Factors Influencing the Intention to Use E-Wallet Services among University Students in the Mekong Delta, Vietnam

Author's Information:

Thien Van Ngo

PhD, Dean, Faculty of Economics, Kien Giang University, Vietnam, 0009-0007-3690-3702.

Tuan Minh Nguyen

MBA, Lecturer, Faculty of Economics, Kien Giang University, Vietnam

Chau Truong Ngoc Le

MBA, Lecturer, Faculty of Economics, Kien Giang University, Vietnam

Luom Thanh Thai

PhD, Associate Professor, Faculty of Economics, Kien Giang University, Vietnam

Vol 03 No 01 (2026):Volume 03 Issue 01 January 2026

Page No.: 01-10

Abstract:

The rapid development of financial technology has accelerated the trend toward cashless payments, in which e-wallets have emerged as a popular choice among young users. However, university students in the Mekong Delta—a region characterized by relatively low urbanization and limited technological infrastructure—have not been sufficiently studied. This research aims to identify the factors that influence students’ intention to use e-wallet services in this context. Based on the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and the Trust–Risk framework, the proposed model integrates seven constructs: perceived usefulness (PU), perceived ease of use (PEU), trust (TR), perceived risk (PR), social influence (SI), attitude (ATT), and behavioral intention (BI). Data were collected from 370 students with prior experience using e-wallets and analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. The results reveal that PU and PEU positively affect ATT; ATT, TR, and SI directly influence BI; while PR has a negative effect on BI. The model explains 52% of the variance in BI and 44.5% of the variance in ATT, with measurement indices demonstrating reliability and validity. These findings extend the TAM framework by incorporating trust, risk, and social influence, offering theoretical insights into digital financial behavior in less urbanized contexts. From a practical perspective, the study provides strategic implications for service providers, educational institutions, and policymakers to foster students’ adoption of e-wallets, thereby contributing to the broader digital transformation process.

KeyWords:

Behavioral intention, e-wallet, Mekong Delta, digital financial services, university students.

References:

  1. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T.
  2. Ajzen, I. (2005). Attitudes, personality and behavior (2nd ed.). Open University Press/McGraw-Hill.
  3. Byrne, B. M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming (3rd ed.). Routledge.
  4. Bui, N. V. (2021). Factors influencing students’ intention to use e-wallets in Can Tho City. Can Tho University Journal of Science, 57(2), 45–55.
  5. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008.
  6. Esawe, A. T. (2022). Exploring retailers’ behavioural intentions towards using m-payment: Extending UTAUT with perceived risk and trust. Paradigm: A Management Research Journal, 26(1), 8–28.
  7. Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451–474. https://doi.org/10.1016/S1071-5819(03)00111-3.
  8. Franke, G., & Sarstedt, M. (2019). Heuristics versus statistics in discriminant validity testing: A comparison of four procedures. Industrial Management & Data Systems, 119(1), 230–244. https://doi.org/10.1108/IMDS-07-2018-0315.
  9. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). SAGE.
  10. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8.
  11. Kustono, A. S., Suprapto, W., & Rahmawati, E. (2020). Determinants of intention to use e-wallets in Indonesia. International Journal of Economics and Business Administration, 8(4), 3–18. https://doi.org/10.35808/ijeba/564.
  12. Nguyen, N. A. N., Dang, T. L., & Nguyen, T. D. (2020). Vietnam’s e-wallet market: Opportunities and challenges. Banking Reviewhttps://tapchinganhang.gov.vn/thi-truong-vi-dien-tu-viet-nam-co-hoi-va-thach-thuc-9829.html.
  13. Nguyen, K. H., & Vo, V. D. (2021). Factors influencing the use of digital financial services among Vietnamese students. Journal of Economics & Development, 287, 75–84.
  14. Nur, N., & Noah, S. M. (2023). Social influence and behavioral intention in digital payment adoption. Asian Journal of Business Research, 13(1), 45–59.
  15. Prime Minister of Vietnam. (2021). Decision No. 1813/QD-TTg dated October 28, 2021 approving the scheme for developing cashless payments in the period 2021–2025. Hanoi, Vietnam.
  16. Tuoi Tre. (2025, March 6). The number of universities in the Red River Delta is nearly double that of the Southeast.https://tuoitre.vn/so-luong-dai-hoc-o-dong-bang-song-hong-gan-gap-doi-dong-nam-bo-20250306123815874.htm.
  17. Vasudevan, R., Chauhan, S., & Yadav, R. (2023). Trust and perceived risk in mobile wallet adoption: An extended TAM approach. Journal of Retailing and Consumer Services, 71, 103215. https://doi.org/10.1016/j.jretconser.2023.103215.
  18. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926.
  19. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540.