Factors Affecting the Behavioral Intention of using Sedayuone Mobile Application

Yanfi Yanfi, Yohannes Kurniawan, Yulyani Arifin


This research evaluated the factors that influenced the behavioral intention to use a mobile application. The case study used was SedayuOne mobile application. The method used was the questionnaires using Unified Theory of Acceptance and Use of Technology (UTAUT2) model. The questionnaires were sent to the 342 members by using email. The result shows that the user habit is the highest factor that influences the user behavioral intention to consume the SEDAYUONE application.
Therefore, to maintain the user behavior, the company must know the user habit and consider promotional strategies to enhance the attractiveness and maintain customer loyalty.


mobile application, behavioral intention, user behavior, UTAUT2

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Baird, G. L., & Bieber, S. L. (2016). The Goldilocks dilemma:

Impacts of multicollinearity--a comparison of simple linear regression, multiple regression, and ordered variable regression models. Journal of Modern Applied Statistical Methods, 15(1), 18.

Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319-340.

Escobar-Rodríguez, T., & Carvajal-Trujillo, E. (2014). Online purchasing tickets for low cost carriers: An application of the unified theory of acceptance and use of technology (UTAUT) model. Tourism Management, 43, 70-88.

Harsono, L. D., & Suryana, L. A. (2014). Factor affecting the user behavior of social media using UTAUT2 Model. In Proceedings of the First Asia-Pacific Conference on Global Business, Economics, Finance

and Social Sciences. Singapore.

Hung, S. Y., Chang, C.-M., & Kuo, S.-R. (2013). User acceptance

of mobile e-government services: An empirical study. Government Information Quarterly, 30(1), 33-44.

Kim, Y. G., & Woo, E. (2016). Consumer acceptance of a Quick Response (QR) code for the food traceability system: Application of an extended technology acceptance model (TAM). Food Research International, 85, 266-272.

Kit, A. K., Ni, A. H., Badri, E. N., & Yee, T. K. (2014). UTAUT2 influencing the behavioural intention to adopt mobile applications (Bachelor Thesis). Universiti Tunku Abdul Rahman.

Masa’deh, R., Tarhini, A., Mohammed, A. B., & Maqableh, M. (2016). Modeling factors affecting student’s usage behaviour of e-learning systems in Lebanon. International Journal of Business and Management, 11(2), 299-312.

Selcuk Korkmaz, D. G. (2014). MVN: An r package for assessing

multivariate normality. The R Journal, 6(2), 151-162.

Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance

test for normality (complete samples). Biometrika, 52(3), 591-611.

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.

Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178.

Wang, M. H. (2016). Factors influencing usage of e-learning systems in Taiwan’s public sector: Applying the UTAUT model. Advances in Management and Applied Economics, 6(6), 63-82.

DOI: https://doi.org/10.21512/comtech.v8i3.3722


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