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Experience and artificial intelligence in hospitality and tourism: a review of reviews and a bibliometric analysis

[PDF] Experience and artificial intelligence in hospitality and tourism a review of reviews.pdf (2.295Mo)
Identificadores
URI: https://hdl.handle.net/10481/105429
DOI: https://doi.org/10.1108/IJCHM-07-2024-0988
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Estadísticas
Statistiques d'usage de visualisation
Metadatos
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Auteur
Polo Peña, Ana Isabel; Frías Jamilena, Dolores María; Peco Torres, Francisco; Rodríguez Molina, Miguel Ángel
Editorial
Emerald Insight
Materia
Artificial intelligence
 
AI
 
Experience
 
Experience economy
 
Literature review
 
Bibliometric analysis
 
Date
2025-04-15
Referencia bibliográfica
Polo-Peña, A. I., Frías-Jamilena, D. M., Peco-Torres, F., & Rodríguez-Molina, M. Á. (2025). Experience and artificial intelligence in hospitality and tourism: a review of reviews and a bibliometric analysis. International Journal of Contemporary Hospitality Management, 37(7), 2306-2326.
Patrocinador
Grant TED2021-132078B-I00 funded by MICIU/AEI/10.13039/501100011033 and by the European UnionNextGenerationEU/PRTR, and Project A-SEJ-462-UGR20 funded by the Consejería de Universidad, Investigación e Innovación de la Junta de Andalucía y por FEDER, Una manera de Hacer Europa.
Résumé
Purpose: This study seeks to determine the current state of the literature—and propose future research directions—on the topic of tourist experiences shaped by artificial intelligence (AI). A review of reviews dealing with the tourist experience is conducted, highlighting the growing use of AI (and its most advanced forms, captured under the umbrella term strong AI). A bibliometric analysis of tourist experiences powered by strong AI is conducted on this review. Design/methodology/approach: This study implements a mixed methodology that combines a review of reviews with bibliometric analysis of the scientific literature on strong-AI-enhanced tourist experiences. Findings: The analysis provides insights into the evolution of the tourist experience based on the “experience economy” theory, through a performance-based analysis and scientific mapping of studies dealing with strong-AI-enhanced tourist experiences. Relevant future lines of research are proposed that explore new conceptual frameworks and their evolution toward considering more varied AI-based tools, services, and environments, and tourism “agents,” and contributing to the scholarship on sustainability, authenticity, and possible detrimental effects of AI. Originality: This highly original work addresses the current lack of studies that adopt a combined perspective—blending a review of reviews and bibliometric analysis—to examine the evolution of the tourist experience and, particularly, how AI is influencing that experience. Research implications: This study theoretically connects the “experience economy” model with tourism and strong AI. Lines of research are proposed to expand theoretical boundaries toward a more comprehensive understanding of tourist experiences mediated by strong AI and their contribution to well-being, authenticity, and sustainability.
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