Analisis Faktor-Faktor yang Mempengaruhi Adopsi E-Wallet pada Baby Boomers: Perspektif Extended Technology Acceptance Model
Keywords:
E-wallet Adoption, Perceived Compatibility, Perceived Usefulness, Perceived ease of use, Intention to use, Technology Acceptance Models, Social Influence, Perceived Compatibility
Abstract
Penelitian ini bertujuan menganalisis faktor-faktor yang mempengaruhi adopsi e-wallet pada generasi Baby Boomers di Indonesia dengan menggunakan perspektif Technology Acceptance Model (TAM) yang diperluas. Penelitian berfokus pada pengaruh social influence dan perceived compatibility sebagai variabel eksternal terhadap perceived usefulness dan perceived ease of use, serta dampaknya pada attitude toward using dan behavioral intention. Menggunakan pendekatan kuantitatif, data dikumpulkan melalui kuesioner dengan teknik purposive sampling pada 290 responden Baby Boomers yang familiar dengan aplikasi e-wallet utama di Indonesia. Instrumen penelitian menggunakan skala Likert 5 poin dengan 30 item pernyataan yang mewakili enam konstruk penelitian. Analisis data menggunakan Structural Equation Modeling-Partial Least Square (SEM-PLS) dengan bantuan software SmartPLS 4.0. Model pengukuran dievaluasi melalui uji validitas konvergen, validitas diskriminan, dan reliabilitas, sedangkan model struktural diuji menggunakan analisis R-square, effect size, dan pengujian hipotesis. Penelitian ini memberikan kontribusi teoretis dalam pengembangan model penerimaan teknologi dan kontribusi praktis bagi penyedia layanan e-wallet dalam mengembangkan strategi yang sesuai untuk meningkatkan adopsi e-wallet pada generasi Baby Boomers.
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References
Abedi, E., Ghorbanzadeh, D., & Rahehagh, A. (2020). Influence of eWOM information on consumers' behavioral intentions in mobile social networks: Evidence of Iran. Journal of Advances in Management Research, 17(1), 84109. https://doi.org/10.1108/JAMR-04-2019-0058
Al-Rahmi, W. M., Alias, N., Othman, M. S., Marin, V. I., & Tur, G. (2019). Use of e-learning by University students in Malaysian higher educational institutions: A case in Universiti Teknologi Malaysia. IEEE Access, 7, 14268-14276. https://doi.org/10.1109/ACCESS.2019.2899368
Bilal, M., Akram, U., Rasool, H., Yang, X., & Tanveer, Y. (2022). Social commerce isn't the cherry on the cake, its the new cake! How consumers' attitudes and eWOM influence online purchase intention in China. International Journal of Quality and Service Sciences, 14(2), 180196. https://doi.org/10.1108/IJQSS-01-2021-0016
Cimbaljevi?, M., Demirovi? Bajrami, D., Kova?i?, S., Pavlukovi?, V., Stankov, U., & Vuji?i?, M. (2023). Employees' technology adoption in the context of smart tourism development: The role of technological acceptance and technological readiness. European Journal of Innovation Management, 27(8), 2457-2482. https://doi.org/10.1108/EJIM-09-2022-0516
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
Debasa, F., Senapathy, M., & Chovancovα, M. (2023). Do stress and anxiety influence users' intention to make restaurant reservations through mobile apps? European Research on Management and Business Economics, 29(1), 1-15. https://doi.org/10.1016/j.iedeen.2022.100205
Fard, M. H., & Marvi, R. (2020). Viral marketing and purchase intentions of mobile applications users. International Journal of Emerging Markets, 15(2), 287301. https://doi.org/10.1108/IJOEM-06-2018-0291
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139152. https://doi.org/10.2753/MTP1069-6679190202
Hamid, R. S., & Anwar, S. M. (2019). Structural Equation Modeling (SEM) Berbasis Varian: Konsep Dasar dan Aplikasi Dengan Program SmartPLS 3.2.8 dalam Riset Bisnis. PT Inkubator Penulis Indonesia.
