Determinants of LMS Continuance Intention: An Extended UTAUT Approach

Authors

  • Ngakan Nyoman Kutha Krisnawijaya Universitas Pendidikan Nasional
  • Ni Made Dhian Rani Yulianti Universitas Pendidikan Nasional
  • Ni Putu Dhanan Kumaradewi M Universitas Pendidikan Nasional
  • Anak Agung Adi Wiryya Putra Universitas Pendidikan Nasional

DOI:

https://doi.org/10.35870/ijmsit.v6i2.7403

Keywords:

Learning Management System, UTAUT, User Satisfaction, Continuation Intention, International Students

Abstract

This study aims to analyze the factors influencing user satisfaction and continuance intention of Learning Management Systems (LMS) among international students in a mandatory academic ecosystem. This study has significant significance in bridging the theoretical gap between the cognitive adoption model (UTAUT) and the affective post-adoption evaluation (ECM) in a tech-savvy cross-cultural user segment. Using a causal-associative quantitative design, data were collected through a structured online questionnaire from 71 International Undergraduate Program (IUP) student respondents selected through a purposive sampling method. Data analysis was conducted using the Partial Least Squares–Structural Equation Modeling (PLS-SEM) method with the assistance of SmartPLS software version 4.0. The results of the path analysis showed that effort expectancy and social influence had a positive and significant effect on satisfaction, while performance expectancy and facilitating conditions did not show a significant effect. Furthermore, satisfaction was proven to exclusively mediate the effect of effort expectancy on continuance intention of LMS. The implications of this research confirm that in institutionally mandated systems, user motivation shifts to academic compliance. Therefore, higher education institutions are advised to prioritize eliminating everyday technical barriers through intuitive interface design to foster genuine international student satisfaction.

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Author Biographies

  • Ngakan Nyoman Kutha Krisnawijaya, Universitas Pendidikan Nasional

    Information Technology Study Program, Faculty of Engineering and Informatics, Universitas Pendidikan Nasional, Denpasar City, Bali Province, Indonesia

  • Ni Made Dhian Rani Yulianti, Universitas Pendidikan Nasional

    Management Study Program, Faculty of Economics and Business, Universitas Pendidikan Nasional, Denpasar City, Bali Province, Indonesia

  • Ni Putu Dhanan Kumaradewi M, Universitas Pendidikan Nasional

    Management Study Program, Faculty of Economics and Business, Universitas Pendidikan Nasional, Denpasar City, Bali Province, Indonesia

  • Anak Agung Adi Wiryya Putra, Universitas Pendidikan Nasional

    Information Technology Study Program, Faculty of Engineering and Informatics, Universitas Pendidikan Nasional, Denpasar City, Bali Province, Indonesia

References

Abbad, M. M. M. (2021). Using the UTAUT model to understand students' usage of e-learning systems in developing countries. Education and Information Technologies, 26(6), 7205–7224. https://doi.org/10.1007/s10639-021-10573-5

Ahmad, N., Umar, N., Kadar, R., & Othman, J. (2020). Factors affecting students' acceptance of e-learning system in higher education. Journal of Computing Research and Innovation, 5(2), 54–65. https://doi.org/10.24191/jcrinn.v5i2.134

Al Mulhem AA (2025) A model for sustainable mobile education beyond the COVID-19 pandemic. Front. Educ. 10:1657635. doi: 10.3389/feduc.2025.1657635

Alalwan, A. A. (2020). Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse. International Journal of Information Management, 50, 28–44. https://doi.org/10.1016/j.ijinfomgt.2019.04.008

Aldiabat, K., Gharaibeh, M. K., & AlQudah, N. F. (2024). Assessment of student satisfaction with e-learning in Jordan using TAM and UTAUT as a mediator for synchronous and asynchronous learning. International Journal on Informatics Visualization, 8(3), 1361–1369.

