Online distance learning in higher education institutions is experiencing significant growth and is increasingly adopting digital transformation. However, employee acceptance and adoption of these changes present a major challenge. This study investigates the factors influencing employee acceptance of digital transformation in online distance learning institutions. It examines the influence of latent variables, such as effort expectancy, performance expectancy, self-efficacy, and intention, on the acceptance of digital transformation. It also expands on existing theoretical frameworks and provides empirical evidence of their importance. Data was collected from 387 employees using a structured questionnaire, and statistical analysis, including regression and PLS structural equation modelling, was used to assess the relationships between variables. The findings revealed that effort expectancy, performance expectancy, self-efficacy, and intention significantly influenced employee acceptance of digital transformation. The indirect relationship hypotheses are also supported. Several practical implications and strategies such as user-friendly technologies, effective communications, professional development opportunities and involvement in decision-making processes are identified as key strategies to enhance employee acceptance. The study contributes to the existing knowledge of acceptance theories and suggests avenues for future research including exploring additional variables such as culture and contextual factors and conducting longitudinal studies to understand the long-term effects of digital transformation.
Al-Kumaim, N. H., Mohammed, F., Gazem, N. A., Fazea, Y., Alhazmi, A. K., & Dakkak, O.
(2021). Exploring the impact of transformation to fully online learning during COVID-19 on Malaysian university students' academic life and performance. International Journal of Interactive Mobile Technologies, 15(5).
Ajzen, I., & Fishbein, M. (1980), Understanding Attitudes and Predicting Social Behavior, Prentice-Hall.
Ajzen, I. (1991). The theory of planned behaviour. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
Benavides, L. M. C., Arias, T. J. A., Serna, A. M. D., Bedoya, B. J. W., & Burgos, D. (2020). Digital transformation in higher education institutions: A systematic literature review. Sensors, 20(11), 3291.
Bozintan, A., George, C., Lucian, E., & Pinco, O. (2023). The impact of digital transformation on strategic management. The Annals of the University of Oradea, Economic Sciences TOM XXXII, Issue 1, July
Chaouali, W., Souiden, N., & Ringle, C. M. (2021). Elderly customers’ reactions to service
failures: The role of future time perspective, wisdom and emotional intelligence.
Journal of Services Marketing 35: 65–77.
Damberg, S. (2021a). Predicting future use intention of fitness apps among fitness app users in the United Kingdom: The role of health consciousness. International Journal of Sports
Marketing and Sponsorship. https:// doi. org/ 10. 1108/ ijsms- 01- 2021- 0013.
Damberg, S. (2021b). Wahrgenommene Reputation der Genossenschaftsbanken und
nachhaltige Zufriedenheit ihrer Mitglieder-Kunden in Deutschland. Zeitschrift fur das gesamte Genossenschaftswesen 71: 70–89.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319–340. https://doi.org/10.2307/249008
Fernandez-Vidal, J., Perotti, F. A., Gonzales, R., & Gasco, J. (2022) Managing digital transformation: The view from the top. Journal of Business Research 152, 29-41.
Giang, N. T. H., Hai, P. T. T., Tu, N. T. T., & Tan, P. X. (2021). Exploring the readiness for
digital transformation in a higher education institution towards industrial revolution 4.0. International Journal of Engineering Pedagogy, 11(2), 4-24.
Grosseck, G., Mali?a, L., & Bunoiu, M. (2020). Higher education institutions towards digital
transformation—the WUT case. In European higher education area: Challenges for a new decade (pp. 565-581). Springer International Publishing.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modelling (PLS-SEM) (2nd ed.). Sage.
Hair, J. F., Sarstedt. M., Ringle, C. M., & Gudergan, S. P. (2018). Advanced issues in partial
least squares structural equation modelling. Sage.
Henseler, J., Ringle, C. M., & Sarstedt. M. (2015). A new criterion for assessing discriminant
validity in variance-based structural equation modelling. Journal of the Academy of
Marketing Science 43:115–135.
