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Multi-Generation Perception Towards Digital Wallet in Indonesia

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Published:25 August 2020Publication History

ABSTRACT

Digital wallet in Indonesia exists to facilitate payment transactions without using cash. Popular brands of digital wallet products in Indonesia are Go-pay, Ovo, Dana, LinkAja. This study aims to identify the influencing factors of user intentions to use and recommend digital wallets based on a multi-generation preference perspective. The existing model is modified and adapted to the characteristics of users in Indonesia, then the model is validated by Expert Judgment. The data obtained from the respondents by filling in an online form at Google form, in which the link was spreaded out through social media such as WhatsApp and Instagram. The total of sample of this study is 205 respondents. This study is using the Partial Least Square (PLS) method using SMARTPLS 3 software, the results of data analysis show in Generation X, Perceived ease of use, Perceived Usefulness, Compatibility, and Trust positively influence Intention to Use, and the factors that influence intention to use in generation Y are Perceived Usefulness, Perceived Behavioral Control, and Trust. Factors that influence intention to use in generation Z are Perceived Ease of Use, and Perceived Usefulness. eventually, based on the data of each generation, the Intention to use indirectly influence Actual Use, Perceived Satisfaction, AND Recommendation to use.

References

  1. Liu, J., Kauffman, R.J. and Ma, D. 2015. Competition, cooperation and regulation: Understanding the evolution of the mobile payments technology ecosystem. Electronic Commerce Research and Applications.Google ScholarGoogle Scholar
  2. Aldridge, I. 2013. High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading System, second edition. John Wiley and Sons, New York.Google ScholarGoogle Scholar
  3. Redaksi, 2019 "Daftar 10 Dompet Digital Terpopuler di RI, Siapa Jawaranya", CNBC Indonesia, Jakarta.Google ScholarGoogle Scholar
  4. Author, 2019 "Persaingan Dompet Digital", Indonesia.go.id, Jakarta.Google ScholarGoogle Scholar
  5. Indah Rahmayani, 2015 "Indonesia Raksasa Teknologi Digital Asia", Kominfo, Jakarta.Google ScholarGoogle Scholar
  6. Fahmi A. Burhan, 2020 "Bukan Bakar Uang, Begini Strategi DANA Capai 170 Juta Pengguna" katadata, Jakarta.Google ScholarGoogle Scholar
  7. Author, 2019 "Perilaku Belanja Online Generasi X, Y dan Z" Sirclo, Indonesia.Google ScholarGoogle Scholar
  8. I. Alnawas and F. Aburub, "The effect of benefits generated from interacting with branded mobile," Journal of Retailing and Consumer Services, vol. 31, pp. 313--322, 2016.Google ScholarGoogle Scholar
  9. Venkatesh, V., and Davis, F.D. 1996. A model of the antecedents of perceived ease of use: development and test. Decision Sciences.Google ScholarGoogle Scholar
  10. F. D. Davis, User acceptance of information technology: System characteristics, user perceptions and behavioral impacts, International Journal of ManMachine Studies, vol. 38, no. 3, pp. 475--487, 1.Google ScholarGoogle Scholar
  11. Madan, K., Yadav, R., 2016. Behavioural intention to adopt mobile wallet: a developing country perspective. Journal of Indian Business Research 8 (3), 227--244.Google ScholarGoogle ScholarCross RefCross Ref
  12. Natarajan, T., Balasubramanian, S.A., Kasilingam, D.L., 2017. Understanding the intention to use mobile shopping applications and its influence on price sensitivity. J. Retail. Consum. Serv. 37, 8--22.Google ScholarGoogle ScholarCross RefCross Ref
  13. Shin, D., & Kim, W. (2008). Applying the technology acceptance model and flowtheory to cyworld user behavior.Cyber Psychology and Behavior, 11 (4), 12--20Google ScholarGoogle Scholar