Kampa, R. K. (2023). Combining technology readiness and acceptance model for investigating the acceptance of m-learning in higher education in India. Asian Association of Open Universities Journal, 18(2), 105-120. https://doi.org/10.1108/AAOUJ-10-2022-0149
Kelly, A. E., & Palaniappan, S. (2023). Using a technology acceptance model to determine factors influencing continued usage of mobile money service transactions in Ghana. Journal of Innovation and Entrepreneurship, 12(1). https://doi.org/10.1186/s13731-023-00301-3
Kim, S., Kwon, H. J., & Kim, H. (2023). Mobile banking service design attributes for the sustainability of internet-only banks: A case study of KakaoBank. Sustainability, 15(8). https://doi.org/10.3390/su15086428
Leon, S. (2018). Service mobile apps: A millennial generation perspective. Industrial Management and Data Systems, 118(9), 18371860. https://doi.org/10.1108/IMDS-10-2017-0479
Madias, K., Szymkowiak, A., & Borusiak, B. (2023). What builds consumer intention to use smart water meters Extended TAM-based explanation. Water Resources and Economics, 44. https://doi.org/10.1016/j.wre.2023.100233
Maziriri, E. T., Nyagadza, B., Chuchu, T., & Mazuruse, G. (2023). Antecedents of attitudes towards the use of environmentally friendly household appliance products in Zimbabwe: An extension of the theory of planned behaviour. PSU Research Review, 8(3), 749-773. https://doi.org/10.1108/PRR-03-2022-0033
McLean, G., Osei-Frimpong, K., Wilson, A., & Pitardi, V. (2020). How live chat assistants drive travel consumers' attitudes, trust and purchase intentions. International Journal of Contemporary Hospitality Management, 32(5), 17951812. https://doi.org/10.1108/IJCHM-07-2019-0605
Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222.
Mpinganjira, M. (2019). Cognitive absorption and behavioural intentions in virtual health communities. Journal of Systems and Information Technology, 21(1), 122-145. https://doi.org/10.1108/JSIT-06-2017-0044
Ngoc, A. M., Nishiuchi, H., & Nhu, N. T. (2023). Determinants of carriers' intentions to use electric cargo vehicles in last-mile delivery by extending the technology acceptance model: A case study of Vietnam. International Journal of Logistics Management, 34(1), 210235. https://doi.org/10.1108/IJLM-12-2021-0566
Nikou, S., & Luukkonen, M. (2023). The push-pull factor model and its implications for the retention of international students in the host country. Higher Education, Skills and Work-Based Learning, 14(1), 76-94. https://doi.org/10.1108/HESWBL-04-2023-0084
Oloveze, A. O., Ogbonna, C., Ahaiwe, E., & Ugwu, P. A. (2022). From offline shopping to online shopping in Nigeria: Evidence from African emerging economy. IIM Ranchi Journal of Management Studies, 1(1), 5568. https://doi.org/10.1108/irjms-08-2021-0110
Permana, G. P. L., & Arianti, N. M. (2022). Adopsi digital payment: Eksplorasi pada generasi baby boomer. Widya Akuntansi dan Keuangan, 3(2), 173-190. https://doi.org/10.32795/widyaakuntansi.v3i2.1531
Pitchay, A. A., Ganesan, Y., Zulkifli, N. S., & Khaliq, A. (2022). Determinants of customers' intention to use online food delivery application through smartphone in Malaysia. British Food Journal, 124(3), 732753. https://doi.org/10.1108/BFJ-01-2021-0075
Rachmasari, A., Hariadi, B., & Baridwan, Z. (2023). E-wallet usage behavior: A TAM approach and success model. The International Journal of Accounting and Business Society, 31(2), 137-151. https://doi.org/10.21776/ub.ijabs.2023.31.2.8
Safari, K., Bisimwa, A., & Buzera Armel, M. (2022). Attitudes and intentions toward internet banking in an under developed financial sector. PSU Research Review, 6(1), 3958. https://doi.org/10.1108/PRR-03-2020-0009
Savitri, C., Faddila, S. P., Irmawartini, I., Iswari, H. R., Anam, C., Syah, S., Mulyani, S. R., Sihombing, P. R., Kismawadi, E. R., Pujianto, A., Mulyati, A., Astuti, Y., Adinugroho, W. C., Imanuddin, R., Kristia, K., Nuraini, A., & Siregar, M. T. (2021). STATISTIK MULTIVARIAT DALAM RISET (D. Ahmaddien, Ed.; 1st ed.). CV WIDINA MEDIA UTAMA.
