Unveiling trends in digital tourism research: A bibliometric analysis of co-citation and co-word analysis

Digital tourism has witnessed substantial evolution, shaping the trajectory of tourism research. Employing bibliometric analysis on 1,079 articles from the Web of Science database, this study identifies predominant themes and research trends in digital tourism. Key findings revealed three main co-citation clusters: ‘Smart tourism destinations and smart tourists', ‘Evolution and impact of E-tourism on travel behavior’, and ‘Personalized smart tourism experience’. Additionally, co-word analysis showcased prominent themes such as ‘AR-Integrated E-Tourism’, ‘Co-creation of smart tourism destinations in China post-COVID-19′, and ‘AI-driven personalized destination recommender systems in tourism’. The study highlights gaps in digital tourism research, advocating for socio-cultural preservation alongside tech advancements. Co-citation analysis suggests new travel theory directions, while AR's role in sustainable tourism is spotlighted. Practically, AI and Big Data emerge as pivotal in personalized experiences, with co-word analysis aiding industry foresight and emphasizing AI-driven, sustainable strategies. Limitations include reliance on a single database, suggesting future studies to integrate multiple sources and qualitative insights. The study's findings offer a roadmap for academics and practitioners, emphasizing potential avenues in digital tourism, especially in the context of sustainable and responsible practices.