Factors Influencing Cryptocurrency Retention Of Use In Indonesia

I Made Adwesta Mahotma; Gusi Putu Lestara Permana; Caren Angellina Mimaki

doi:10.31004/riggs.v4i4.4552

Authors

I Made Adwesta Mahotma Universitas Pendidikan Nasional
Gusi Putu Lestara Permana Universitas Pendidikan Nasional
Caren Angellina Mimaki Universitas Pendidikan Nasional

DOI:

https://doi.org/10.31004/riggs.v4i4.4552

Keywords:

Technology Acceptance Model (TAM), Perceived Ease of Use, Perceived Usefulness, Cryptocurrency

Abstract

This research investigates the determinants of continued cryptocurrency usage in Indonesia by extending the Technology Acceptance Model (TAM). A quantitative research approach was employed using a survey method to collect data from cryptocurrency users located in Java and Bali. Respondents were selected through purposive sampling to ensure that participants had prior experience using cryptocurrency. The collected data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) with SmartPLS software to assess the reliability and validity of the measurement model, as well as to examine the structural relationships among variables through bootstrapping techniques. The results indicate that perceived ease of use and perceived usefulness both have a positive and significant influence on cryptocurrency retention of use, confirming their importance in post-adoption behavior. In addition, cryptocurrency knowledge plays a moderating role in the model. Specifically, higher levels of cryptocurrency knowledge strengthen the relationship between perceived usefulness and retention of use, while weakening the effect of perceived ease of use. This finding suggests that knowledgeable users tend to prioritize functional benefits and investment advantages over system simplicity when deciding whether to continue using cryptocurrency. From a practical perspective, the study provides valuable insights for cryptocurrency platform developers, educators, and policymakers. Enhancing system functionality, improving user education, and developing supportive regulatory frameworks may help promote sustainable and long-term cryptocurrency usage in Indonesia.

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References

B. L. Song and C. Y. Liew, “Customers’ Satisfaction and Continuance Intention to Adopt Fintech Services: Developing Countries’ Perspective,” in Fintech and Cryptocurrency, United States of America: John Wiley & Sons and Scrivener Publishing, 2023, pp. 105–136.

S. Hassan, “Influential Factors towards Investment in Fintech based Currency: New Evidence from Australian Bitcoin Investors,” Eur. Online J. Nat. Soc. Sci., vol. 10, no. 3, pp. 391--402, 2021, [Online]. Available: https://european-science.com/eojnss/article/view/6252

M. Kim, “A psychological approach to Bitcoin usage behavior in the era of COVID-19: Focusing on the role of attitudes toward money,” J. Retail. Consum. Serv., vol. 62, no. May, p. 102606, 2021, doi: 10.1016/j.jretconser.2021.102606.

A. Echchabi, M. M. S. Omar, and A. M. Ayedh, “Factors influencing Bitcoin investment intention: The case of Oman,” Int. J. Internet Technol. Secur. Trans., vol. 11, no. 1, pp. 1–15, 2021, doi: 10.1504/IJITST.2021.112867.

R. Manurung and D. K. Paath, “Pengaruh Regulasi Digital Cryptocurrency Model Bitcoin Terhadap Sistem Pembayaran Pada UMKM,” is Best Account. Inf. Syst. Inf. Technol. Bus. Enterp. this is link OJS us, vol. 5, no. 2, pp. 151–165, Dec. 2020, doi: 10.34010/aisthebest.v5i2.4017.

A. Budree, C. Town, and S. Africa, “Can Cryptocurrency Be a Payment Method in a Developing Economy ? The Case of Bitcoin in South Africa,” J. Electron. Commer. Organ., vol. 21, no. 1, 2023, doi: 10.4018/JECO.320223.

M. F. Shahzad, S. Xu, W. M. Lim, M. F. Hasnain, and S. Nusrat, “Cryptocurrency awareness, acceptance, and adoption: the role of trust as a cornerstone,” Humanit. Soc. Sci. Commun., vol. 11, no. 4, 2024.

A. Bhattacherjee, “Understanding Information Systems Continuance: An Expectation-Confirmation Model,” MIS Q., vol. 25, no. 3, pp. 351–370, 2001.

T. Hariguna, A. Ruangkanjanases, B. Bin Madon, and K. M. Alfawaz, “Assessing Determinants of Continuance Intention Toward Cryptocurrency Usage: Extending Expectation Confirmation Model With Technology Readiness,” Sage Open, vol. 13, no. 1, Jan. 2023, doi: 10.1177/21582440231160439.

