Article Sidebar

Download
PDF
Statistic
Read Counter : 213 Download : 303

Main Article Content

Abstract

The use of e-wallets has an impact on the ease of transactions. Various kinds of transactions can be done through this application. However, despite the convenience offered, e-wallet adoption remains low. This study aims to determine what factors influence the determinants of mobile e-wallet adoption across generations in Indonesia. The study was investigated using a composite model based on the diffusion of innovation theory (DIT), technology acceptance model (TAM) and information system success model (ISSM). Data was collected from 200 e-wallet users in West Nusa Tenggara province and analyzed using multiple linear regression (PLS-SEM). The results showed that the use of e-wallets was not affected by observability, relative advantage, information quality and system quality. Ease of use and perceived usefulness have a positive impact on the decision to use e-wallets in Indonesia. The results of this study are very important to assess the situation and prospects of e-wallets in Indonesia. The results of this study offer significant insights for policy makers and e-wallet service providers to develop appropriate strategies to increase e-wallet users in Indonesia.

Keywords

E-wallet Adoption Across Generation

Article Details

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite
Arini, N., Hilendri Lestari, B. A., & Hanani, T. (2024). The Determinants of Mobile E-Wallet Adoption Across Generation, A Lesson Learned From Indonesia. Ilomata International Journal of Tax and Accounting, 5(2), 488-502. https://doi.org/10.61194/ijtc.v5i2.1132