Shaker, A. K., Mostafa, R. H. A., & Elseidi, R. I. (2023). Predicting intention to follow online restaurant community advice: A trust-integrated technology acceptance model. European Journal of Management and Business Economics, 32(2), 185202. https://doi.org/10.1108/EJMBE-01-2021-0036
Singh, S., & Srivastava, R. K. (2020). Understanding the intention to use mobile banking by existing online banking customers: An empirical study. Journal of Financial Services Marketing, 25(34), 8696. https://doi.org/10.1057/s41264-020-00074-w
Sudarsono, H., Tumewang, Y. K., Meutia, & Yulianti. (2024). Antecedents of Muslim students' adoption of mobile banking: An extended TAM and UTAUT approach. Jurnal Organisasi dan Manajemen, 20(1), 114-128. https://doi.org/10.33830/jom.v20i1.7514.2024
Syahruddin, S., Setyosari, P., Ulfa, S., Malang, U. N., & Jaya, H. (2021). Students' acceptance to distance learning during COVID-19. Heliyon, 7(9), e08043. https://doi.org/10.1016/j.heliyon.2021.e08043
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157178. https://doi.org/10.2307/41410412
Wang, X., Yang, M., Li, J., & Wang, N. (2018). Factors of mobile library user behavioral intention from the perspective of information ecology. Electronic Library, 36(4), 705720. https://doi.org/10.1108/EL-03-2017-0046
Zhang, Y., Ahmad, A., Azman, N., & Mingxia, W. (2023). The effect of perceived usefulness, perceived ease of use, and social influence toward purchase intention mediated by trust in live streaming platform. Journal of Law and Sustainable Development, 11(9), e1284. https://doi.org/10.55908/sdgs.v11i9.1284
Al-Rahmi, W. M., Alias, N., Othman, M. S., Marin, V. I., & Tur, G. (2019). Use of e-learning by University students in Malaysian higher educational institutions: A case in Universiti Teknologi Malaysia. IEEE Access, 7, 14268-14276. https://doi.org/10.1109/ACCESS.2019.2899368
Bilal, M., Akram, U., Rasool, H., Yang, X., & Tanveer, Y. (2022). Social commerce isn't the cherry on the cake, its the new cake! How consumers' attitudes and eWOM influence online purchase intention in China. International Journal of Quality and Service Sciences, 14(2), 180196. https://doi.org/10.1108/IJQSS-01-2021-0016
Cimbaljevi?, M., Demirovi? Bajrami, D., Kova?i?, S., Pavlukovi?, V., Stankov, U., & Vuji?i?, M. (2023). Employees' technology adoption in the context of smart tourism development: The role of technological acceptance and technological readiness. European Journal of Innovation Management, 27(8), 2457-2482. https://doi.org/10.1108/EJIM-09-2022-0516
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
Debasa, F., Senapathy, M., & Chovancovα, M. (2023). Do stress and anxiety influence users' intention to make restaurant reservations through mobile apps? European Research on Management and Business Economics, 29(1), 1-15. https://doi.org/10.1016/j.iedeen.2022.100205
Fard, M. H., & Marvi, R. (2020). Viral marketing and purchase intentions of mobile applications users. International Journal of Emerging Markets, 15(2), 287301. https://doi.org/10.1108/IJOEM-06-2018-0291
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139152. https://doi.org/10.2753/MTP1069-6679190202
Hamid, R. S., & Anwar, S. M. (2019). Structural Equation Modeling (SEM) Berbasis Varian: Konsep Dasar dan Aplikasi Dengan Program SmartPLS 3.2.8 dalam Riset Bisnis. PT Inkubator Penulis Indonesia.
Kampa, R. K. (2023). Combining technology readiness and acceptance model for investigating the acceptance of m-learning in higher education in India. Asian Association of Open Universities Journal, 18(2), 105-120. https://doi.org/10.1108/AAOUJ-10-2022-0149
Kelly, A. E., & Palaniappan, S. (2023). Using a technology acceptance model to determine factors influencing continued usage of mobile money service transactions in Ghana. Journal of Innovation and Entrepreneurship, 12(1). https://doi.org/10.1186/s13731-023-00301-3
Kim, S., Kwon, H. J., & Kim, H. (2023). Mobile banking service design attributes for the sustainability of internet-only banks: A case study of KakaoBank. Sustainability, 15(8). https://doi.org/10.3390/su15086428
Leon, S. (2018). Service mobile apps: A millennial generation perspective. Industrial Management and Data Systems, 118(9), 18371860. https://doi.org/10.1108/IMDS-10-2017-0479
Madias, K., Szymkowiak, A., & Borusiak, B. (2023). What builds consumer intention to use smart water meters Extended TAM-based explanation. Water Resources and Economics, 44. https://doi.org/10.1016/j.wre.2023.100233
Maziriri, E. T., Nyagadza, B., Chuchu, T., & Mazuruse, G. (2023). Antecedents of attitudes towards the use of environmentally friendly household appliance products in Zimbabwe: An extension of the theory of planned behaviour. PSU Research Review, 8(3), 749-773. https://doi.org/10.1108/PRR-03-2022-0033
McLean, G., Osei-Frimpong, K., Wilson, A., & Pitardi, V. (2020). How live chat assistants drive travel consumers' attitudes, trust and purchase intentions. International Journal of Contemporary Hospitality Management, 32(5), 17951812. https://doi.org/10.1108/IJCHM-07-2019-0605
Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222.
