Salman faris Insani


The purpose of this research is to test and analyze the mediating role of resistance in the factors influencing intention use mobile learning which includes relative advantages, complexity, inertia, and innovative. The sample in this study was 171 high school students in Indonesia. The sampling method used is non-probability sampling, while the technique used is purposive sampling. Hypothesis testing in this study using Structural Equation Modeling. Results of this study shows that the complexity has an effect on intention to use mobile learning and inertia affect mobile learning resistance. Relative advantages and innovative has no effect on intention to use mobile learning. In addition, the relative advantages and complexity has no effect on mobile learning resistance. Mobile learning resistance does not mediate the relative advantage effect on intention to use mobile learning, whereas mobile learning resistance partially mediates the effect of complexity on intention to use mobile learning.


relative advantage; complexity; resistance; intention to use; mobile learning

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Abbas, M., Shahid Nawaz, M., Ahmad, J., & Ashraf, M. (2017). The effect of innovation and consumer related factors on consumer resistance to innovation. Cogent Business and Management, 4(1).

Al-Gahtani, S. S. (2003). Computer technology adoption in Saudi Arabia: Correlates of perceived innovation attributes. Information Technology for Development, 10(1), 57–69.

Al-Jabri, brahim M., & Sohail, M. S. (2012). Mobile banking adoption: Application of diffusion of innovation theory. Journal of Electronic Commerce Research, 13(4), 379–391.

Au, Y. A., & Kauffman, R. J. (2008). The economics of mobile payments: Understanding stakeholder issues for an emerging financial technology application. Electronic Commerce Research and Applications, 7(2), 141–164.

Bovey, W. H., & Hede, A. (2001). Resistance to organisational change: The role of defence mechanisms. Journal of Managerial Psychology, 16(7), 534–548.

Cheung, W., Chang, M. K., & Lai, V. S. (2000). Prediction of Internet and World Wide Web usage at work: A test of an extended Triandis model. Decision Support Systems, 30(1), 83–100.

Crompton, H., & Burke, D. (2018). The use of mobile learning in higher education: A systematic review. Computers and Education, 123(September 2017), 53–64.

Dahlberg, T., Mallat, N., Ondrus, J., & Zmijewska, A. (2008). Past, present and future of mobile payments research: A literature review. Electronic Commerce Research and Applications, 7(2), 165–181.

Damar, A. M. (2021). Ruangguru Kantongi 22 Juta Pengguna hingga Akhir 2020. Liputan6. (diakses pada 28 mei 2022)

Ferdinand, A. (2014). Structural Equation Modeling Dalam Penelitian Manajemen: Aplikasi Model-Model Rumit Dalam Penelitian untuk Skripsi, Tesis, dan Disertasi Doktor (5th ed.). Seri Pustaka Kunci.

Ferneley, E. H., & Sobreperez, P. (2006). Resist, comply or workaround? An examination of different facets of user engagement with information systems. European Journal of Information Systems, 15(4), 345–356.

Furió Ferri, D., Juan, M., Segui, I., & Vivó Hernando, R. . (2015). Mobile learning vs . traditional classroom lessons : A comparative study . Journal of Computer Assisted Learning . 31 ( 3 ). Journal of Computer Assisted Learning, 31, 189–201.

Gal, D. (2006). A psychological law of inertia and the illusion of loss aversion. Judgment and Decision Making, 1(1), 23–32.

Huang, R. T. (2014). Exploring the moderating role of self-management of learning in mobile english learning. Educational Technology and Society, 17(4), 255–267.

Joo., Y. J., Lim, K. Y., & Lim, E. (2014). Investigating the structural relationship among perceived innovation attributes, intention to use and actual use of mobile learning in an online university in South Korea. Australasian Journal of Educational Technology, 30(4), 427–439.

Joo, Y. J., Kim, N., & Kim, N. H. (2016). Factors predicting online university students’ use of a mobile learning management system (m-LMS). Educational Technology Research and Development, 64(4), 611–630.

Kim, H. J., Lee, J. M., & Rha, J. Y. (2017). Understanding the role of user resistance on mobile learning usage among university students. Computers and Education, 113, 108–118.

Lee, H., Lim, H., Jolly, L. D., Lee, J., & Lee, H. (2009). Consumer Lifestyles and Adoption of High- Technology Products : A Case of South Korea. Journal of International Consumer Marketing, 21(2), 153–167.

Lee, S. (2013). An integrated adoption model for e-books in a mobile environment: Evidence from South Korea. Telematics and Informatics, 30(2), 165–176.

Luarn, P., & Lin, H. H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21(6), 873–891.

Macfadyen, L. P., & Dawson, S. (2012). Why e-learning analytics fail to inform an institutional strategic plan. Educational Technology and Society, 15(3), 149–163.

Mallat, N. (2006). Exploring Consumer Adoption of Mobile Payments - A Qualitative Study. Presented at Helsinki Global Mobility Roundtable. 1–14.

McCloskey, D. W. (2011). The Importance of Ease of Use, Usefulness, and Trust to Online Consumers. End-User Computing, January 2008.

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.

Mouza, C., & Barrett-Greenly, T. (2015). Bridging the app gap: An examination of a professional development initiative on mobile learning in urban schools. Computers and Education, 88, 1–14.

Parasuraman, A., & Colby, C. L. (2015). An Updated and Streamlined Technology Readiness Index: TRI 2.0. Journal of Service Research, 18(1), 59–74.

Pitari, D. F., Gayatri, G., Furinto, A., & Assauri, S. (2020). Integration Of Intention And Resistance In Adopting Near Field Communication-Based Mobile Payment Innovation. 9(04), 857–866.

Polites, & Karahanna. (2012). Shackled to the Status Quo: The Inhibiting Effects of Incumbent System Habit, Switching Costs, and Inertia on New System Acceptance. MIS Quarterly, 36(1), 21.

Püschel, J., Mazzon, J. A., & Hernandez, J. M. C. (2010). Mobile banking: Proposition of an integrated adoption intention framework. International Journal of Bank Marketing, 28(5), 389–409.

Ram, S., & Sheth, J. N. (1989). Consumer resistance to innovations: The marketing problem and its solutions. Journal of Consumer Marketing, 6(2), 5.

Sanford, C., & Oh, H. (2010). The role of user resistance in the adoption of a mobile data service. Cyberpsychology, Behavior, and Social Networking, 13(6), 663–672.

Sekaran, U. & Bougie, R. (2017). Metode Penelitian untuk Bisnis: Pendekatan Pengembangan-Keahlian (6th ed.). Jakarta: Penerbit Salemba Empat.

Sugiyono. (2017). Metode Penelitian Kuantitatif, Kualitatif, dan R&D. Bandung: Alfabeta.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2012). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478.

Wang, Y. S., Wang, Y. M., Lin, H. H., & Tang, T. I. (2003). Determinants of user acceptance of Internet banking: An empirical study. In International Journal of Service Industry Management (Vol. 14, Issue 5).

Warshaw, P. R., & Davis, F. D. (1985). Disentangling behavioral intention and behavioral expectation. Journal of Experimental Social Psychology, 21(3), 213–228.

Zhang, L., Wen, H., Li, D., Fu, Z., & Cui, S. (2010). E-learning adoption intention and its key influence factors based on innovation adoption theory. Mathematical and Computer Modelling, 51(11–12), 1428–1432.



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Tim Redaksi:

Jurusan Manajemen Fakultas Ekonomi dan Bisnis, Universitas Syiah Kuala

Lantai II Gedung Induk

Darussalam, Banda Aceh, 2311


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