Comparative Impact of Remote Work on Employee Wellbeing Across Industries

Thesis Abstract

The rapid shift to remote work across industries has raised concerns about differential impacts on employee wellbeing, with implications for productivity, retention, and organizational resilience in a post-pandemic economy. This study investigates how remote work arrangements influence wellbeing dimensions—psychological, physical, social, and job-related well-being—and whether these effects vary by industry, job characteristics, and individual differences. The aim is to identify patterns of wellbeing outcomes associated with remote work and to explain cross-industry variations through theoretical lenses of Job Demands-Resources (JD-R) and Self-Determination Theory (SDT). Specific objectives are (1) to compare levels of psychological, physical, social, and job-related well-being among employees in technology, finance, education, and manufacturing sectors engaged in remote work; (2) to examine the moderating roles of managerial support, home-work boundary management, and perceived autonomy on wellbeing; (3) to assess whether work arrangement characteristics (full-time remote, hybrid, or occasional remote) predict wellbeing outcomes after controlling for sociodemographic factors; and (4) to provide evidence-based recommendations for industry-specific HR practices. The study adopts a cross-sectional, comparative research design utilizing a mixed-methods approach. A stratified random sample of 1,200 employed adults across four industries (technology, finance, education, manufacturing) who have engaged in remote work for at least six months will be surveyed, ensuring representation by gender, age, tenure, and managerial level. Data collection will use a structured online questionnaire comprising validated scales the Utrecht Work Engagement Scale (UWES) for vigor and absorption, the WHO-5 Well-Being Index for general wellbeing, the Depression Anxiety Stress Scales (DASS-21) for psychological distress, the Short Form-36 (SF-36) for physical and social functioning, and a bespoke remote-work characteristics scale (autonomy, boundary management, communication quality) developed for this study. Additionally, a subset of 40 participants per industry (total n = 160) will participate in semi-structured interviews to enrich interpretation through thematic analysis. Data will be analyzed using multivariate techniques descriptive statistics and reliability analyses; multivariate analysis of covariance (MANCOVA) to compare wellbeing domains across industries while controlling for age, gender, tenure, and remote-work modality; hierarchical multiple regression to test moderating effects of supervisor support, boundary management, and autonomy; and interaction terms to explore cross-industry differences. Structural equation modeling (SEM) will test the JD-R and SDT-based theoretical model linking job demands, resources, motivational processes, and wellbeing outcomes. The qualitative data will be analyzed using thematic analysis to identify patterns related to cultural and organizational practices influencing wellbeing in each industry. Expected findings anticipate that wellbeing outcomes will differ by industry, with technology showing higher perceived autonomy and social connectedness but greater cognitive fatigue due to rapid changes, finance exhibiting moderate wellbeing with pronounced job-related stress, education showing higher social well-being tied to collaboration but challenges in boundary management, and manufacturing presenting lower physical and social wellbeing due to on-site requirements and ergonomics. The JD-R framework is expected to reveal that job resources (autonomy, supervisory support, and adequate home-office setup) buffer the negative impact of job demands (time pressure, screen fatigue, and isolation), while SDT will highlight the importance of autonomy, competence, and relatedness in sustaining wellbeing across contexts. The study aims to advance knowledge by providing cross-industry evidence on remote-work wellbeing, clarifying how industry-specific job designs and managerial practices shape employee experiences. It will contribute to HR theory by integrating JD-R and SDT in a cross-industry remote-work context and offer practical guidance for HR practitioners designing flexible work policies, investing in home-office resources, fostering inclusive virtual collaboration, and tailoring wellbeing interventions to industry-specific risk profiles. The main conclusion is that remote-work wellbeing is contingent on a combination of job resources and individual needs, with industry context moderating these relationships. Recommendations include structured onboarding for remote work, ongoing managerial training to support remote teams, targeted wellbeing programs addressing psychological and social domains, ergonomic assessments, and policy mechanisms enabling autonomous yet connected work arrangements across sectors.