Mpinganjira, M. (2019). Cognitive absorption and behavioural intentions in virtual health communities. Journal of Systems and Information Technology, 21(1), 122-145. https://doi.org/10.1108/JSIT-06-2017-0044
Ngoc, A. M., Nishiuchi, H., & Nhu, N. T. (2023). Determinants of carriers' intentions to use electric cargo vehicles in last-mile delivery by extending the technology acceptance model: A case study of Vietnam. International Journal of Logistics Management, 34(1), 210235. https://doi.org/10.1108/IJLM-12-2021-0566
Nikou, S., & Luukkonen, M. (2023). The push-pull factor model and its implications for the retention of international students in the host country. Higher Education, Skills and Work-Based Learning, 14(1), 76-94. https://doi.org/10.1108/HESWBL-04-2023-0084
Oloveze, A. O., Ogbonna, C., Ahaiwe, E., & Ugwu, P. A. (2022). From offline shopping to online shopping in Nigeria: Evidence from African emerging economy. IIM Ranchi Journal of Management Studies, 1(1), 5568. https://doi.org/10.1108/irjms-08-2021-0110
Permana, G. P. L., & Arianti, N. M. (2022). Adopsi digital payment: Eksplorasi pada generasi baby boomer. Widya Akuntansi dan Keuangan, 3(2), 173-190. https://doi.org/10.32795/widyaakuntansi.v3i2.1531
Pitchay, A. A., Ganesan, Y., Zulkifli, N. S., & Khaliq, A. (2022). Determinants of customers' intention to use online food delivery application through smartphone in Malaysia. British Food Journal, 124(3), 732753. https://doi.org/10.1108/BFJ-01-2021-0075
Rachmasari, A., Hariadi, B., & Baridwan, Z. (2023). E-wallet usage behavior: A TAM approach and success model. The International Journal of Accounting and Business Society, 31(2), 137-151. https://doi.org/10.21776/ub.ijabs.2023.31.2.8
Safari, K., Bisimwa, A., & Buzera Armel, M. (2022). Attitudes and intentions toward internet banking in an under developed financial sector. PSU Research Review, 6(1), 3958. https://doi.org/10.1108/PRR-03-2020-0009
Savitri, C., Faddila, S. P., Irmawartini, I., Iswari, H. R., Anam, C., Syah, S., Mulyani, S. R., Sihombing, P. R., Kismawadi, E. R., Pujianto, A., Mulyati, A., Astuti, Y., Adinugroho, W. C., Imanuddin, R., Kristia, K., Nuraini, A., & Siregar, M. T. (2021). STATISTIK MULTIVARIAT DALAM RISET (D. Ahmaddien, Ed.; 1st ed.). CV WIDINA MEDIA UTAMA.
Shaker, A. K., Mostafa, R. H. A., & Elseidi, R. I. (2023). Predicting intention to follow online restaurant community advice: A trust-integrated technology acceptance model. European Journal of Management and Business Economics, 32(2), 185202. https://doi.org/10.1108/EJMBE-01-2021-0036
Singh, S., & Srivastava, R. K. (2020). Understanding the intention to use mobile banking by existing online banking customers: An empirical study. Journal of Financial Services Marketing, 25(34), 8696. https://doi.org/10.1057/s41264-020-00074-w
Sudarsono, H., Tumewang, Y. K., Meutia, & Yulianti. (2024). Antecedents of Muslim students' adoption of mobile banking: An extended TAM and UTAUT approach. Jurnal Organisasi dan Manajemen, 20(1), 114-128. https://doi.org/10.33830/jom.v20i1.7514.2024
Syahruddin, S., Setyosari, P., Ulfa, S., Malang, U. N., & Jaya, H. (2021). Students' acceptance to distance learning during COVID-19. Heliyon, 7(9), e08043. https://doi.org/10.1016/j.heliyon.2021.e08043
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157178. https://doi.org/10.2307/41410412
Wang, X., Yang, M., Li, J., & Wang, N. (2018). Factors of mobile library user behavioral intention from the perspective of information ecology. Electronic Library, 36(4), 705720. https://doi.org/10.1108/EL-03-2017-0046
Zhang, Y., Ahmad, A., Azman, N., & Mingxia, W. (2023). The effect of perceived usefulness, perceived ease of use, and social influence toward purchase intention mediated by trust in live streaming platform. Journal of Law and Sustainable Development, 11(9), e1284. https://doi.org/10.55908/sdgs.v11i9.1284
Published
2026-03-31
Section
Original Articles
Copyright (c) 2026 Muhammad Rehan Saputra, Ahmad Najhan Firdiansah, Dewi Tamara
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