This study examines the three stressors of technostress, telepressure, and role stress and their relationship with innovative work behaviour (IWB) among academic staff members who teach students in virtual learning environments (VLEs), and whether digital literacy serves as a moderating factor between these stressors and the dependent variable. The Job Demands–Resources model is used and each stressor is conceptualized as a higher order construct composed of dimensions. This study used a positivist philosophy with a deductive and quantitative approach and data were gathered using a self-administered questionnaire from 384 academic staff of nine academic private universities in Klang Valley, Malaysia, analysed using the partial least squares structural equation modelling (PLS-SEM) in SmartPLS 4 with 10,000 subsamples of the bootstrap. The measurement model had good reliability, convergent and discriminant validity and the weight for all higher-order formative measures and no collinearity. Structural model accounted for the variance of IWB 49.4 % (Q²predict = 0.47). The findings supported the hypotheses that indicated that technostress (? = -0.42), role stress (? = - 0.39) and telepressure (? = -0.34) had significant negative effects on IWB. The extent of digital literacy did not significantly moderate any of the three relationships, and had no direct significant effect, so the fourth hypothesis was not accepted. The results suggest that technology strain hinders educator innovation irrespective of digital-literacy levels and that institutions need to mitigate the strain, not just on the basis of the difference among educators in digital-literacy. The study adds to the technostress and IWB literature the higher order evidence of moderation in a context of higher education in Southeast Asia.
Awang Kader, M. A. R., Abd Aziz, N. N., Mohd Zaki, S., Ishak, M., & Hazudin, S. F. (2022). The effect of technostress on online learning behaviour among undergraduates. Malaysian Journal of Learning and Instruction, 19(1), 183–211.
Bakker, A. B., & Demerouti, E. (2007). The job demands-resources model: State of the art. *Journal of Managerial Psychology, 22*(3), 309–328. https://doi.org/10.1108/02683940710733115
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.
Barber, L. K., & Santuzzi, A. M. (2015). Please respond ASAP: Workplace telepressure and employee recovery. *Journal of Occupational Health Psychology, 20*(2), 172–189. https://doi.org/10.1037/a0038278
Becker, J.-M., Klein, K., & Wetzels, M. (2012). Hierarchical latent variable models in PLS-SEM: Guidelines for using reflective-formative type models. Long Range Planning, 45(5–6), 359–394.
Bourlakis, M., Nisar, T. M., & Prabhakar, G. (2023). How technostress may affect employee performance in educational work environments. *Technological Forecasting and Social Change, 193*, 122674. https://doi.org/10.1016/j.techfore.2023.122674
Brod, C. (1984). Technostress: The human cost of the computer revolution. Addison-Wesley.
Callista, F., & Hastuti, R. (2024). Relationship of role stress, technostress, and performance at high school teacher in West Jakarta. *Journal of Communication in Scientific Inquiry (JCSI), 5*(2), 107–117. https://doi.org/10.58915/jcsi.v5i2.1097
Chou, H. L., & Chou, C. (2021). A multigroup analysis of factors underlying educators’ technostress and their continuance intention toward online teaching. Computers & Education, 175, 104335.
Cotos-Gamarra, A., Ruelas-Salazar, M., Fernández-Hurtado, G., & Cordova-Buiza, F. (2023). The influence of job stress on employee performance in higher education institutions: A review and research agenda. *IBIMA Business Review, 2023*, Article 141493. https://doi.org/10.5171/2023.141493
Czaja, S. J., Charness, N., Fisk, A. D., Hertzog, C., Nair, S. N., Rogers, W. A., & Sharit, J. (2006). Factors predicting the use of technology: Findings from the CREATE project. Psychology and Aging, 21(2), 333–352.
Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli, W. B. (2001). The job demands-resources model of burnout. *Journal of Applied Psychology, 86*(3), 499–512.
French, J. R. P., Rodgers, W., & Cobb, S. (1974). Adjustment as person–environment fit. In G. V. Coelho, D. A. Hamburg, & J. E. Adams (Eds.), Coping and adaptation (pp. 316–333). Basic Books.
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Springer Nature.
Hassan, R. S., Amin, H. M. G., & Ghoneim, H. (2024). Decent work and innovative work behavior of academic staff in higher education institutions: The mediating role of work engagement and job self-efficacy. *Humanities and Social Sciences Communications, 11*(1), Article 744. https://doi.org/10.1057/s41599-024-03177-0
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135.
Janssen, O. (2000). Job demands, perceptions of effort–reward fairness and innovative work behaviour. Journal of Occupational and Organizational Psychology, 73(3), 287–302.
Kahn, R. L., Wolfe, D. M., Quinn, R. P., Snoek, J. D., & Rosenthal, R. A. (1964). Organizational stress: Studies in role conflict and ambiguity. John Wiley.
Khan, A. A., Shahzad, S., & Gul, H. (2022). Effect of techno-stress on the work behaviour of university educators. Global Educational Studies Review, 7(2), 427–439.
Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1–10.
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610.
Memon, M. A., Ting, H., Cheah, J. H., Thurasamy, R., Chuah, F., & Cham, T. H. (2020). Sample size for survey research: Review and recommendations. Journal of Applied Structural Equation Modeling, 4(2), 1–20.
Pfaffinger, K. F., Reif, J. A., & Spieß, E. (2022). When and why telepressure and technostress creators impair employee well-being. International Journal of Occupational Safety and Ergonomics, 28(2), 958–973.
Ragu-Nathan, T. S., Tarafdar, M., Ragu-Nathan, B. S., & Tu, Q. (2008). The consequences of technostress for end users in organizations. Information Systems Research, 19(4), 417–433.
Rizzo, J. R., House, R. J., & Lirtzman, S. I. (1970). Role conflict and ambiguity in complex organizations. Administrative Science Quarterly, 15(2), 150–163.
Sarstedt, M., Hair, J. F., Cheah, J.-H., Becker, J.-M., & Ringle, C. M. (2019). How to specify, estimate, and validate higher-order constructs in PLS-SEM. Australasian Marketing Journal, 27(3), 197–211.
Semaan, R., Gamaiunova, L., Pereira Teixeira, P., Nater, U. M., Heinzer, R., Haba-Rubio, J., Vlerick, P., Cambier, R., & Gomez, P. (2025). Psychometric properties of telepressure measures in the workplace and private life among French-speaking employees. *BMC Psychology, 13*(1). https://doi.org/10.1186/s40359-025-02616-0
Tarafdar, M., Tu, Q., Ragu-Nathan, B. S., & Ragu-Nathan, T. S. (2007). The impact of technostress on role stress and productivity. *Journal of Management Information Systems, 24*(1), 301–328. https://doi.org/10.2753/MIS0742-1222240109
West, M. A., & Farr, J. L. (1989). Innovation at work: Psychological perspectives. Social Behaviour, 4(1), 15–30.
Yang, D., Liu, J., Wang, H., Chen, P., Wang, C., & Metwally, A. H. S. (2025). Technostress among teachers: A systematic literature review and future research agenda. *Computers in Human Behavior, 168*, 108619. https://doi.org/10.1016/j.chb.2025.108619
Din, N. N. O., Vasudevan, H., & Singh, J. S. K. (2026). Innovative Work Behaviour in Virtual Learning Environments: Examining the Effects of Technostress, Telepressure and Role Stress with Digital Literacy as a Moderator. International Journal of Academic Research in Business and Social Sciences, 16(9), 1431–1447.
Copyright: © 2026 The Author(s)
Published by Knowledge Words Publications (www.kwpublications.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode
