From Technostress to Techno-Recovery: Strategic HRM Job Resources to Reduce Digital Burnout in the JD-R Model - Manippi, Wahyu Anugrah; M. Nursaid; Muhajir; Meri Hariratuljannah (PT Inovasi Pratama Internasional, 2026)
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