Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Saxena, Anshul; Rishi, Bikramjit Title A name given to the resource AI and human collaboration in tourism: a framework for scalable, authentic, and engaging content Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Asia Pacific Journal of Tourism Research;Volume;30;Issue;9;pp.1226-1244 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1080/10941665.2025.2486033" target="_blank" rel="noreferrer noopener">https://doi.org/10.1080/10941665.2025.2486033</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105003456335?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105003456335?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Saxena A., Christ University, Maharashtra, Pune, India; Rishi B., School of Management &amp; Entrepreneurship, Shiv Nadar Institution of Eminence Deemed to be University, Greater Noida, India Description An account of the resource This study examines the effectiveness of AI-generated content in tourism marketing by comparing it to human-generated narratives. While AI enhances scalability and factual accuracy, its ability to replicate emotional engagement and cultural authenticity remains unexplored. Using the Information Quality Framework (IQF), the study employs readability analysis, sentiment analysis, and thematic analysis to assess AI- and human-generated content. AI-generated travel narratives were sourced from large language models, while human content came from tourism blogs and vlogs. Findings reveal that AI-generated content is well-structured and highly readable but lacks emotional depth and trust-building elements. Sentiment analysis shows stronger emotional responses in human narratives, while thematic analysis highlights richer cultural insights. The study proposes a Hybrid AI-Human Collaboration Model, leveraging AI's efficiency with human creativity. These insights contribute to AI ethics, tourism storytelling, and digital marketing, offering practical recommendations for integrating AI into tourism content creation. 2025 Asia Pacific Tourism Association. Subject The topic of the resource content automation; digital storytelling; Generative AI; personalization; tourism marketing; tourism narratives Publisher An entity responsible for making the resource available Routledge Relation A related resource ISSN: 10941665; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online