Advertisement

The Roles of Perceived Risk and Trust on E–Payment Adoption

  • Thanh D. Nguyen
  • Phuc A. Huynh
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 760)

Abstract

E–payment is one of the major constituents of e–commerce, which assists to enhance user efficiency and smarten intention to use of e–commerce in the digital era. This study investigates the roles of perceived risk and trust on e–payment adoption. Data is collected from respondents who have used or intend to use e–payments for e–commerce in Ho Chi Minh City. The structural equation modelling (SEM) is analyzed on a total convenient sampling of 200 respondents. Interestingly, research results externalize that perceived risk and trust have the principal roles of the structural model of e–payment adoption. The research model accounts for 38% of e–payment adoption.

Keywords

E–commerce E–payment Perceived risk IT adoption Trust 

References

  1. 1.
    Ajzen, I.: The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50(2), 179–211 (1991)CrossRefGoogle Scholar
  2. 2.
    Aladwani, A.M.: Online banking: a field study of drivers, development challenges, and expectations. Int. J. Inf. Manag. 21(3), 213–225 (2001)CrossRefGoogle Scholar
  3. 3.
    Bankole, F., Bankole, O.: The effects of cultural dimension on ICT innovation: empirical analysis of mobile phone services. Telemat. Inform. 34(2), 490–505 (2017)CrossRefGoogle Scholar
  4. 4.
    Barkhordari, M., Nourollah, Z., Mashayekhi, H., Mashayekhi, Y., Ahangar, M.: Factors influencing adoption of e–payment systems: an empirical study on Iranian customers. Inf. Syst. e–Bus. Manag. 14(3), 89–116 (2016)Google Scholar
  5. 5.
    Bauer R.A.: Consumer behavior as risk taking. In: AMA Proceedings, Chicago (1960)Google Scholar
  6. 6.
    Byrne, B.: Structural Equation Modeling with AMOS. Routledge, New York (2016)Google Scholar
  7. 7.
    Cabanillas, F., Fernandez, J., Leiva, F.: The moderating effect of experience in the adoption of mobile payment tools in virtual social networks: the m-payment acceptance model in virtual social networks (MPAM-VSN). Int. J. Inf. Manage. 34(2), 151–166 (2014)CrossRefGoogle Scholar
  8. 8.
    Cabanillas, F., Leiva, F., Fernandez, J.: A global approach to the analysis of user behavior in mobile payment systems in the new electronic environment. Serv. Bus. 11(1), 1–40 (2017)CrossRefGoogle Scholar
  9. 9.
    Davis, F.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3), 319–340 (1989)CrossRefGoogle Scholar
  10. 10.
    Davis, F., Bagozzi, R., Warshaw, P.: User acceptance of computer technology: a comparison of two theoretical models. Manag. Sci. 35(8), 982–1003 (1989)CrossRefGoogle Scholar
  11. 11.
    E–commerce and IT department: 2015 e–commerce report. Hanoi (2016)Google Scholar
  12. 12.
    Featherman, M., Miyazaki, A., Sprott, D.: Reducing online privacy risk to facilitate e–service adoption: the influence of perceived ease of use and corporate credibility. J. Serv. Mark. 24(3), 219–229 (2010)CrossRefGoogle Scholar
  13. 13.
    Featherman, M., Pavlou, P.: Predicting e–services adoption: a perceived risk facets perspective. Int. J. Hum.-Comput. Stud. 59(4), 451–474 (2003)CrossRefGoogle Scholar
  14. 14.
    Fishbein, M., Ajzen, I.: Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Addison–Wesley, Reading (1975)Google Scholar
  15. 15.
    Francisco, L., Francisco, M., Juan S.: Payment systems in new electronic environments: consumer behavior in payment systems via SMS. Int. J. Inf. Technol. Decis. Mak. 14(2), 421–449 (2015)Google Scholar
  16. 16.
    Fornell, C., Larcker, D.: Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18(1), 39–50 (1981)CrossRefGoogle Scholar
  17. 17.
    Gao, L., Waechter, K.: Examining the role of initial trust in user adoption of mobile payment services: an empirical investigation. Inf. Syst. Front. 19(3), 525–548 (2017)CrossRefGoogle Scholar
  18. 18.
    Gefen, D., Karahanna, E., Straub, D.: Trust and TAM in online shopping: an integrated model. MIS Q. 27(1), 51–90 (2003)CrossRefGoogle Scholar
  19. 19.
    Goczek, L., Witkowski, B.: Determinants of card payments. Appl. Econ. 48(16), 1530–1543 (2016)CrossRefGoogle Scholar
  20. 20.
