Conversational AI in Tourism: A systematic literature review using TCM and ADO framework

This systematic literature review explores how conversational AI chatbots revolutionise tourism by altering how travellers gather information, make decisions, and interact with services. Using the theory, context, and method (TCM) and antecedents, decisions, and outcomes (ADO) frameworks, this review analyses 77 articles from EBSCOhost, ProQuest, Scopus and Web of Science. The study complies with primary bibliometric data, categorises 49 commonly employed theories and maps their relevance to chatbot adoption and user engagement. It organises these theories, examines ADO framework relationships, and identifies key antecedents influencing user trust, emotional engagement, and satisfaction, such as user characteristics, technological attributes, and service quality. Further, this study applied the Mixed Methods Appraisal Tool (MMAT) to systematically evaluate the risk of bias among the included articles. The analysis highlighted the significant role of cultural contexts and emotional factors, such as trustworthiness and chatbot intelligence, in shaping user perceptions. The review addresses research gaps regarding cross-cultural nuances, ethical issues, and the need for personalisation by contributing a relationship map within the ADO framework and suggesting future research directions based on TCM and ADO. These insights offer valuable guidance for researchers and practitioners aiming to leverage chatbots to improve customer experience and operational benefits in tourism.