Mediating effect of knowledge transfer between human-robot interaction and project team creativity in uncertain environments: evidence from China

Purpose In complex and highly uncertain environments, the integration of artificial intelligence is significantly transforming decision-making processes, resource allocation, human-robot team behaviors and governance mechanisms in construction and operational projects. Human-robot interaction has gradually become an important operational mode within complex project organizations. However, existing research has predominantly focused on technological empowerment and organizational contexts, while insufficient attention has been paid to the role of interactive behaviors in construction project governance. Design/methodology/approach Grounded in the knowledge-based view, resource dependence theory and trust theory, this study develops a moderated mediation model that examines how human-robot interaction reshapes traditional work scenarios and organizational patterns. Drawing on regression analysis of data collected from 232 smart construction project teams, this study investigates the effect of human-robot interaction on team creativity under conditions of uncertainty, examines the mediating role of knowledge transfer and tests the moderating role of human-robot trust. Findings The results show that human-robot interaction significantly enhances smart construction project team creativity. Knowledge transfer partially mediates this relationship. Furthermore, human-robot trust not only positively moderates the relationship between human-robot interaction and project team creativity, but also strengthens the mediating effect of knowledge transfer between human-robot interaction and team creativity. Originality/value These findings advance the understanding of behavioral cognition and organizational adaptation in human-robot teamwork within smart construction projects. They also provide insights into human-robot interactive decision-making and innovation management in uncertain environments.