Publications. Rehman, Z. U., Omar, S. S. B., Zabri, S. B. M., & Lohana, S. (2019). Mobile banking adoption and its determinants in Malaysia. International Journal of Innovative Technology and Exploring Engineering, 9(1), 4231-4239. Saldaña, J. (2013). The Coding Manual for Qualitative Researchers. SAGE Publications. Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural equation modeling. In Handbook of market research (pp. 587-632). Cham: Springer International Publishing. Sina Finance. (2020). Yunnan mobile payment usage statistics report. Retrieved from https://finance.sina.com.cn/ Sutticherchart, J., & Rakthin, S. (2023). Determinants of digital wallet adoption and super app: A review and research model. Management & Marketing, 18(3), 270-289. Ullman, J. B., & Bentler, P. M. (2012). Structural equation modeling. In R. H. Hoyle (Ed.), Handbook of structural equation modeling (pp. 1-16). The Guilford Press. Venkatesh, V., Davis, F. D., & Morris, M. G. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. Venkatesh, V., Thong, J. Y., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328-376. Zhang, R., & Moon, T. (2013). An Empirical Study on User Acceptance of Mobile Payment in China: Based on UTAUT Model. 인터넷전자상거래연구, 13(2), 187-215. Zhou, T. (2011). An empirical examination of continuance intention of mobile payment services. Decision Support Systems, 52(2), 486-495.

Page: 
1-18.
Content Status: 
Published