Al-Fraihat, D., Joy, M., Masa'deh, R., & Sinclair, J. (2020). Evaluating e-learning systems success: An empirical study. Computers in Human Behavior, 102, 67–86. https://doi.org/10.1016/j.chb.2019.08.004

Alharbi, A., Aljojo, N., Zainol, A., Alshutayri, A., Alharbi, B., Aldhahri, E., Khairullah, E. F., & Almandeel, S. (2021). Identification of critical factors affecting the students' acceptance of learning management system (LMS) in Saudi Arabia. International Journal of Innovation, 9(2), 353–388. https://doi.org/10.5585/iji.v9i2.19652

Almamary, Y. H. S., Siddiqui, M. A., Abdalraheem, S. G., Jazim, F., Rashed, R. Q., Alquhaif, A. S., & Alhaji, A. A. (2023). Factors impacting Saudi students' intention to adopt learning management systems using the TPB and UTAUT integrated model. Journal of Science and Technology Policy Management, 14(6), 1200–1223. https://doi.org/10.1108/JSTPM-04-2022-0068

Almogren, A. S. (2022). Art education lecturers' intention to continue using the Blackboard during and after the COVID-19 pandemic: An empirical investigation into the UTAUT and TAM model. Frontiers in Psychology, 13, 944335. https://doi.org/10.3389/fpsyg.2022.944335

Al-Rahmi, W. M., Yahaya, N., Aldraiweesh, A. A., Alamri, M. M., Aljarboa, N. A., Alturki, U., & Aljeraiwi, A. A. (2019). Integrating technology acceptance model with innovation diffusion theory: An empirical investigation on students' intention to use e-learning systems. IEEE Access, 7, 26797–26809. https://doi.org/10.1109/ACCESS.2019.2899368

Alzahrani, L., & Seth, K. P. (2021). Factors influencing students' satisfaction with continuous use of learning management systems during the COVID-19 pandemic: An empirical study. Education and Information Technologies, 26(6), 6787–6805. https://doi.org/10.1007/s10639-021-10492-5

Amsal, A. A., Putri, S. L., Rahadi, F., & Fitri, M. E. Y. (2021, February). Perceived satisfaction and perceived usefulness of e-learning: The role of interactive learning and social influence. In The 3rd international conference on educational development and quality assurance (ICED-QA 2020) (pp. 535-541). Atlantis Press. https://doi.org/10.2991/assehr.k.210202.092

Anderson, R. E., & Srinivasan, S. S. (2003). E‐satisfaction and e‐loyalty: A contingency framework. Psychology & marketing, 20(2), 123-138. https://doi.org/10.1002/mar.10063

Ashrafi, A., Zareravasan, A., Rabiee Savoji, S., & Amani, M. (2022). Exploring factors influencing students' continuance intention to use the learning management system (LMS): A multi-perspective framework. Interactive Learning Environments, 30(8), 1475–1497. https://doi.org/10.1080/10494820.2020.1734028

asuthevan K, Vaithilingam S, Ng JWJ (2024) Academics’ continuance intention to use learning technologies during COVID-19 and beyond. PLoS ONE 19(1): e0295746. https://doi.org/10.1371/journal.pone.0295746

Batucan, G. B., Gonzales, G. G., Balbuena, M. G., Pasaol, K. R. B., Seno, D. N., & Gonzales, R. R. (2022). An extended UTAUT model to explain factors affecting online learning system amidst COVID-19 pandemic: The case of a developing economy. Frontiers in Artificial Intelligence, 5, 768831. https://doi.org/10.3389/frai.2022.768831

Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model1. MIS quarterly, 25(3), 351-370. https://doi.org/10.2307/3250921

Cheng, D., Shi, J., Yang, J., & Yu, H. (2024). Assessment of blended learning courses based on unified theory of acceptance and use of technology in higher education. Journal of Computer Science and Technology Studies, 6(3), 97–114. https://doi.org/10.32996/jcsts.2024.6.3.10

Das, R. L. (2023). Students' adoption of Google Classroom investigated by technology acceptance model. MIER Journal of Educational Studies, Trends & Practices, 13(1), 98–113. https://doi.org/10.52634/mier/2023/v13/i1/2337

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Sage.

Hien, D. T. T., & Nhung, T. T. (2026). Determinants of online learning application effectiveness: Evidence from Vietnam. International Journal of Data and Network Science, 10(3), 1099–1106. https://doi.org/10.5267/j.ijdns.2026.4.017

Lee, K. C., & Chung, N. (2009). Understanding factors affecting trust in and satisfaction with mobile banking in Korea: A modified DeLone and McLean's model perspective. Interacting with Computers, 21(5–6), 385–392. https://doi.org/10.1016/j.intcom.2009.06.004

Likert, R. (1932). A technique for the measurement of attitudes. Archives of psychology.