  14. Mallat, N., 2007. Exploring consumer adoption of mobile payments e a qualitative study. J. Strateg. Inf. Syst. 16, 413--432Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Karnouskos, S., Fokus, F., 2004. Mobile Payment: a journey through existing procedures and standardization initiatives. IEEE Communications Surveys and Tutorials 6 (4), 44--66.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Ajzen, Icek (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50 (2), 179--211.Google ScholarGoogle ScholarCross RefCross Ref
  17. Pavlou, P.A., & Gefen, D. (2004). Building effective online market places with institution-based trust. Information Systems Research, 15(1), 37--59..Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Casidy, R., & Wymer, W. (2016). A risk worth taking: Perceived risk as moderator of perceived satisfaction, loyalty, and willingness to pay premium price. Journal of Retailing and Consumer Services, 32, 189--197.Google ScholarGoogle ScholarCross RefCross Ref
  19. Miltgen, C.L., Popovic, A., & Oliveira, T. (2013). Determinants of end-user acceptance of biometrics: Integrating the "Big3" of technology acceptance with privacy context. Decision Support Systems, 56, 103--114.Google ScholarGoogle ScholarCross RefCross Ref
  20. E. Masud, "Partial Least Squares (PLS)". Hanbook of Brawijaya University, 2015. http://masud.lecture.ub.ac.id/files/2015/05/14.PLS.pdf.Google ScholarGoogle Scholar
  21. Y. Nabila, "Analysis Impact of Knowledge Management System Implementation on Increasing Organizational Competitiveness" Industrial Engineering Department Universitas Indonesia, 2018.Google ScholarGoogle Scholar
  22. Ling, F., shan li, sui, p., & ofori, G. 2012, "mathematical models for predicting chinese A/E/C firms' competitiveness". Automotion in construction, 40--51.Google ScholarGoogle Scholar
  23. V. E. Vinzi et al., "PLS Path Modeling: From Foundations to Recent Developments and Open Issues for Model Assessment and Improvement", Handbook of Partial Least Square, 2010.Google ScholarGoogle ScholarCross RefCross Ref
  24. J. F. Hair, C. M. Ringle and M. Sarstedt, "PLS-SEM: Indeed a silver bullet," Journal of Marketing Theory and Practice, vol. 19, no. 2, pp. 139--151, 2011.Google ScholarGoogle Scholar
  25. R. P. Bagozzi and Y. Yi, "On the evaluation of structural equation models," Journal of The Academy of Marketing Science, vol. 88, no. 2, pp. 207--218, 1988.Google ScholarGoogle Scholar
  26. J. Cohen, Statistical Power Analysis for the Behavioral Sciences: Second Edition, New York: Lawrence Erlbaum Associates Publishers, 1988.Google ScholarGoogle Scholar
  27. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M, "A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)", Thousand Oaks: Sage. 2013.Google ScholarGoogle Scholar
  28. Ghozali, "Structural Equation Modeling Metode Alternatif dengan Partial Least Square", ISBN:979.704.300.2.Badan Penerbit Universitas Diponegoro Semarang. 2014Google ScholarGoogle Scholar
  29. Chatterjee, D., & Kartikeya Bolar (2018): Determinants of Mobile Wallet Intentions to Use: The Mental Cost Perspective. International Journal of Human-Computer Interaction, DOI: 10.1080/10447318.2018.1505697Google ScholarGoogle Scholar
  30. Singh, N., Neena, S., Francisco, J.C. (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, 191--205.Google ScholarGoogle Scholar
  31. Ghozali, "Structural Equation Modeling Metode Alternatif dengan Partial Least Square", ISBN:979.704.300.2.Badan Penerbit Universitas Diponegoro Semarang. 2014Google ScholarGoogle Scholar

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      • Published in

        cover image ACM Other conferences
        APCORISE '20: Proceedings of the 3rd Asia Pacific Conference on Research in Industrial and Systems Engineering
        June 2020
        410 pages
        ISBN:9781450376006
        DOI:10.1145/3400934

        Copyright © 2020 ACM

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        Publication History

        • Published: 25 August 2020

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        APCORISE '20 Paper Acceptance Rate68of110submissions,62%Overall Acceptance Rate68of110submissions,62%

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