Bibliometric analysis of the role of artificial intelligence in tourism destination management - Bacuy-Ortiz, Karem Xiomara; Soriano-Torres, Liliana Elizabeth (Journal of Asian Scientific Research, 2025)
This study performs an in-depth bibliometric analysis to explore the role of artificial intelligence (AI) in managing tourism destinations. Its objectives are to uncover current trends, key contributors, collaboration networks, and emerging research themes. A total of 87 publications from Scopus and Web of Science were examined, selected through a precise search strategy and strict inclusion criteria. The methodology consisted of five stages: database selection, query formulation, screening, data extraction, and visualization using RStudio and VOSviewer. Findings indicate a significant rise in research output since 2018, with prominent contributions in machine learning, sentiment analysis, and recommender systems. China, Spain, and the United Kingdom are leading contributors, supported by robust international collaborations. AI enhances operational efficiency, personalization, and decision-making in tourism destinations, though challenges such as data privacy, infrastructure, and ethical concerns remain. This study advances academic understanding by offering a dual-database visualization of AI applications in tourism. Its insights are valuable for researchers, policymakers, and practitioners seeking to promote sustainable, data-driven tourism management.