Deep affection: service robots increase brand love of restaurants

Purpose Service robots with advanced artificial intelligence (AI) can collect data on customer preferences, understand complex requests, improve services, and tailor marketing strategies. This study examined how perceived relatedness, perceived warmth, and customer–AI-assisted exchanges (CAIX) of service robots affect customer service competencies and brand love through service-robot intimacy. Design/methodology/approach A brand love model was developed based on the AI device using acceptance and an emotional perspective. Data were collected from customers who had dined in robot restaurants; 415 questionnaires were completed, and partial least squares analysis was adapted to the proposed model. Findings The results demonstrate that the perceived relatedness, perceived warmth and CAIX of service robots affect the intimacy of robot restaurants. Customers who feel friendly and satisfied with a restaurant’s service robot will recommend it to their friends. Research limitations/implications This study draws on theory and existing literature to identify principal factors in robot restaurant service capabilities. Future research can include service robot data analysis capabilities and adoption process factors as the direction of customer relationship management research while also exploring the influence of AI computing on restaurant supply chains. Likewise, the agility of service robots in the stages of innovation can be discussed in future research based on different theories, which will bridge unique insights. Practical implications The findings of this study emphasize the relationship between service robots and restaurant brand love and propose specific practice areas for restaurants. Originality/value This study expands the main issue of current brand love research from traditional restaurant operations to the novel field of humanoid service robot restaurants. It enriches our understanding of how consumers’ emotional fondness for a brand affects their behavioural intentions.