Understanding visitors’ trust in human−robot interaction in museum scene: an elaboration likelihood perspective

Purpose This study aims to employ the Elaboration Likelihood Model (ELM) theory to identify the antecedents (service quality, perceived risk, and perceived expertise) that affect visitors' trust intentions, with trust beliefs serving as the mediating variable. Design/methodology/approach This study targeted visitors who had experience with museum service robots and adopted a face-to-face questionnaire survey (385) for data analysis. Structural equation modeling was implemented for hypothesis testing. Findings The study found that the service quality of the central route and the perceived expertise of the peripheral route had a significant and positive effect on trust beliefs, while the perceived risk of the peripheral route had a significant and negative effect on trust beliefs. Trust beliefs mediate the relationship between service quality, perceived risk, perceived expertise and trust intention. Originality/value This study revealed how visitors’ trust is formed in human−robot interaction. It expands the research on the antecedents and outcome variables of visitors’ trust beliefs and enriches the existing understanding of the visitors’ psychology and behavior when they interact with service robots. The results provide implications for the design of service robots and service scene management in museums.