Robots at the Table: Interaction Quality and Technology Acceptance Shape Customer Revisit in Restaurant

Restaurant service robots are increasingly deployed in food service establishments to perform table service, deliver food, and handle routine customer interactions, yet their ability to generate repeat patronage remains uncertain. This study examines how interaction quality and core technology acceptance factors, namely, perceived ease of use and perceived usefulness, directly influence customer intentions to revisit robot-assisted restaurants. Data were collected between October 2024 and January 2025 across 18 participating full-service and casual dining restaurants in Malaysia. A purposive online survey produced 251 usable responses from verified adult patrons who had experienced restaurant service robots during the preceding six months. Data were analysed using partial least squares structural equation modeling (PLS-SEM via SmartPLS 4). The structural results reveal that perceived usefulness (β = 0.248, p < 0.001) and perceived ease of use (β = 0.150, p < 0.05) directly drive customer revisit intention, explaining 11.5% of the total variance (R2 = 0.115). Conversely, interaction quality exerts no significant direct effect on revisit intention (β = 0.003, p > 0.05). These findings demonstrate that a pleasant robot encounter does not, by itself, secure customer return unless translated into tangible utility and effortlessness. Restaurant operators should prioritize seamless functional execution, clear interface usability, and visible operational benefits such as reduced waiting times.