Modeling cause-and-effect relationships among predictive variables of human error based on the fuzzy multi-criteria decision-making method

Abstract

Abstract Human error is the result of different variables the study of which helps prevent committing such errors. This study aimed at modeling the cause-and-effect relationships among different variables that can predict human error based on the fuzzy multi-criteria decision-making method. The study was carried out based on the opinions of 17 safety experts in 2020. The variables of the study were determined by reviewing previous research and the expert panel’s brainstorming process. The results revealed that among 14 studied variables, shift work, job satisfaction, environmental discomfort and role conflict can be singled out as the root causes of human error. Although human error is affected by each studied variable, each variable can influence human error differently. Hence, safety and controlling measures presented to reduce and prevent human error need to take into account the different roles and influence weight of variables. The result of this study is applicable to researchers and managers in different work environments.