 How practitioners can leverage GenAI to bridge the research-practice gapW. Lasarov (),
M. Trabandt (),
S. Hoffmann and
G. Viglia ()
Post-Print from HAL Abstract: Despite the practical relevance of many tourism research studies, organizations and policymakers often struggle to integrate them due to time constraints, language barriers, limited resources, and interaction challenges. Generative artificial intelligence (GenAI) offers new capabilities to overcome these barriers. We propose a GenAI-enabled knowledge translation process with three stages: (i) research curation to identify and translate relevant literature; (ii) content creation to produce materials; and (iii) market research using synthetic guests to pre-test their effectiveness. We examine the capabilities, limitations, and ethical implications of GenAI at each stage, drawing on a systematic review of GenAI and tourism literature. To equip managers with the knowledge and tools needed to harness research-based insights effectively, we offer a toolkit comprising a handbook, a promptbook, and tailored GPT models. The toolkit enables tourism and hospitality practitioners to apply research findings in their decision-making and content strategies without direct stakeholder interaction. Keywords: Research-practice gap; GenAI; Knowledge translation process; Toolkit; Literature review (search for similar items in EconPapers) Published in Tourism Management, 2026, ⟨10.1016/j.tourman.2025.105309⟩ There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05286024 DOI: 10.1016/j.tourman.2025.105309 Access Statistics for this paper More papers in Post-Print from HAL |
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