Malanga, A. C. M., Bernardes, R. C., Borini, F. M., Pereira, R. M., & Rossetto, D. E. (2022). Towards integrating quality in theoretical models of acceptance: An extended proposed model applied to e-learning services. British Journal of Educational Technology, 53(1), 8–22. https://doi.org/10.1111/bjet.13091

Marinković, V., Đorđević, A., & Kalinić, Z. (2020). The moderating effects of gender on customer satisfaction and continuance intention in mobile commerce: A UTAUT-based perspective. Technology Analysis and Strategic Management, 32(3), 306–318. https://doi.org/10.1080/09537325.2019.1655537

Masrani SA, Mohd Amin MR, Sivakumaran VM, Piaralal SK (2023), "Important factors in measuring learners' satisfaction and continuance intention in open and distance learning (ODL) institutions". Higher Education, Skills and Work-based Learning, Vol. 13 No. 3 pp. 587–608, doi: https://doi.org/10.1108/HESWBL-12-2022-0274

Nıcholas-omoregbe, O. S., Azeta, A. A., Chıazor, İ. A., & Omoregbe, N. (2017). Predicting The Adoption of E-Learning Management System: A Case of Selected Private Universities In Nigeria. Turkish Online Journal of Distance Education, 18(2), 106-121. https://doi.org/10.17718/tojde.306563

Patil, H., & Undale, S. (2023). Willingness of university students to continue using e-learning platforms after compelled adoption of technology: Test of an extended UTAUT model. Education and Information Technologies, 28, 14943–14965. https://doi.org/10.1007/s10639-023-11778-6

Rawashdeh, B., & Rawashdeh, A. (2021). Factors influencing the usage of XBRL tools. Management Science Letters, 11(4), 1345-1356. https://doi.org/10.5267/j.msl.2020.11.005

Raza, S. A., Qazi, W., Khan, K. A., & Salam, J. (2021). Social isolation and acceptance of the learning management system (LMS) in the time of COVID-19 pandemic: An expansion of the UTAUT model. Journal of Educational Computing Research, 59(2), 183–208. https://doi.org/10.1177/0735633120960421

Salgado-Chamorro, D. L., Noble-Ramos, V. M., & Gómez-Jaramillo, S. (2023). Adoption of learning management systems in face-to-face learning: A systematic literature review of variables, relationships, and models. International Journal of Learning, Teaching and Educational Research, 22(12), 326–350. https://doi.org/10.26803/ijlter.22.12.16

Song, Y., Gui, L., Wang, H., & Yang, Y. (2023). Determinants of continuous usage intention in community group buying platform in China: Based on the information system success model and the expanded technology acceptance model. Behavioral Sciences, 13(11), 941. https://doi.org/10.3390/bs13110941

Sugiyono. (2019). Metode penelitian kuantitatif, kualitatif, dan R&D. Alfabeta.

Teng, Z., Cai, Y., Gao, Y., Zhang, X., & Li, X. (2022). Factors affecting learners' adoption of an educational metaverse platform: An empirical study based on an extended UTAUT model. Mobile Information Systems, 2022, 5479215. https://doi.org/10.1155/2022/5479215

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

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 Technology1. MIS Quarterly 1 March 2012; 36 (1): 157–178. https://doi.org/10.2307/41410412

Wandira, R., Fauzi, A., & Nurahim, F. (2024). Analysis of factors influencing behavioral intention to use cloud-based academic information system using extended technology acceptance model (TAM) and expectation-confirmation model (ECM). Journal of Information Systems Engineering and Business Intelligence, 10(2), 179–190. https://doi.org/10.20473/jisebi.10.2.179-190

Wang, Y. S., Tseng, T. H., Wang, W. T., Shih, Y. W., & Chan, P. Y. (2019). Developing and validating a mobile catering app success model. International Journal of Hospitality Management, 77, 19–30. https://doi.org/10.1016/j.ijhm.2018.06.002

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Published

2026-07-03

How to Cite

Krisnawijaya, N. N. K., Yulianti, N. M. D. R., Kumaradewi M, N. P. D., & Putra, A. A. A. W. (2026). Determinants of LMS Continuance Intention: An Extended UTAUT Approach. International Journal of Management Science and Information Technology, 6(2), 1087-1098. https://doi.org/10.35870/ijmsit.v6i2.7403

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