Digitalization and employee well-being: A fuzzy-tism approach of remote work stressors

Abstract The recent advancements in digital technologies have made remote work a core aspect of modern organizations, bringing opportunities and challenges for employee well-being. Drawing on the Job Demands-Resources model, the study investigates key stressors undermining employees’ well-being within digitalized settings. Fuzzy total interpretive structural modeling (F-TISM) and MICMAC analysis are employed to understand the hierarchical interrelationship and classify the stressors according to their driving and dependence power. The findings reveal low supervisor support, unrealistic supervisor expectations, digital overload, digital fatigue, and constant connectivity as critical drivers undermining remote workers’ well-being in these work practices. The proposed health impairment process of the JD-R model provides theoretical insights into how high job demands in digitalized settings undermine the well-being of remote workers, amid the growing emphasis on digital transition and flexible work models. The developed decision model provides actionable insights for practitioners and policymakers.