ISSN: 2225-8329
Open access
This study aims to comprehensively assess the direct and indirect relationships among performance expectancy, effort expectancy, innovative work behavior, facilitating conditions, intention, and the acceptance of digital transformation within the context of online distance learning higher education institutions in Malaysia. We build upon existing theoretical frameworks and empirically validate the relevance of these constructs in this specific educational setting. Data for this research were collected through a carefully structured questionnaire distributed among employees within online flexible distance learning higher education institutions. Our analysis involved a rigorous examination of the associations between latent variables and acceptance, incorporating a range of statistical methods. We conducted regression analysis and hypothesis testing on data gathered from a diverse sample of 387 participants. The statistical backbone of this study was the robust structural equation modelling (SEM) technique. Our findings supported most of the direct relationship hypotheses, except the direct links between performance expectancy and acceptance, and innovative work behavior and acceptance. However, all indirect relationship hypotheses were substantiated, highlighting the intricate dynamics of acceptance in the online distance learning context. The theoretical implications of this study extend the existing body of knowledge on acceptance theories. They shed light on the multifaceted nature of acceptance factors in online distance learning. Future research avenues include exploring additional variables, conducting longitudinal studies to understand the long-term impact of digital transformation, and investigating cultural and contextual factors that may influence acceptance dynamics. This research contributes to a better understanding of the evolving landscape of digital transformation within the realm of online education, offering insights that can inform practice and policy in higher education institutions.
Ahmad, S., Mohd Noor, A. S., Alwan, A. A., Gulzar, Y., Khan, W. Z., & Reegu, F. A. (2023). eLearning acceptance and adoption challenges in Higher Education. Sustainability, 15(7), 6190.
Al-Musharafi, M., & Yusuf, M. (2017). Facilitating conditions for effective blended learning: A study of students' perspectives. International Journal of Emerging Technologies in Learning, 12(2), 12.
Altalhi, M. (2021). Toward a model for acceptance of MOOCs in higher education: The modified UTAUT model for Saudi Arabia. Education and Information Technologies, 26, 1589-1605.
Alyoussef, I. Y. (2023). Acceptance of e-learning in higher education: The role of task-technology fits with the information systems success model. Heliyon, 9(3).
Bond, A., Graham, C. R., & Sibley, S. (2018). Digital transformation in higher education: An Opportunity to rethink teaching and learning. Educause Review, 53(5), 32-47.
Brock, Douglas & Sarason, Irwin & Sanghvi, Hari & Gurung, Regan. (1998). The Perceived Acceptance Scale: Development and Validation. Journal of Social and Personal Relationships. 15. 5-21. 10.1177/0265407598151001.
Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155–159. doi:10.1037/0033-2909.112.1.155
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. doi:10.2307/249008
Davis, Fred & Warshaw, Paul. (1992). What Do Intention Scales Measure? The Journal of General Psychology. 119. 391-407. 10.1080/00221309.1992.9921181.
Ellis, R. A., & Goodyear, P. (2016). Digital learning spaces: A new frontier for research in networked learning. British Journal of Educational Technology, 47(2), 471-484.
Fedorko, I., Ba?ik, R., & Gavurova, B. (2021). Effort expectancy and social influence factors as main determinants of performance expectancy using electronic banking. Banks and Bank Systems, 16(2), 27.
Gafurov, A., Jackson, S., & Sifakis, P. (2020). Digital transformation in higher education: A review of the literature. Journal of Higher Education Policy and Management, 42(4), 410-428.
Giua, C., Materia, V. C., & Camanzi, L. (2022). Smart farming technologies adoption: Which factors play a role in the digital transition?. Technology in Society, 68, 101869.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Thousand Oaks, CA: SAGE.
Hair, J.F., M. Sarstedt, C.M. Ringle, and S.P. Gudergan. (2018). Advanced issues in partial least squares structural equation modeling. Thousand Oakes, CA: Sage Publications.
Hair, J.F., G.T.M. Hult, C.M. Ringle, and M. Sarstedt. 2022. A primer on partial least squares structural equation modeling (PLS-SEM), 3rd edition. Thousand Oaks, CA: Sage.
Hairul, M., Rosli, M., & Hashim, M. (2020). Facilitating conditions for effective learning in blended learning environment. International Journal of Emerging Technologies in Learning, 15(1), 12.
Henseler, J., C.M. Ringle, and M. Sarstedt. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science 43:115–135.
