Natural-Resource-Based Approaches to Employee Well-Being under Flexible Work Arrangements: Evidence from IT Companies

Abstract

Flexible work arrangements have transformed the nature of work in IT organizations, creating opportunities for greater autonomy while simultaneously increasing digital overload, blurred work–life boundaries, and difficulties in psychological recovery. This study examines how natural-resource-based approaches can support employee well-being under flexible work arrangements, with particular emphasis on natural-resource exposure and employee recovery. A hybrid mixed-method approach is proposed, integrating a three-wave longitudinal quantitative design, qualitative interviews, and machine-learning techniques. Illustratively, data from 450 IT professionals are analysed using descriptive statistics, correlation analysis, time-lagged regression, mediation and moderation analysis, while qualitative interviews provide contextual insights into employees’ experiences of flexible work and nature-based recovery. Clustering and classification algorithms are additionally employed to identify heterogeneous employee well-being profiles and generate data-driven recommendations. The illustrative findings indicate that flexible work arrangements are positively associated with employee well-being, while natural-resource exposure demonstrates significant positive relationships with employee recovery and well-being. Recovery partially mediates the relationship between natural-resource exposure and well-being, while natural-resource exposure strengthens the positive association between flexible work and well-being. Machine-learning analysis further identifies distinct employee profiles, highlighting differences in environmental resources, recovery, stress, and well-being. The study extends the Job Demands–Resources perspective by conceptualising natural-resource exposure as an environmental resource that can complement flexible work and facilitate employee recovery. The findings offer implications for developing healthier, sustainable, and differentiated flexible-work policies in IT organizations.