What are the occupational hazards of construction project managers: A data mining analysis in China
Document Type
Article
Publication Date
2-1-2021
Abstract
In contrast to physical and biological hazards for on-site construction laborers, chronic stress and its antecedents are the most significant occupational hazards for construction professionals, especially for construction project managers (CPMs). This study examined burnout to measure the chronic stress of CPMs and aimed to systematically identify the core factors that cause burnout from individual, job-related, organizational and social aspects. With reference to the classic and domestic measurement scales, a cross-sectional survey was conducted, and 634 questionnaires were received from Chinese CPMs. Breaking away from the traditional research paradigm of the “hypothesis-test”, this research applied a data mining method, association rule analysis, to identify the core factors and mechanisms of CPM burnout. In addition to the traditional mechanisms, complex interactive networks among the impact factors and job burnout and the reversed effects of burnout were also obtained. The results show that organizational and social factors have significant impacts on all dimensions of job burnout and that high job demands can improve professional efficacy. In addition, after the formation of job burnout, there are reversed influences on individuals’ behavior and perceptions of jobs, organizations, and society. This study demonstrates that association rule analysis is an underused tool that can offer innovative psychological and organizational behavioral insights into CPM occupational hazards. Interventions such as creating a better organizational culture and offering professional training should be implemented to relieve burnout among CPMs in China.
Publication Source (Journal or Book title)
Safety Science
Recommended Citation
Li, X., Fei, Y., Rizzuto, T., & Yang, F. (2021). What are the occupational hazards of construction project managers: A data mining analysis in China. Safety Science, 134 https://doi.org/10.1016/j.ssci.2020.105088