Hu, Y., Zhang, J., & Zhang, X. (2019). The impact of authentic leadership on innovative work behavior: The mediating roles of proactive personality and employee engagement. Frontiers in Psychology, 10, 1645. https://doi.org/10.3389/fpsyg.2019.01645
Hsiao, C. L., & Chen, Y. C. (2016). Antecedents of innovative work behavior: A cross-study. Journal of Business Research, 69(10), 4135-4142. doi:10.1016/j.jbusres.2016.04.027
Ifinedo, P. (2017). Facilitating conditions for effective e-learning: A systematic review of the literature. Computers in Human Behavior, 75, 268-277.
Jackson, S. (2019). Digital transformation and the future of higher education. Routledge.
Janssen, O. (2000) Job Demands, Perceptions of Effort-Reward Fairness, and Innovative Work Behavior. Journal of Occupational and Organizational Psychology, 73, 287-302. http://dx.doi.org/10.1348/096317900167038
Kamil, A. I. M., Ismail, N. A. A., Hassan, A. A., Rooshdi, R. R. R. M., & Marhani, M. A. (2022). Satisfaction of Quantity Surveying Students towards Online Distance Learning (ODL) during Covid-19 Pandemic. Asian Journal of University Education, 18(2), 422-429.
Kebah, M., Raju, V., & Osman, Z. (2019). Growth of online purchase in Saudi Arabia retail industry. International Journal of Recent Technology and Engineering, 8(3), 869-872.. ISSN: 2277-3878
Kebah, M., Raju, V., & Osman, Z. (2019). Online purchasing trend in the retail industry in Saudi. International Journal of Recent Technology and Engineering (IJRTE), 8(3), 865-868. ISSN: 2277-3878
Khan, M. M., Mubarik, M. S., Islam, T., Rehman, A., Ahmed, S. S., Khan, E., & Sohail, F. (2022). How servant leadership triggers innovative work behavior: exploring the sequential mediating role of psychological empowerment and job crafting. European Journal of Innovation Management, 25(4), 1037-1055.
Kurniawan, D. T., Kusnayain, Y. I., Aulisaina, F. I., & Hakim, M. A. R. (2021). EXPLORING THE EXISTANCE OF INNOVATIVE WORK BEHAVIOR AMONG GOVERNMENT EMPLOYEE: HAVE BEEN THERE?. Journal of Indonesian Economy & Business, 36(3).
Kwahk, K.-Y., & Kim, B. (2017). Knowledge sharing and innovative work behavior: Themediating role of psychological safety. Handbook of research on multidisciplinary approaches to innovation, 1, 422-441. doi:10.1177/1938965510362871
Li, X. T., Rahman, A., Connie, G., & Osman, Z. (2020). Examining customers' perception of electronic shopping mall's e-service quality. International Journal of Services, Economics and Management, 11(4), 329-346.
Liengaard, B. D., Sharma, P. N., Hult, G. T. M., Jensen, M. B., Sarstedt, M., Hair, J. F., & Ringle, C. M. (2021). Prediction: Coveted, Yet Forsaken? Introducing a Cross-validated Predictive Ability Test in Partial Least Squares Path Modeling. Decision Sciences, 52(2), 362-392.
Mohamad, L., & Osman, Z. (2025). INTENTION TO ADOPT INNOVATION CULTURE AMONG EMPLOYEES IN ONLINE DISTANCE LEARNING HIGHER EDUCATION INSTITUTIONS. Turkish Online Journal of Distance Education, 26(1), 122-133. ISSN: 1302-6488
Muangmee, C., Kot, S., Meekaewkunchorn, N., Kassakorn, N., & Khalid, B. (2021). Factors determining the behavioral intention of using food delivery apps during COVID-19 pandemics. Journal of Theoretical and Applied Electronic Commerce Research, 16(5), 1297-1310.
Nikolopoulou, K., Gialamas, V., & Lavidas, K. (2021). Habit, hedonic motivation, performance expectancy and technological pedagogical knowledge affect teachers’ intention to use mobile internet. Computers and Education Open, 2, 100041.
Nguyen, H.A.T., Osman, Z., Serrano, J., Suhandoko, A.D.J. & Intaratat, K. (2025) Determinants of environmental awareness toward the green living behaviour of students: the role of family, university and social environmental factors in Hanoi, Vietnam. Environmental & Socio-economic Studies, 2025, Sciendo, vol. 13 no. 1, pp. 1-14. https://doi.org/10.2478/environ-2025-0001
Osman, Z., Mohamad, W., Mohamad, R. K., Mohamad, L., & Sulaiman, T. F. T. (2018). Enhancing students’ academic performance in Malaysian online distance learning institutions. Asia Pacific Journal of Educators and Education, 33, 19-28.