References

  1. Abidin, A., Zahra, N. S., & Yusuf, A. (2023). Analisis Aplikasi Kredivo Berdasarkan Information System Success Model (ISSM). Jurnal Maksipreneur: Manajemen, Koperasi, Dan Entrepreneurship, 12(2), 602–616.
  2. Agustina, N., & Sutinah, E. (2019). Model Delone dan McLean Untuk Menguji Kesuksesan Aplikasi Mobile Penerimaan Mahasiswa Baru. InfoTekJar (Jurnal Nasional Informatika Dan Teknologi Jaringan), 3(2), 76–82. https://doi.org/10.30743/infotekjar.v3i2.1008
  3. Al-Emran, M., Mezhuyev, V., & Kamaludin, A. (2020). Towards a conceptual model for examining the impact of knowledge management factors on mobile learning acceptance. Technology in Society, 61, 101247. https://doi.org/10.1016/j.techsoc.2020.101247
  4. Al-Saedi, K., Al-Emran, M., Abusham, E., & El Rahman, S. A. (2019). Mobile Payment Adoption: A Systematic Review of the UTAUT Model. 2019 International Conference on Fourth Industrial Revolution (ICFIR), 1–5. https://doi.org/10.1109/ICFIR.2019.8894794
  5. Azizah, N., Handayani, P. W., & Azzahro, F. (2018). Factors influencing continuance usage of mobile wallets in Indonesia. 2018 International Conference on Information Management and Technology (ICIMTech), 92–97.
  6. Balakrishnan, J., Dwivedi, Y. K., Hughes, L., & Boy, F. (2021). Enablers and inhibitors of AI-powered voice assistants: a dual-factor approach by integrating the status quo bias and technology acceptance model. Information Systems Frontiers, 1–22.
  7. Chen, L., & Aklikokou, A. K. (2020). Determinants of E-government Adoption: Testing the Mediating Effects of Perceived Usefulness and Perceived Ease of Use. International Journal of Public Administration, 43(10), 850–865. https://doi.org/10.1080/01900692.2019.1660989
  8. Choi, J., & Kim, S. (2016). Is the smartwatch an IT product or a fashion product? A study on factors affecting the intention to use smartwatches. Computers in Human Behavior, 63, 777–786. https://doi.org/10.1016/j.chb.2016.06.007
  9. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
  10. DeLone, W. H., & McLean, E. R. (1992). Information Systems Success: The Quest for the Dependent Variable. Information Systems Research, 3(1), 60–95. https://doi.org/10.1287/isre.3.1.60
  11. Endriyanto, R., & Indrarini, R. (2022). Pengaruh Promosi dan Fitur Layanan terhadap Minat Menggunakan E-Wallet Linkaja (Studi Kasus di Surabaya). Jurnal Ekonomika Dan Bisnis Islam, 5(1), 67–80. https://doi.org/10.26740/jekobi.v5n1.p67-80
  12. Fatmawati, A., Christina, B. A., & Murtiasri, E. (2022). ANALISIS KESUKSESAN SIAP BOS (SISTEM INFORMASI APLIKASI PENGELOLAAN BANTUAN OPERASIONAL SEKOLAH) DI KABUPATEN BLORA. Jurnal Aktual Akuntansi Keuangan Bisnis Terapan (AKUNBISNIS), 5(1), 142. https://doi.org/10.32497/akunbisnis.v5i1.3620
  13. Gopinath, K., Selvam, G., & Narayanamurthy, G. (2022). Determinants of the Adoption of Wearable Devices for Health and Fitness: A Meta-analytical Study. Communications of the Association for Information Systems, 50(1), 445–450. https://doi.org/10.17705/1CAIS.05019
  14. Gumilang, I., & Hidayatullah, D. S. (2018). Pengaruh Relative Advantage, Complexity, Compatibilty, Subjective Norm, Dan Perceived Behavioral Control Terhadap Niat Berwirausaha Online Pada Lulusan Sekolah Bisnis Di Bandung (Studi Kasus Pada Sekolah Bisnis Manajemen Institut Teknologi Bandung Dan Fakultas Ekonomi Bisnis Universitas Telkom). EProceedings of Management, 5(1).
  15. Hair, J. F., Hult, G. T. M., & Ringle, C. M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd Edition). Sage Publications, Inc.
  16. Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442–458. https://doi.org/10.1108/IMDS-04-2016-0130
  17. Halim, F. , E. B. M. , M. A. R. , & S. A., Efendi, B., M., M. A. R., & Sudirman, A. (2020, October 14). Constituents Driving Interest in Using E-Wallets in Generation Z. Proceeding on International Conference of Science Management Art Research Technology. https://doi.org/10.31098/ic-smart.v1i1.32
  18. Hidayat, A. R. (2023). Analisis Adopsi Penggunaan Sistem Pembayaran Fintech pada Generasi Milenial Menggunakan Teori Difusi Inovasi. Jurnal Ilmu Manajemen, 13. https://doi.org/10.32502/jimn.v13i2.6974
  19. Hidayat, D., Pangaribuan, C. H., Putra, O. P. B., & Taufiq, F. J. (2021). Expanding the technology acceptance model with the inclusion of trust and mobility to assess e-wallet user behavior: Evidence from OVO consumers in Indonesia. IOP Conference Series: Earth and Environmental Science, 729(1). https://doi.org/10.1088/1755-1315/729/1/012050
  20. Iman, N. (2018). Is mobile payment still relevant in the fintech era? Electronic Commerce Research and Applications, 30, 72–82. https://doi.org/10.1016/j.elerap.2018.05.009
  21. Indonesia, J. P. (n.d.). Abdillah, W., & Hartono, J.(2015). Partial Least Square (PLS): Alternatif Structural Equation Modeling (SEM) Dalam Penelitian Bisnis. Yogyakarta: Penerbit Andi. Agarwal, S., & Dewan, J.(2020). An Analysis of The Effectiveness of Online Learning in Colleges of Uttar Pradesh During the COVID 19 Lockdown. Journal Of Xi’an University of Architecture & Technology, 2957, 2963.
  22. Ipsos, P., Dompet, E., Menuju, D., & Bisnis, K. (2020). PRESS RELEASE.
