A risk-based view of trust in human–machine collaboration on cooking robots

Human–machine collaboration is becoming increasingly prevalent across a wide range of industries. However, the risks associated with the adoption of emerging technologies have triggered a crisis of trust, leading to widespread concerns about the deployment of collaborative machines in the service industry. Therefore, this study aimed to investigate the role of trust in human–machine collaboration from a risk-based view, with the following research objectives: (1) to identify the antecedents of trust and test hypothesized associations among trust, perceived risk, adoption intention, and use behavior; and (2) to construct a risk-based model capturing the associations of trust with behavior in human–machine collaboration. Survey data were collected from 201 respondents in China and analyzed using partial least squares structural equation modeling (PLS-SEM). The results show that empathy, competence, reciprocity, and assurance were associated with trust in collaborative machines, while perceived risk mediates the hypothesized paths between trust and adoption intention. These findings provide insights into designing for trust in human–machine collaboration on cooking robots.