Pangaribuan, C. H., & Wulandar, Y. S. (2019). A crowdfunding platform user acceptance: An empirical examination of performance expectancy, effort expectancy, social factors, facilitating condition, attitude, and behavioral intention. In SU-AFBE 2018: Proceedings of the 1st Sampoerna University-AFBE International Conference, SU-AFBE 2018, 6-7 December 2018, Jakarta Indonesia (p. 346). European Alliance for Innovation.
Podsakoff, P. M., & Organ, D. W. (1986b). Self-Reports in Organizational Research: Problems and Prospects. Journal of Management, 12(4), 531–544. https://doi.org/10.1177/014920638601200408
Rahim, N. N. A., Humaidi, N., Aziz, S. R. A., & Zain, N. H. M. (2022). Moderating Effect ofTechnology Readiness Towards Open and Distance Learning (ODL) Technology Acceptance During COVID-19 Pandemic. Asian Journal of University Education, 18(2), 406-421.
Raju, R., Md Noh, N. H., Ishak, S. N. H., & Eri, Z. D. (2021). Digital Tools Acceptance in Open Distance Learning (ODL) among Computer Science Students during COVID-19 Pandemic: A Comparative Study. Asian Journal of University Education, 17(4), 408-417.
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.
Ringle, C.M., and M. Sarstedt. (2016). Gain more insight from your PLS-SEM results: The importance-performance map analysis. Industrial Management & Data Systems 116: 1865–1886.
Ringle, Christian M., Wende, Sven, & Becker, Jan-Michael. (2022). SmartPLS 4. Oststeinbek: SmartPLS. Retrieved from https://www.smartpls.com
Sair, S. A., & Danish, R. Q. (2018). Effect of performance expectancy and effort expectancy on the mobile commerce adoption intention through personal innovativeness among Pakistani consumers. Pakistan Journal of Commerce and social sciences (PJCSS), 12(2), 501-520.
Shaikh, A. A., Glavee-Geo, R., & Karjaluoto, H. (2021). How relevant are risk perceptions, effort, and performance expectancy in mobile banking adoption?. In Research Anthology on Securing Mobile Technologies and Applications (pp. 692-716). IGI Global.
Shmueli, G., S. Ray, J.M. Velasquez Estrada, and S.B. Chatla. (2016). The elephant in the room: predictive performance of PLS models. Journal of Business Research 69: 4552–4564.
Shmueli, G., M. Sarstedt, J.F. Hair, J.-H. Cheah, H. Ting, S. Vaithilingam, and C.M. Ringle. (2019). Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict. European Journal of Marketing 53: 2322–2347.
Sherer, M., Maddux, J. E., Mercandante, B., Prentice-Dunn, S., Jacobs, B., & Rogers, R. W. (1982). Self-Efficacy Scale [Database record]. APA PsycTests. https://doi.org/10.1037/t01119-000
Shiferaw, K. B., Mengiste, S. A., Gullslett, M. K., Zeleke, A. A., Tilahun, B., Tebeje, T., ... & Mehari, E. A. (2021). Healthcare providers’ acceptance of telemedicine and preference of modalities during COVID-19 pandemics in a low-resource setting: An extended UTAUT model. Plos one, 16(4), e0250220.
Toh, S. Y., Ng, S. A., & Phoon, S. T. (2023). Accentuating technology acceptance among academicians: A conservation of resource perspective in the Malaysian context. Education and information technologies, 28(3), 2529-2545.
Udovita, I. (2020). Digital transformation in higher education: challenges and opportunities. Journal of Educational Technology & Society, 23(1), 28-39.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. doi:10.1287/mnsc.46.2.186.11926
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.
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda oninterventions. Decision Sciences, 39(2), 273-315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
Walrave, M., Waeterloos, C., & Ponnet, K. (2021). Ready or not for contact tracing? Investigating the adoption intention of COVID-19 contact-tracing technology using an extended unified theory of acceptance and use of technology model. Cyberpsychology, Behavior, and Social Networking, 24(6), 377-383.
Wang, Y., & Liao, C. (2014). Extending UTAUT to explain information security behavior: An empirical study of cloud computing adoption. Information & Management, 51(6), 679-689.
Yu, L., Wu, Y., & Wang, H. (2017). A research on the acceptance of enterprise social media: An extended UTAUT perspective. Information & Management, 54(1), 1-12.
Zhang, Z., Liu, M., & Yang, Q. (2021). Examining the external antecedents of innovative work behavior: the role of government support for talent policy. International Journal of Environmental Research and Public Health, 18(3), 1213.
Osman, Z., Serrano, J., Nguyen, H.-A. T., Intaratat, K., & Suhandoko, A. D. J. (2025). Future is Digital: Digital Transformation Acceptance in Online Flexible Distance Learning Higher Education Institutions. International Journal of Academic Research in Accounting, Finance and Management Sciences, 15(2), 183–200.
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