Skip to main content
SpringerLink
Log in

The Optimal Model for Consumers’ E-wallets Usage Intention

  • Conference paper
  • First Online:
Software Engineering Application in Informatics (CoMeSySo 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 232))

Included in the following conference series:

  • 880 Accesses

Abstract

These days, the entire world is getting digitalized, and payments through cell phones have become the most straightforward payment method, supplanting cash-based payment methods. The technological progressions have made it essential for the present buyers to utilize their cell phones since it is quicker, simpler, and convenient to do the everyday exchanges. In addition, the reasons (bonus points and cashback) give to the client, deciding to pay through e-wallets, pulls the clients from all age gatherings to pay through e-wallets. This study aims to empirical research for searching the optimal model to clients’ e-wallets usage intention. We implemented the Akaike information criterion (AIC) technique with RStudio software for selecting the optimal model. AIC is one of the most widely used model choice techniques in most statistical software packages. The finding reveals the best model includes determinants (effort expectancy, perceived ease to use, promotions, and perceived security and privacy) that significantly impact clients’ e-wallets usage intention.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Nag, A.K., Gilitwala, B.: E-Wallet- factors affecting its intention to use. Int. J. Rec. Technol. Eng. 8(4) (2019). https://doi.org/10.35940/ijrte.d6756.118419

  2. Hoang, T.: E-wallet market boom (Vietnamese). https://bankingplus.vn/bung-no-thi-truong-vi-dien-tu-99515.html

  3. Singh, N., Sinha, N., Liébana-Cabanillas, F.J.: 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. Int. J. Inf. Manage. 50, 191–205 (2020). https://doi.org/10.1016/j.ijinfomgt.2019.05.022

    Article  Google Scholar 

  4. Ridaryanto, Firmansyah, R., Kartono, R., Sundjaja, A..: Factors affecting the use of E-Wallet in JABODETABEK area. Int. J. Adv. Trends Comput. Sci. Eng. 8, 3645–3651 (2019)

    Google Scholar 

  5. Karim, M., Haque, A., Ulfy, M., Hossain, M., Anis, M.: Factors influencing the use of E-wallet as a payment method among malaysian young adults. J. Int. Bus. Manag. 3, 1–11 (2020). https://doi.org/10.37227/jibm-2020-2-21/

    Article  Google Scholar 

  6. Yang, M., Al Mamun, A., Mohiuddin, M., Nawi, N.C., Zainol, N.R.: Cashless transactions: a study on intention and adoption of e-wallets. Sustainability (Switzerland). 13, 1–18 (2021). https://doi.org/10.3390/su13020831

    Article  Google Scholar 

  7. Punwatkar, S., Verghese, M.: Adaptation of e-wallet payment: an empirical study on consumers’ adoption behavior in central india. Int. J. Adv. Manag. Technol. Eng. Sci. 8, 1147–1156 (2018)

    Article  Google Scholar 

  8. Venkatesh, V., Morris, M., Davis, G., Davis, F.: User acceptance of information technology: toward a unified view. MIS Q. 27, 425–478 (2003). https://doi.org/10.1016/j.inoche.2016.03.015

    Article  Google Scholar 

  9. Davis, F.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13, 319–340 (1989). https://doi.org/10.5962/bhl.title.33621

    Article  Google Scholar 

  10. Anwar, N.B.: Singaporean consumers’ attitudes to technology usage. Int. J. Bus. Admin. Stud. 4, 1–14 (2018). https://doi.org/10.20469/ijbas.4.10001-1

    Article  Google Scholar 

  11. Ajzen, I.: The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50, 179–211 (1991). https://doi.org/10.1016/0749-5978(91)90020-T

    Article  Google Scholar 

  12. Venkatesh, V., Thong, J.Y., Xu, X.: Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q. 36, 157–178 (2012). https://doi.org/10.1109/MWSYM.2015.7167037

    Article  Google Scholar 

  13. Angelina, C., Rahadi, R.A.: A conceptual study on the factors influencing usage intention of e-Wallets in Java. Int. J. Acc. Financ. Bus. 5, 19–29 (2020)

    Google Scholar 

  14. Okumus, B., Ali, F., Bilgihan, A., Ozturk, A.B.: Psychological factors influencing customers’ acceptance of smartphone diet apps when ordering food at restaurants. Int. J. Hosp. Manag. 72, 67–77 (2018). https://doi.org/10.1016/j.ijhm.2018.01.001

    Article  Google Scholar 

  15. Junadi, S.: A model of factors influencing consumer’s intention to use e-payment system in Indonesia. Proc. Comput. Sci. 59, 214–220 (2015). https://doi.org/10.1016/j.procs.2015.07.557

    Article  Google Scholar 

  16. Lu, J., Yao, J.E., Yu, C.S.: Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. J. Strat. Inf. Syst. 14, 245–268 (2005). https://doi.org/10.1016/j.jsis.2005.07.003

