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Abstract
Penelitian ini bertujuan menganalisis pengaruh Technology Acceptence Model dan risiko persepsian pada niat beralih penguna aplikasi dan permainan daring freemium versi gratis ke versi berbayar. Ukuran sampel dalam penelitian ini adalah 200 responden yang merupakan mahasiswa pengguna aplikasi dan permainan daring freemium versi gratis. Dari hasil analisis menggunakan Structural Equation Modelling ditemukan bahwa kegunaan persepsian berpengaruh positif pada sikap, kemudahan penggunaan persepsian tidak berpengaruh positif pada sikap. Sedangkan, risiko finansial persepsian tidak berpengaruh positif pada sikap, risiko kinerja persepsian berpengaruh positif pada sikap, dan sikap berpengaruh positif pada niat beralih menggunakan aplikasi dan permainan daring freemium versi berbayar.
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References
- Awa, H. O., Eze, S. C., Urieto, J. E., & Inyang, B. J. (2011). Upper echelon theory (UET): A major determinant of information technology (IT) adoption by SMEs in Nigeria. Journal of Systems and Information Technology.
- Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16(1), 74-94.
- Carter, L., & Bélanger, F. (2005). The utilization of e?government services: citizen trust, innovation and acceptance factors. Information systems journal, 15(1), 5-25.
- Cheng, H. H., & Huang, S. W. (2013). Exploring antecedents and consequence of online group-buying intention: An extended perspective on theory of planned behavior. International Journal of Information Management, 33(1), 185-198.
- Cunningham, S., 1967. The major dimensions of perceived risk. In: D. Cox (Ed.), Risk Taking and Information Handling in Consumer Behavior. Harvard University Press, Cambridge, MA.
- Dahiya, R., & Gayatri. (2017). Investigating Indian car buyers’ decision to use digital marketing communication: an empirical application of decomposed TPB. Vision, 21(4), 385-396.
- Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319 – 340
- Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: a perceived risk facets perspective. International journal of human-computer studies, 59(4), 451-474.
- Forsythe, S. M., & Shi, B. (2003). Consumer patronage and risk perceptions in Internet shopping. Journal of Business research, 56(11), 867-875.
- George, A., & Kumar, G. G. (2013). Antecedents of customer satisfaction in internet banking: Technology acceptance model (TAM) redefined. Global business review, 14(4), 627-638.
- Kaplan, L. B., Szybillo, G. J., & Jacoby, J. (1974). Components of perceived risk in product purchase: A cross-validation. Journal of applied Psychology, 59(3), 287.
- Lee, J., Kim, J., & Choi, J. Y. (2019). The adoption of virtual reality devices: The technology acceptance model integrating enjoyment, social interaction, and strength of the social ties. Telematics and Informatics, 39, 37-48.
- Lee, M. C. (2009). Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electronic commerce research and applications, 8(3), 130-141.
- Lu, H. P., Hsu, C. L., & Hsu, H. Y. (2005). An empirical study of the effect of perceived risk upon intention to use online applications. Information management & computer security.
- Lu, Y., Zhou, T., & Wang, B. (2009). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in human behavior, 25(1), 29-39.
- Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International journal of electronic commerce, 7(3), 101-134.
- Putra, H. B., Pradita, N., & Hayuningtias, K. A. (2020). Prediksi Niat Penggunaan Aplikasi Dan Permainan Daring Freemium Versi Berbayar Dengan Menggunakan Model TPB. Managament Insight: Jurnal Ilmiah Manajemen, 15(2), 130-143.
- Putra, H. B., Pradita, N., & Mansyur, A. (2022). Integration Model TPB And Perceived Risk Of Intention Of Use Applications And Games Online Freemium Paid Version: Indonesian Students Context. novbiz: Jurnal Inovasi Bisnis 9 (2021) 110-116
- Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
- Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model. Information & management, 42(5), 719-729.
- Wu, L., & Chen, J. L. (2005). An extension of trust and TAM model with TPB in the initial adoption of on-line tax: an empirical study. International Journal of Human-Computer Studies, 62(6), 784-808.
- Xie, Q., Song, W., Peng, X., & Shabbir, M. (2017). Predictors for e-government adoption: integrating TAM, TPB, trust and perceived risk. The Electronic Library.