    Hair, J., Black, W., Babin, B., Anderson, R., Tatham, R.: Multivariate Data Analysis. Pearson (2014)Google Scholar
  21. 21.
    Junadi, S.: A model of factors influencing consumer’s intention to use e–payment system in Indonesia. In: ICCSCI 2015 Proceedings, pp. 214–220. Indonesia (2015)Google Scholar
  22. 22.
    Kim, D., Benbasat, I.: The effects of trust–assuring arguments on consumer trust in internet stores: application of Toulmin’s model of argumentation. Inf. Syst. Res. 17(3), 286–300 (2006)CrossRefGoogle Scholar
  23. 23.
    Lacan, C., Desmet, P.: Does the crowdfunding platform matter? Risks of negative attitudes in two–sided markets. J. Consum. Mark. 34, 472–479 (2017)CrossRefGoogle Scholar
  24. 24.
    Laudon, K., Traver, C.: E–commerce: Business Technology Society. Pearson (2016)Google Scholar
  25. 25.
    Lu, Y., Yang, S., Chau, P., Cao, Y.: Dynamics between the trust transfer process and intention to use mobile payment services: a cross–environment perspective. Inf. Manag. 48(8), 393–403 (2011)CrossRefGoogle Scholar
  26. 26.
    Nguyen, T.D., Cao, T.H.: Structural model for adoption and usage of e–banking in Vietnam. J. Econ. Dev. 220, 116–135 (2014)CrossRefGoogle Scholar
  27. 27.
    Nguyen, V.T.T., Nguyen, T.D.: Perceived risk in the e–payment adoption via social network. J. Econ. Dev. 27(12), 66–81 (2016)Google Scholar
  28. 28.
    Park, J., Lee, D., Ahn, J.: Risk–focused e–commerce adoption model: a cross–country study. J. Glob. Inf. Technol. Manag. 7, 6–30 (2004)Google Scholar
  29. 29.
    Pavlou, P.A.: Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model. Int. J. Electron. Commer. 7(3), 101–134 (2003)Google Scholar
  30. 30.
    Pham, L., Cao, N.Y., Nguyen, T.D., Tran, P.T.: Structural models for e–banking adoption in Vietnam. Int. J. Enterp. Inf. Syst. 9(1), 31–48 (2013)CrossRefGoogle Scholar
  31. 31.
    Phonthanukitithaworn, C., Sellitto, C., Fong, M.: An investigation of mobile payment (m–payment) services in Thailand. Asia-Pac. J. Bus. 8(1), 37–54 (2016)CrossRefGoogle Scholar
  32. 32.
    Poon, W.C.: Users’ adoption of e–banking services: the Malaysian perspective. J. Bus. Ind. Mark. 23(1), 59–69 (2007)MathSciNetCrossRefGoogle Scholar
  33. 33.
    Rahman, S.: Introduction to E–Commerce Technology in Business. GRIN (2014)Google Scholar
  34. 34.
    Schumacker, R., Lomax, R.: A Beginner’s Guide to Structural Equation Modeling. Routledge, New York (2016)zbMATHGoogle Scholar
  35. 35.
    Swick, N.K.: Benefits & risks of electronic payment systems (2010). https://thatcreditunionblog.wordpress.com
  36. 36.
    Tee, H., Ong, H.: Cashless payment and economic growth. Financ. Innov. 2(1), 2–4 (2016)CrossRefGoogle Scholar
  37. 37.
    Tella, A.: Determinants of e–payment systems success: a user’s satisfaction perspective. Int. J. E-Adopt. 4(3), 15–38 (2012)CrossRefGoogle Scholar
  38. 38.
    Venkatesh, V.: Determinants of perceived ease of use: integrating perceived behavioral control, computer anxiety and enjoyment into the technology acceptance model. Inf. Syst. Res. 11(4), 342–365 (2000)CrossRefGoogle Scholar
  39. 39.
    Venkatesh, V., Davis, F.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag. Sci. 46(2), 186–204 (2000)CrossRefGoogle Scholar
  40. 40.
    Venkatesh, V., Bala, H.: Technology acceptance model 3 and a research agenda on interventions. Decis. Sci. 39(2), 273–315 (2008)CrossRefGoogle Scholar
  41. 41.
    Venkatesh, V., Morris, M., Davis, F.: User acceptance of information technology: toward a unified view. MIS Q. 27, 425–478 (2003)CrossRefGoogle Scholar
  42. 42.
    Vietnam e–commerce association: Vietnam e–commerce index report. HCMC (2016)Google Scholar
  43. 43.
    Yang, Q., Pang, C., Liu, L., Yen, D., Tarn, J.: Exploring consumer perceived risk and trust for online payments: an empirical study in China’s younger generation. Comput. Hum. Behav. 50, 9–24 (2015)CrossRefGoogle Scholar
  44. 44.
    Yaokumah, W., Kumah, P., Okai, E.: Demographic influences on e–payment services. Int. J. E-Bus. Res. 13(1), 44–65 (2017)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Banking University of Ho Chi Minh CityHo Chi Minh CityVietnam
  2. 2.Bach Khoa UniversityHo Chi Minh CityVietnam

Personalised recommendations