Service Robots in the Restaurants: A Systematic Literature Review Using TCCM Framework

Abstract

This study aims to analyze academic literature on service robots in restaurants using the TCCM framework and bibliometric analysis based on the SPAR-4-SLR protocol. A systematic literature review utilized the WOS and SCOPUS databases. The performance analysis of the articles obtained after applying the exclusion and inclusion criteria was carried out using Bibliometrix R studio. According to the results, anthropomorphism theory, uncanny valley theory, TAM, role congruence theory, and UTAUT are the most frequently used theories in the reviewed studies. China, the USA, and Korea have the highest number of articles. However, the authors are primarily from a single country. According to the conceptual framework, the frequently used variables are classified as consumer characteristics, robot-related, and consumer perception-related. PROCESS Macro, Structural Equation Modeling, PLS/SEM, ANOVA, and ANCOVA are the most widely used analysis methods. The data in the reviewed studies were predominantly collected via a questionnaire with scenario analysis. This study offers insights to guide future research, identify promising areas for further investigation, and advance the emerging research field. Finally, this study will provide scholars, service providers, managers, and entrepreneurs with valuable theoretical and practical insights and guidelines.