Abstract

Purpose: Several variables can affect work stress. This study aims to model the cause-and-effect relationships among different variables that can predict work stress based on one of the most important fuzzy multicriteria decision-making methods used to investigate the cause-and-effect relationships among variables. Design/methodology/approach: This study was conducted in 2020, including 17 experts in safety management, occupational health and work psychology, based on the fuzzy decision-making trial and evaluation laboratory method as a robust approach to identify the cause-and-effect relationships among different variables. Findings: Shift work, lack of job satisfaction, mental health, mental overload, fatigue, job security, sleep disorders, environmental discomfort, work pressure, job knowledge (this could mean expertise/level of qualifications/familiarity with the job), work complexity and role conflict were found to be the most significant variables affecting work stress. Moreover, the cause-and-effect model of relationships among variables showed that shift work and lack of job satisfaction are root causes, and mental health, fatigue, mental workload, sleep disorder and environmental discomfort are direct causes. Originality/value: Although the results of this study demonstrate that work stress can be influenced by 12 different variables, the modeling results show that some variables, such as shift work and lack of job satisfaction, can directly or indirectly impact other variables and thus result in work stress. © 2022, Emerald Publishing Limited.