Technostress and Productivity: A Systematic Literature Review Using TCCM (Theory, Context, Characteristics, and Methodology) Framework

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This study systematically examines the relationship between technostress and productivity, addressing the fragmentation present in the existing literature.By applying the TCCM (Theory, Context, Characteristics, and Methodology) framework, the review synthesises diverse empirical perspectives and identifies research gaps to guide both theoretical advancement and practical intervention.Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, a systematic literature review was conducted using the Scopus database, covering publications from 2015 to 2025.Seventy relevant documents were analysed through the TCCM framework to examine theoretical foundations, contextual settings, technostress characteristics, and methodological approaches.The review demonstrates that technostress negatively affects productivity, primarily through stressor pathways such as techno-overload, techno-invasion, and techno-complexity.Nevertheless, emerging evidence suggests that technology demands can also produce positive outcomes, notably enhanced innovation, through the construct of techno-eustress.The principal theoretical frameworks employed across the reviewed studies are the Job Demands-Resources model, the Transactional Theory of Stress and Coping, and the Technostress Model.Research is geographically concentrated in Asia and Europe, with banking, healthcare, and higher education as the most studied sectors.Methodological diversity is evident across the corpus, though longitudinal and cross-cultural studies remain limited.Theoretically, this review advances understanding of technology-induced stressors through an integrated TCCM synthesis.From a practical standpoint, it provides evidence-based guidance for designing technology implementations and support systems that maximise productivity benefits while reducing the adverse consequences of technostress, a concern of particular relevance given the accelerating reliance on digital technologies and emerging paradigms such as artificial intelligence and algorithmic management.