Jambulingam, M. (2013). Behavioural intention to adopt mobile technology among tertiary students. World Applied Sciences Journal, 22(9), 1262-1271
Kinis, F., Tanova, C. (2022). Can I trust my phone to replace my wallet? The determinants of e-wallet adoption in North Cyprus. Journal of Theoretical and Applied Electronic Commerce Research, 17, 1696-1715. Doi: https://doi.org/10.3390/jtaer17040086
Lazim, C. S. L. M., Ismail, N. D. B., & Tazilah, M. D. A. K. (2021). Application of
technology acceptance model (TAM) towards online learning during COVID-19 pandemic: Accounting students’ perspective. International Journal of Business Economics and Law, 24(1), 13-20.
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 modelling. Decision Sciences, 52(2), 362-392.
Lu, H. P., & Wang, J. C. (2023). Exploring the effects of sudden institutional coercive
pressure on digital transformation in colleges from teachers’ perspective. Education and Information Technologies, 1-25.
Moslehpour, M., Dadvari, A., Nugroho, W., & Do, B. (2020), The dynamic stimulus of social media marketing on purchase intention of Indonesian airline products and services. Asia Pacific Journal of Marketing and Logistics, 33(2), 563-585. DOI 10.1108/APJML-07-2019-0442
Mujahed, H. M., Ahmed, E. M., & Samikon, S. A. (2021). Factors influencing Palestinian small and medium enterprises’ intention to adopt mobile banking. Journal of Science and Technology Policy Management, 13(2), 561-584. DOI 10.1108/JSTPM-05-2020-0090
Othman, I. W., Mokhtar, S., Tham, A., & Yong, K. (2021). The Significance of
Entrepreneurship Education Literacy in The Era of Digital Transformation: Graduates of the Post-Pandemic Covid-19 Unemployment Crisis. International Journal of Accounting, 6(37).
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
Raju, R., Noh, M. 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.
Richter, N. F., Sinkovics, R. R., Ringle, C. M., & Schlägel, C. (2016). A critical look at the use
of SEM in international business research. International Marketing Review 33: 376–404.
Ringle, C. M., & Sarstedt, M. (2016). Gain more insight from your PLS-SEM results: The
importance-performance map analysis. Industrial Management & Data Systems 116: 1865–1886.
Ringle, C. M., Sarstedt, M., Mitchell, R., & Gudergan, S. P. (2020). Partial least squares
structural equation modelling in HRM research. The International Journal of Human
Resource Management 31: 1617–1643.
Ringle, C. M., Wende, Sven, & Becker, Jan-Michael. (2022). SmartPLS 4. Oststeinbek:
SmartPLS. Retrieved from https://www.smartpls.com
Rof, A., Bikfalvi, A., & Marques, P. (2022). Digital Transformation in Higher Education:
Intelligence in Systems and Business Models. In Intelligent Systems in Digital Transformation: Theory and Applications (pp. 429-452). Cham: Springer International Publishing.
Shmueli, G., Sarstedt, M., J.F. Hair, J.-H. Cheah, H. Ting, S. Vaithilingam, & Ringle, C. M.
(2019). Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict.
European Journal of Marketing 53: 2322–2347.
Schloderer, M. P., Sarstedt, M., & Ringle, C. M. (2014). The relevance of reputation in the
non-profit sector: The moderating effect of sociodemographic characteristics.
International Journal of Nonprofit and Voluntary Sector Marketing 19: 110–126.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance
of information technology: toward a unified view. MIS Q. 27, 425–478
Wold, H. (1982). Soft modelling: The basic design and some extensions. In Systems under
indirect observations: Part II, ed. K.G. Jöreskog and H. Wold, pp. 1–54. Amsterdam:
North-Holland.
Zamani, S. (2022). Small and medium enterprises (SMEs) facing an evolving technological era: A systematic literature review on the adoption of technologies in SMEs. European Journal of Innovation Management. https://doi.org/10.1108/ejim-07-2021-0360