F. D. Davis, R. P. Bagozzi, and P. R. Warshaw, “User Acceptance of Computer Technology : A Comparison of Two Theoretical Models,” Manage. Sci., vol. 35, no. 8, pp. 982–1003, 1989, doi: 10.1287/mnsc.35.8.982.

P. Jariyapan, S. Mattayaphutron, S. N. Gillani, and O. Shafique, “Factors Influencing the Behavioural Intention to Use Cryptocurrency in Emerging Economies During the COVID-19 Pandemic: Based on Technology Acceptance Model 3, Perceived Risk, and Financial Literacy,” Front. Psychol., vol. 12, no. February, 2022, doi: 10.3389/fpsyg.2021.814087.

V. Venkatesh, “Determinants of Perceived Ease of Use : Integrating Control , Intrinsic Motivation , Acceptance Model,” Inf. Syst. Res., vol. 11, no. 4, pp. 342–365, 2000, doi: 10.1287/isre.11.4.342.11872.

D. Gefen, “E-commerce : the role of familiarity and trust,” Int. J. Manag. Sci., vol. 28, no. January, pp. 725–737, 2018, doi: 10.1016/S0305-0483(00)00021-9.

K. S. Al-Omoush, A. M. Gomez-Olmedo, and A. G. Funes, “Why do people choose to continue using cryptocurrencies?,” Technol. Forecast. Soc. Change, vol. 200, no. 123151, p., 2024, doi: https://doi.org/10.1016/j.techfore.2023.123151.

H. Islam, M. Rana, S. Shaa, T. Khatun, M. R. Ritu, and M. R. Islam, “Factors influencing the adoption of cryptocurrency in Bangladesh: an investigation using the technology acceptance model (TAM),” Tehcnological Sustain., vol. 2, no. 4, pp. 423–443, 2023.

Coinvestasi, “Investor Wilayah Jawa dan Bali Dominasi Pasar Kripto di Indonesia 2023.” [Online]. Available: https://coinvestasi.com/berita/investor-jawa-dan-bali-dominasi-pasar-kripto-di-indonesia

J. F. Hair, C. M. Ringle, G. T. M. Hult, M. Sarstedt, N. P. Danks, and S. Ray, Partial Least Squares Structural Equation Modeling ( PLS-SEM ) Using R. Spinger, 2022. doi: 10.1007/978-3-030-80519-7.

L. Chen and A. K. Aklikokou, “Determinants of E-government Adoption : Testing the Mediating Effects of Perceived Usefulness and Perceived Ease of Use Determinants of E-government Adoption : Testing the Mediating Effects of Perceived Usefulness and Perceived Ease of Use,” Int. J. Public Adm., vol. 43, no. 10, pp. 850–865, 2020, doi: 10.1080/01900692.2019.1660989.

V. Venkatesh and V. Tech, “Determinants of Perceived Ease of Use : Integrating Control , Intrinsic Motivation , and Emotion into the Technology Acceptance Model,” no. March, 2022, doi: 10.1287/isre.11.4.342.11872.

J. C. Mendoza-Tello, H. Mora, F. A. Pujol-López, and M. D. Lytras, “Social Commerce as a Driver to Enhance Trust and Intention to Use Cryptocurrencies for Electronic Payments,” IEEE Access, vol. 6, pp. 50737–50751, 2018, doi: 10.1109/ACCESS.2018.2869359.

T. Hariguna, A. Ruangkanjanases, and K. M. Alfawaz, “Assessing Determinants of Continuance Intention Toward Cryptocurrency Usage: Extending Expectation Confirmation Model With Technology Readiness,” SAGE Open, vol. 13, no. 1, 2023.

C. M. Ringle, M. Sarstedt, N. Sinkovics, and R. R. Sinkovics, “A perspective on using partial least squares structural equation modelling in data articles,” Data Br., vol. 48, 2023, doi: 10.1016/j.dib.2023.109074.

C. Fornell and D. Larcker, “Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of marketing research‏,” J. Mark. Res., vol. 18, no. 3, pp. 382-388., 1981.

V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “User Acceptance of Information Technology: Toward A Unified View,” MIS Quaterly, vol. 27, no. 3, pp. 425–478, 2003, doi: 10.2307/30036540.

A. Daud, N. Farida, Andryansyah, and M. Razak, “Impact of customer trust toward loyalty: the mediating role of perceived usefulness and satisfaction,” J. Bus. Retail Manag. Res., vol. 13, no. 02, 2018.