- Xie, Q., Song, W., Peng, X., & Shabbir, M. (2017). Predictors for e-government adoption: integrating TAM, TPB, trust and perceived risk. The Electronic Library.
- Yang, H. C., & Zhou, L. (2011). Extending TPB and TAM to mobile viral marketing: An exploratory study on American young consumers’ mobile viral marketing attitude, intent and behavior. Journal of Targeting, Measurement and Analysis for Marketing, 19(2), 85-98.
References
Awa, H. O., Eze, S. C., Urieto, J. E., & Inyang, B. J. (2011). Upper echelon theory (UET): A major determinant of information technology (IT) adoption by SMEs in Nigeria. Journal of Systems and Information Technology.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16(1), 74-94.
Carter, L., & Bélanger, F. (2005). The utilization of e?government services: citizen trust, innovation and acceptance factors. Information systems journal, 15(1), 5-25.
Cheng, H. H., & Huang, S. W. (2013). Exploring antecedents and consequence of online group-buying intention: An extended perspective on theory of planned behavior. International Journal of Information Management, 33(1), 185-198.
Cunningham, S., 1967. The major dimensions of perceived risk. In: D. Cox (Ed.), Risk Taking and Information Handling in Consumer Behavior. Harvard University Press, Cambridge, MA.
Dahiya, R., & Gayatri. (2017). Investigating Indian car buyers’ decision to use digital marketing communication: an empirical application of decomposed TPB. Vision, 21(4), 385-396.
Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319 – 340
Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: a perceived risk facets perspective. International journal of human-computer studies, 59(4), 451-474.
Forsythe, S. M., & Shi, B. (2003). Consumer patronage and risk perceptions in Internet shopping. Journal of Business research, 56(11), 867-875.
George, A., & Kumar, G. G. (2013). Antecedents of customer satisfaction in internet banking: Technology acceptance model (TAM) redefined. Global business review, 14(4), 627-638.
Kaplan, L. B., Szybillo, G. J., & Jacoby, J. (1974). Components of perceived risk in product purchase: A cross-validation. Journal of applied Psychology, 59(3), 287.
Lee, J., Kim, J., & Choi, J. Y. (2019). The adoption of virtual reality devices: The technology acceptance model integrating enjoyment, social interaction, and strength of the social ties. Telematics and Informatics, 39, 37-48.
Lee, M. C. (2009). Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electronic commerce research and applications, 8(3), 130-141.
Lu, H. P., Hsu, C. L., & Hsu, H. Y. (2005). An empirical study of the effect of perceived risk upon intention to use online applications. Information management & computer security.
Lu, Y., Zhou, T., & Wang, B. (2009). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in human behavior, 25(1), 29-39.
Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International journal of electronic commerce, 7(3), 101-134.
Putra, H. B., Pradita, N., & Hayuningtias, K. A. (2020). Prediksi Niat Penggunaan Aplikasi Dan Permainan Daring Freemium Versi Berbayar Dengan Menggunakan Model TPB. Managament Insight: Jurnal Ilmiah Manajemen, 15(2), 130-143.
Putra, H. B., Pradita, N., & Mansyur, A. (2022). Integration Model TPB And Perceived Risk Of Intention Of Use Applications And Games Online Freemium Paid Version: Indonesian Students Context. novbiz: Jurnal Inovasi Bisnis 9 (2021) 110-116
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model. Information & management, 42(5), 719-729.
Wu, L., & Chen, J. L. (2005). An extension of trust and TAM model with TPB in the initial adoption of on-line tax: an empirical study. International Journal of Human-Computer Studies, 62(6), 784-808.
Xie, Q., Song, W., Peng, X., & Shabbir, M. (2017). Predictors for e-government adoption: integrating TAM, TPB, trust and perceived risk. The Electronic Library.
Xie, Q., Song, W., Peng, X., & Shabbir, M. (2017). Predictors for e-government adoption: integrating TAM, TPB, trust and perceived risk. The Electronic Library.
Yang, H. C., & Zhou, L. (2011). Extending TPB and TAM to mobile viral marketing: An exploratory study on American young consumers’ mobile viral marketing attitude, intent and behavior. Journal of Targeting, Measurement and Analysis for Marketing, 19(2), 85-98.