  23. Krismawan, A. (2014). PENGARUH KOMPONEN PENERIMAAN TEKNOLOGI DAN DIFUSI INOVASI TERHADAP NIAT BERPERILAKU MENGGUNAKAN TELEPON PINTAR. Universitas Atma Jaya .
  24. Lazaroni Ibrahim. (2017). Analisis Kesuksesan “Sistem Informasi Manajemen Kinerja Pegawai Secara Elektronik (E-Performance) Pada Dinas Tenaga Kerja Kota Surabaya” Menggunakan Information System Success Model (ISSM).
  25. Lin, W. R., Lin, C.-Y., & Ding, Y.-H. (2020). Factors Affecting the Behavioral Intention to Adopt Mobile Payment: An Empirical Study in Taiwan. Mathematics, 8(10), 1851. https://doi.org/10.3390/math8101851
  26. Marpaung, F. K., Dewi, R. S., Grace, E., Sudirman, A., & Sugiat, M. (2021). Behavioral Stimulus for Using Bank Mestika Mobile Banking Services: UTAUT2 Model Perspective. Golden Ratio of Marketing and Applied Psychology of Business, 1(2), 61–72. https://doi.org/10.52970/grmapb.v1i2.68
  27. Mombeuil, C. (2020). An exploratory investigation of factors affecting and best predicting the renewed adoption of mobile wallets. Journal of Retailing and Consumer Services, 55, 102127. https://doi.org/10.1016/j.jretconser.2020.102127
  28. Okonkwo, C. W., Amusa, L. B., Twinomurinzi, H., & Wamba, S. F. (2022). Mobile wallets in cash-based economies during COVID-19. Industrial Management & Data Systems, 123(2), 653–671.
  29. Rogers, E. M., Singhal, A., & Quinlan, M. M. (2014). Diffusion of innovations. In An integrated approach to communication theory and research (pp. 432–448). Routledge.
  30. Sebetci, Ö. (2018). Enhancing end-user satisfaction through technology compatibility: An assessment on health information system. Health Policy and Technology, 7(3), 265–274. https://doi.org/10.1016/j.hlpt.2018.06.001
  31. Setiawan, W., Sunaryo, D., & AR, K. (2022). ANALISIS FITUR LAYANAN DAN KEAMANAN TERHADAP PENGGUNAAN DOMPET DIGITAL (SHOPEE PAY). Digital Business Journal, 1(1), 52. https://doi.org/10.31000/digibis.v1i1.6602
  32. Sha, Z., Xie, Y., Tan, X., Bai, Y., Li, J., & Liu, X. (2017). Assessing the impacts of human activities and climate variations on grassland productivity by partial least squares structural equation modeling (PLS-SEM). Journal of Arid Land, 9(4), 473–488. https://doi.org/10.1007/s40333-017-0022-6
  33. Sharma, S. K., Mangla, S. K., Luthra, S., & Al-Salti, Z. (2018). Mobile wallet inhibitors: Developing a comprehensive theory using an integrated model. Journal of Retailing and Consumer Services, 45, 52–63. https://doi.org/10.1016/j.jretconser.2018.08.008
  34. Sneha, K., Rachita, R., & Vineet, K. (2020). Mobile wallet market. Applied Market Research.
  35. Sudarso, A., Nainggolan, N. T., Munandar, M., Nainggolan, L. E., Fuadi, F., Hastuti, P., Gandasari, D., Mistriani, N., Rumondang, A., & Kusuma, A. H. P. (2020). Perilaku Konsumen Di Era Digital.
  36. Sudarsono, H., Kholid, M. N., Trisanty, A., & Maisaroh, M. (2022). The intention of Muslim customers to adopt mobile banking: The case of Islamic banks in Indonesia. Cogent Business & Management, 9(1), 2154102.
  37. Sukma, A. A., Hudaya, R., & Hanani, T. (2024). Exploring The Effect Of State-Owned Enterprise Corporate Social Responsibility On Small Medium Enterprise Digitalization In Indonesia. Asian Journal of Management, Entrepreneurship and Social Science, 4(01), 594–608.
  38. Sulaiman, S., Tukiyat, T., & Hindasyah, A. (2023). Analisis Sistem Aplikasi Computer Base Test sebagai Sarana Ulangan menggunakan Metode Delone and Mclean. Jurnal Impresi Indonesia, 2(1), 58–70. https://doi.org/10.58344/jii.v2i1.2010
  39. Sun, Y., & Havidz, S. A. H. (2019). Factors Impacting the Intention to Use M-Payment. 2019 International Conference on Information Management and Technology (ICIMTech), 290–294. https://doi.org/10.1109/ICIMTech.2019.8843758
  40. Tam, C., Santos, D., & Oliveira, T. (2020). Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model. Information Systems Frontiers, 22, 243–257.
  41. Trivedi, J. (2016). Factors determining the acceptance of e wallets. International Journal of Applied Marketing and Management, 1(2), 42–53.
  42. Umaiyah, S. (2022). Dalam pusaran dompet digital: Praktik konsumsi dompet digital di kalangan kaum muda kontemporer. Satwika : Kajian Ilmu Budaya Dan Perubahan Sosial, 6(2), 281–298. https://doi.org/10.22219/satwika.v6i2.21780
  43. Wiratno, W. (2020). ANALISIS ADOPSI APLIKASI UANG ELEKTRONIK MELALUI PENDEKATAN TEORI DIFUSI INOVASI (Studi Terhadap Pengguna Aplikasi Uang Elektronik DANA di Kota Malang) . Jurnal Ilmiah Mahasiswa FEB.
  44. Wong, W. H., & Mo, W. Y. (2019). A study of consumer intention of mobile payment in Hong Kong, based on perceived risk, perceived trust, perceived security and Technological Acceptance Model. Journal of Advanced Management Science Vol, 7(2), 33–38.
  45. Wu, L.-H., Wu, L.-C., & Chang, S.-C. (2016). Exploring consumers’ intention to accept smartwatch. Computers in Human Behavior, 64, 383–392. https://doi.org/10.1016/j.chb.2016.07.005
  46. Zamani, E. D., & Giaglis, G. M. (2018). With a little help from the miners: distributed ledger technology and market disintermediation. Industrial Management & Data Systems, 118(3), 637–652. https://doi.org/10.1108/IMDS-05-2017-0231