Exploring Human–Robot Interaction in Hospitality: How Perceived Functionality, Sociality, and Risk Shape Customers’ Usage Intention

Hotel service robots are increasingly becoming a key means to enhance service efficiency. However, customer acceptance of service robots varies significantly. Based on S-O-R theory and incorporating TAM, this study constructs a comprehensive model. It primarily investigates how customers' perceptions of the functional attributes, social attributes, and perceived risk of hotel service robots influence their usage intention through the mediating role of trust. Empirical analysis of 464 valid samples from Chinese hotels reveals that perceived intelligence, usefulness, warmth, and social presence all significantly and positively influence customers’ trust, while perceived risk significantly weakens trust. Trust significantly and positively impacts usage intention and partially mediates multiple pathways. Among these, perceived intelligence and perceived warmth are the most critical factors influencing customers’ trust. By integrating functional and social perspectives, this study deepens the understanding of customer psychological mechanisms in human-machine interactions. The findings provide management insights for hotel managers and robot designers: enhancing robots' intelligence and social characteristics while reducing perceived risk can strengthen customer trust and promote the adoption of service robots.