Research on the Mechanisms Influencing Workers’ Risk-Taking Behaviors at Smart Construction Sites Based on the NCA-fsQCA Hybrid Method

The construction industry is inherently high-risk, with workers’ unsafe behaviors directly causing most safety incidents. As smart technologies are widely deployed on construction sites, new forms of risk-taking behavior have emerged, but their underlying mechanisms remain poorly understood. Grounded in Human–Technology–Organization (HTO) theory, this study establishes a multi-factor coupling analytical framework and employs a mixed NCA–fsQCA method to empirically analyze data from 312 workers across two smart construction sites in Beijing. The results show that no single antecedent variable acts as a necessary condition for either type of high-risk-taking behavior, though each variable exerts distinct bottleneck constraints. Five configurations driving high-risk behaviors are identified: smart technology adaptability serves as the core condition for automation trust bias behaviors, while individual risk-taking propensity and task situational pressure are universal core factors for both behavior types. These findings uncover the multi-dimensional coupling logic of risk-taking behaviors and offer theoretical and practical insights for targeted safety management in smart construction contexts.