From Technostress to Techno-Recovery: Strategic HRM Job Resources to Reduce Digital Burnout in the JD-R Model
Main Article Content
Abstract
The rapid digitalization of work has intensified technostress and heightened the risk of digital burnout, particularly in knowledge-intensive and technology-driven organizations. Drawing on the Job Demands–Resources (JD-R) model, this article develops and tests a conceptual framework in which technostress operates as a key job demand, digital burnout as a central health-impairment outcome, and a bundle of strategic human resource management (HRM) job resources—framed as “techno-recovery” resources—buffers these effects. Techno-recovery resources are defined as integrated organizational, social, and technological practices that support psychological detachment, digital boundary control, and recovery from technology-driven strain. The rapid digitalization of work has intensified technostress and heightened the risk of digital burnout, particularly in knowledge-intensive and technology-driven organizations. Drawing on the Job Demands–Resources (JD-R) model, this article develops and tests a conceptual framework in which technostress operates as a key job demand, digital burnout as a central health-impairment outcome, and a bundle of strategic human resource management (HRM) job resources—framed as “techno-recovery” resources—buffers these effects. Techno-recovery resources are defined as integrated organizational, social, and technological practices that support psychological detachment, digital boundary control, and recovery from technology-driven strain. Using a quantitative survey design among employees in digitally intensive organizations, the study proposes the use of structural equation modeling to test the mediating role of digital burnout between technostress and outcomes (work engagement and turnover intention), and the moderating role of techno-recovery resources within the JD-R framework. While the empirical patterns are presented conceptually for illustrative purposes, the model is grounded in prior evidence on technostress, recovery experiences, and HRM in digital contexts. The article contributes by (1) positioning technostress and techno-recovery within an extended JD-R model, (2) specifying strategic HRM levers to reduce digital burnout, and (3) offering a measurement framework for future empirical work in emerging economies
Downloads
Article Details

This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Adias, L. T., Raimi, A. G., & Raimi, M. O. (2025). Breaking the Silence on Workplace Stress: Scalable HRM Solutions for Mental Health in Nigeria’s Evolving Workforce (Preprint). https://doi.org/10.2196/preprints.77758
Arikunto, S. (2017). Prosedur Penelitian: Suatu Pendekatan Praktik. Jakarta: Rineka Cipta, 2017.
Gaurangi Vasisht. (2025). Talent Management and Leadership Development in the era of Digital Transformation. International Journal of Advanced Research in Science, Communication and Technology, 585–589. https://doi.org/10.48175/IJARSCT-27990
Hermawati, A. (2025). Work Stress in the Creative Industry: The Relationship Between Technostress, Burnout and Employee Innovation. Psikologiya Journal, 2(3), 21–30. https://doi.org/10.62872/fqywwa57
Isah Leontes, N., & Mitonga-Monga, J. (2025). Investigating the influence of industry 4.0 technology on work engagement: Applying the JD-R theory to mitigate technostress. International Journal of Business Ecosystem & Strategy (2687-2293), 7(5), 282–293. https://doi.org/10.36096/ijbes.v7i5.948
Kwon, H. (2025). The Impact of Blurred Work-Family Boundaries on Parents’ Well-Being (pp. 243–266). https://doi.org/10.1007/978-3-031-89737-5_10
Mansuroğlu, E., & Smith, A. P. (2026). Technostress and employee well-being: A systematic review of empirical evidence. Computers in Human Behavior Reports, 21, 100941. https://doi.org/10.1016/j.chbr.2026.100941
Mat, N., Isa, R. M., Abdullah, N. A., & Alias, J. (2026). TECHNOSTRESS AND EMPLOYEE PERFORMANCE IN THE PUBLIC SECTOR UNDER INDUSTRIAL REVOLUTION 4.0. Architecture Image Studies, 7(1), 2311–2321. https://doi.org/10.62754/ais.v7i1.1214
Nilsen, W., Nordberg, T., Lescoeur, K., Ingelsrud, M. H., & Egeland, C. (2026). What do we know about limiting after-hours availability expectations and work-related connectivity? A systematic review of interventions and policies. Scandinavian Journal of Work, Environment & Health. https://doi.org/10.5271/sjweh.4277
Pansini, M., Buonomo, I., De Vincenzi, C., Ferrara, B., & Benevene, P. (2023). Positioning Technostress in the JD-R Model Perspective: A Systematic Literature Review. Healthcare, 11(3), 446. https://doi.org/10.3390/healthcare11030446
Rehabeam, R., & Kustiawan, U. (2025). The Role of the Job Demands & Job Resources Model (JD-R Model) on Turnover Intention with Employee Engagement and Job Satisfaction as Mediating Variables. Interdisciplinary Social Studies, 4(4). https://doi.org/10.55324/iss.v4i4.907
Robertson, K. A., & Byram, J. N. (2025). Applying Job Demands-Resources (JD-R) Theory to the Understanding of Residency Program Director Well-Being. Journal of Applied Social Science. https://doi.org/10.1177/19367244251369113
Safar, I., Yeni, H., Kumala Sari, N., Shalahuddin, S., & Asdar, M. (2026). Mutually exclusive or joint scheme? Effectiveness of mandatory and voluntary training in enhancing employee performance. Journal of Innovation in Business and Economics, 10(01). https://doi.org/10.22219/jibe.v10i01.40732
Sarimin, T., Mahamod, Z., Senawi, A., & Nagaretnam, S. A. (2025). The Role and Challenges of School Leaders in Enhancing the Application of Digital Technology. International Journal of Research and Innovation in Social Science, IX(VIII), 4379–4404. https://doi.org/10.47772/IJRISS.2025.908000351
Sarkar, M. S., Gupta, D. N., Daash, D. A., Naveen, D. L., & Samantaray, D. A. (2025). A STUDY ON THE IMPACT OF DIGITALIZATION ON EMPLOYEE WELL-BEING AND SUSTAINABLE HR PRACTICES: BENEFITS AND CHALLENGES IN THE DIGITAL ERA. Lex Localis - Journal of Local Self-Government, 23(S6), 6006–6034. https://doi.org/10.52152/ebs4fp53
Sugiyono. (2019). Metode Penelitian Kuantitatif, Kualitatif, dan R&D. Bandung Alfabeta.
Susanto, A., Wijaya, E., Nasib, N., Fadila, Z., & Amelia, R. (2025). Digital burnout, work alienation, and turnover intention: Unveiling the mediating role of toxic leadership among Generation Y lecturers in leading universities in Medan. International Journal of ADVANCED AND APPLIED SCIENCES, 12(11), 106–120. https://doi.org/10.21833/ijaas.2025.11.011
Westover, J. (2025). Harnessing Human Capital: How Strategic HR Drives Competitive Advantage. Human Capital Leadership Review, 17(2). https://doi.org/10.70175/hclreview.2020.17.2.9