Evolution and future agenda of service robot research: a computer-assisted qualitative data analysis approach

Purpose Given the rapid proliferation of service robots in the hospitality and tourism industry and the increasing complexity of stakeholder interactions, this study aims to systematically analyze stakeholder perspectives and interactions in service robot implementation in hospitality and tourism studies. Design/methodology/approach The review analyses 175 articles published between 2019 and 2023 in Hospitality and Tourism Management (HTM) and Business Management (BM) journals, combining industry-specific insights and broader business contexts to examine service robot implementation and theoretical development. The study employs Computer-Assisted Qualitative Data Analysis (CAQDA) to systematically analyze research trends and theoretical developments. Findings Our analysis highlights three main points. First, service robot research has evolved from technological implementation to more meaningful human-robot interaction dynamics, emphasizing psychological aspects, social responses, and relationship building in service environments. Second, limited research on stakeholders' viewpoints on organizational impacts suggests a need for more comprehensive stakeholder analysis in service robot studies. Third, HTM and BM journals exhibit different research trends and focus areas, HTM focuses primarily on operational applications, customer experience, and service efficiency. In contrast, BM journals emphasize theoretical development, strategic implications, and organizational transformation. Originality/value This review maps the knowledge structures across HTM and BM journals within hospitality and tourism contexts. This study makes dual contributions. Theoretically, it reveals the current research landscape and guides future research directions. Practically, it provides valuable insights for industry practitioners, including managers implementing service robots, engineers designing robot functionalities, and designers developing human-robot interfaces by offering stakeholder perspectives and evidence-based implementation strategies.