    Article  Google Scholar 

  17. Yang, S., Lu, Y., Gupta, S., Cao, Y., Zhang, R.: Mobile payment services adoption across time: an empirical study of the effects of behavioral beliefs, social influences, and personal traits. Comput. Hum. Behav. 28, 129–142 (2012). https://doi.org/10.1016/j.chb.2011.08.019

    Article  Google Scholar 

  18. Khatimah, H., Susanto, P., Abdullah, N.L.: Hedonic motivation and social influence on behavioral intention of e-money: the role of payment habit as a mediator. Int. J. Entrepreneurship 23, 1–9 (2019)

    Google Scholar 

  19. Chawla, D., Joshi, H.: Role of mediator in examining the influence of antecedents of mobile wallet adoption on attitude and intention. Glob. Bus. Rev. 1–17 (2020). https://doi.org/10.1177/0972150920924506

  20. Peñarroja, V., Sánchez, J., Gamero, N., Orengo, V., Zornoza, A.M.: The influence of organisational facilitating conditions and technology acceptance factors on the effectiveness of virtual communities of practice. Behav. Inf. Technol. 38, 845–857 (2019). https://doi.org/10.1080/0144929X.2018.1564070

    Article  Google Scholar 

  21. Kotler, P., Keller, K.L.: Marketing Management. Pearson Education Inc, Upper Saddle River, New Jersey (2016)

    Google Scholar 

  22. Amoroso, D.L., Magnier-Watanabe, R.: Building a research model for mobile wallet consumer adoption: the case of mobile Suica in Japan. J. Theor. Appl. Electron. Commer. Res. 7, 94–110 (2012). https://doi.org/10.4067/S0718-18762012000100008

    Article  Google Scholar 

  23. Shin, D.H.: Towards an understanding of the consumer acceptance of mobile wallet. Comput. Hum. Behav. 25, 1343–1354 (2009). https://doi.org/10.1016/j.chb.2009.06.001

    Article  Google Scholar 

  24. Ranganathan, C., Ganapathy, S.: Key dimensions of business-to-consumer web sites. Inf. Manag. 39, 457–465 (2002). https://doi.org/10.1016/S0378-7206(01)00112-4

    Article  Google Scholar 

  25. Roca, J.C., García, J.J., de la Vega, J.J.: The importance of perceived trust, security and privacy in online trading systems. Inf. Manag. Comput. Secur. 17, 96–113 (2009). https://doi.org/10.1108/09685220910963983

    Article  Google Scholar 

  26. Jarvenpaa, S.L., Toad, P.A.: Consumer reactions to electronic shopping on the World Wide Web. Int. J. Electron. Commer. 1, 59–88 (1996). https://doi.org/10.1080/10864415.1996.11518283

    Article  Google Scholar 

  27. Akaike, H.: A new look at the statistical model identification. IEEE Trans. Autom. Control 19, 716–723 (1974). https://doi.org/10.1109/TAC.1974.1100705

    Article  MathSciNet  MATH  Google Scholar 

  28. Chaurasia, A., Harel, O.: Model selection rates of information based criteria. Electron. J. Stat. 7, 2762–2793 (2013). https://doi.org/10.1214/13-EJS861

    Article  MathSciNet  MATH  Google Scholar 

  29. Karlsson, P.S., Behrenz, L., Shukur, G.: Performances of model selection criteria when variables are ill conditioned. Comput. Econ. 54(1), 77–98 (2017). https://doi.org/10.1007/s10614-017-9682-8

    Article  Google Scholar 

  30. Bulteel, K., Wilderjans, T.F., Tuerlinckx, F., Ceulemans, E.: CHull as an alternative to AIC and BIC in the context of mixtures of factor analyzers. Behav. Res. Methods 45(3), 782–791 (2013). https://doi.org/10.3758/s13428-012-0293-y

    Article  Google Scholar 

  31. Fabozzi, F.J., Focardi, S.M., Rachev, S.T., Arshanapalli, B.G.: Appendix E: model selection criterion: AIC and BIC. In: The Basics of Financial Econometrics. pp. 399–403. John Wiley & Sons, Inc, New Jersey (2014). https://doi.org/10.1002/9781118856406.app5

  32. Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M.: A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). SAGE Publications Inc, Los Angeles, CA (2017)

    MATH  Google Scholar 

  33. Grömping, U.: Relative importance for linear regression in R: the package relaimpo. J. Stat. Softw. 17, 1–27 (2006). https://doi.org/10.18637/jss.v017.i01

Download references

Author information

Authors and Affiliations

  1. Industrial University of Ho Chi Minh City, Ho Chi Minh City, Vietnam

    Dam Tri Cuong

Authors
  1. Dam Tri Cuong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dam Tri Cuong .

Editor information

Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

  2. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Petr Silhavy

  3. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Zdenka Prokopova

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Cuong, D.T. (2021). The Optimal Model for Consumers’ E-wallets Usage Intention. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds) Software Engineering Application in Informatics. CoMeSySo 2021. Lecture Notes in Networks and Systems, vol 232. Springer, Cham. https://doi.org/10.1007/978-3-030-90318-3_8

Download citation

Publish with us

Policies and ethics

Search

Navigation