This study investigates the complex, systemic interrelationships among psychosocial factors (PSFs) that concurrently influence work stress and job satisfaction in the construction industry. Recognising the limitations of linear and reductionist models, the research adopts a systems-thinking approach to identify high-leverage intervention points that may be used for improving employee well-being and organisational resilience.
Using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology, the study models directional and reciprocal relationships among 16 PSFs identified through an extensive literature review. Data required for modelling were collected via structured interviews with 47 experienced construction professionals in Sri Lanka. The DEMATEL analysis produced a systemic interdependency map, revealing the strength and direction of influence among the PSFs, work stress and job satisfaction.
Heavy workload, poor organisational culture and limited decision latitude were identified by professionals as the most influential PSFs, exerting system-wide effects on both work stress and job satisfaction. A bidirectional relationship between work stress and job satisfaction was also observed, with job satisfaction acting as a potential buffer against work stress. Career stagnation emerged as the most heavily influenced PSF, shaped by multiple upstream stressors. These findings suggest that workplace stressors may operate in cyclical and compounding patterns, highlighting the need for integrated, system-level interventions.
The findings offer actionable insights for intervention design. However, they are based on the perceptions of construction professionals within a specific national and industry context. Therefore, caution is advised when applying them to other settings.
This study contributes to the literature by applying a systems-thinking framework to occupational stress and job satisfaction in construction. It presents a novel, empirically informed model that illustrates the dynamic interdependencies among psychosocial factors. These insights may support the design of targeted, high-impact interventions aimed at addressing underlying conditions rather than surface-level symptoms.
