📄 Sciences Methods and Technologies
International Journal (SciMeTech)

Volume 2 · Special Issue (FR) · 2026
ISSN: 3085-5284
De l'avis en ligne à l'avantage concurrentiel : le rôle de l'intelligence artificielle dans la transformation de l'e-réputation hôtelière
EL AZYZY Youssef
Pages 37–53 · Université Cadi Ayyad, École Supérieure de Technologie d'Essaouira, Laboratoire Interdisciplinaire de Recherche en Environnement, Management, Energie et Tourisme (LIREMET)
⬇ Télécharger le PDF
Résumé
À l'ère de la transformation numérique, les avis en ligne sont devenus un déterminant clé des décisions touristiques, plaçant l'e-réputation au cœur des stratégies de compétitivité des établissements hôteliers et des destinations. Dans ce contexte, cet article analyse comment l'intelligence artificielle (IA) transforme la gestion de l'e-réputation, en permettant de passer d'une approche réactive à une logique proactive de création de valeur.

S'appuyant sur une revue systématique de la littérature selon le protocole PRISMA, l'étude mobilise les apports du marketing digital, du management hôtelier et du marketing territorial. Les résultats montrent que l'IA permet de transformer les avis en ligne en ressources stratégiques, contribuant à l'amélioration de la performance opérationnelle, de l'expérience client et de l'image des destinations, à travers des effets de halo et des mécanismes de transfert de réputation. Toutefois, la création d'un avantage concurrentiel durable dépend d'une intégration responsable de l'IA, fondée sur la transparence, la supervision humaine et la protection des données. L'article met ainsi en évidence le rôle structurant de l'e-réputation intelligente dans la compétitivité touristique.
Mots-clés : Avis en ligne, Intelligence Artificielle, E-réputation Hôtelière, Avantage concurrentiel, Compétitivité des Destinations

Références bibliographiques

  1. Abedin, E., Mendoza, A., Akbarighatar, P., & Karunasekera, S. (2024). Predicting Credibility of Online Reviews: An Integrated Approach. IEEE Access, 12. https://doi.org/10.1109/ACCESS.2024.3383846
  2. Água, M., Antonio, N., Carrasco, M. P., & Rassal, C. (2025). Large Language Models Powered Aspect-Based Sentiment Analysis for Enhanced Customer Insights. Tourism & Management Studies, 21(1), 1-19. https://doi.org/10.18089/tms.20250101
  3. Aranda Cuéllar, P., Such Devesa, M. J., & Torregrosa Martí, T. (2022). El big data, el desglose espacial y su rol en la detección de problemas de saturación en los destinos turísticos. Economía industrial, 426, 79-84. http://hdl.handle.net/10045/133358
  4. Baber, R., & Baber, P. (2023). Influence of Social Media Marketing Efforts, E-reputation and Destination Image on Intention to Visit among Tourists: Application of S–O–R Model. Journal of Hospitality and Tourism Insights, 6(5), 2298-2316. https://doi.org/10.1108/JHTI-06-2022-0270
  5. Chin, W. L., Haddock-Fraser, J., & Hampton, M. P. (2015). Destination competitiveness: evidence from Bali. Current Issues in Tourism 20(12) 1-25. https://doi.org/10.1080/13683500.2015.1111315
  6. Cho, S., Pekgün, P., Janakiraman, R., & Wang, J. (2024). The Competitive Effects of Online Reviews on Hotel Demand. Journal of Marketing, 88(2), 40-60. https://doi.org/10.1177/00222429231191449
  7. Chowdhary, K. R. (2020). Natural Language Processing. In Fundamentals of Artificial Intelligence (pp. 603–649). Springer India.
  8. Crouch, G. I., & Lamont, M. (2023). Destination branding and the competitive reputation of tourist places: A longitudinal analysis. Journal of Travel Research, 62(4), 815-832. https://doi.org/10.1177/00472875221100825
  9. Deng, S., Xu, H., & Zhao, J. (2024). Privacy-preserving mechanisms for AI-based reputation systems: A review of techniques and applications. Information Fusion, 102, 102045. https://doi.org/10.1016/j.inffus.2023.102045
  10. Doğangün, I., Şanlıöz-Özgen, H. K., & Türegün, N. (2025). Is hotel revenue performance effective for destination competitiveness? An assessment by wavelet coherence analysis. Quality & Quantity, 59, 1905–1931. https://doi.org/10.1007/s11135-024-02032-3
  11. Dominy C. L., Arvind V., Tang J. E., Bellaire C. P., Pasik S.D., Kim J. S., & Cho S. K. (2022). Scoliosis surgery in social media: a natural language processing approach to analyzing the online patient perspective. Spine Deformity 10(2):239–246. https://doi.org/10.1007/s43390-0
  12. Dwivedi, Y. K., Hughes, D. L., Baabdullah, A. M., Ribeiro-Navarrete, B., Giannakis, M., Al-Debei, M. M., & Koohang, A. (2023). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 71, 102580. https://doi.org/10.1016/j.ijinfomgt.2022.102580
  13. Elrayah, M., & Alshiha, A. A. (2024). Digital Marketing of Hospitality and Tourism Organizations. International Journal of Instructional Cases, 8(1), 55–72. https://ijicases.com/article-view/?id=104
  14. Fanjul Fernández, M. L., Pradana Pérez, J. F., Barceló Hernando, A., & Ferret Alcaraz, P. (2024). La IA como valor diferencial en la empresa: caso 123compareme [AI as a differential value in business: 123compareme case study]. European Public & Social Innovation Review, 9, 01-21. https://doi.org/10.31637/epsir-2024-842
  15. Floridi, L., Cowls, J., & Taddeo, M. (2024). Ethics of AI and reputational management in tourism: Principles, challenges, and opportunities. Annals of Tourism Research, 105, 103720. https://doi.org/10.1016/j.annals.2023.103720
  16. Gómez-Suárez, M., & Veloso, M (2022). Designing Facebook publications focused on hotel customer experience: How to improve brand attitude and booking intention. En Brand, Label, and Product Intelligence (pp. 247–258). Springer International Publishing.
  17. Hlee, S., Lee, H., & Koo, C. (2018). Hospitality and Tourism Online Review Research: A Systematic Analysis and Heuristic-Systematic Model. Sustainability, 10(4), 1141. https://doi.org/10.3390/su10041141
  18. Izquierdo, L., Ramón, A., Such, M., & Perles, J. (2019). Tourist environment and online reputation as a generator of added value in the sharing economy: The case of Airbnb in urban and sun-and-beach holiday destinations. Journal of Destination Marketing & Management, 11, 53-66. https://doi.org/10.1016/j.jdmm.2018.11.004
  19. Khan, A., Ashfaq, J., Bilal, M., Khan, M. H., & Shad, F. (2021). Destination Image Formation through User Generated Content (UGC). An updated Literature Review. Indian Journal of Economics and Business, 20(2).
  20. Kladou, S., Rigopoulou, E., & Kousi, S. (2023). Strategic destination branding: The role of social media in enhancing destination reputation and preference. Journal of Destination Marketing & Management, 28, 100774. https://doi.org/10.1016/j.jdmm.2023.100774
  21. Kovács, B. (2024). The Turing test of online reviews: Can we tell the difference between human-written and GPT-4-written online reviews? Marketing Letters, 35(4), 651-666. https://doi.org/10.1007/s11002-024-09729-3
  22. Ku, C. H., Chang, Y. C., & Wang, Y. (2024). How to strategically respond to online hotel reviews: A strategy-aware deep learning approach. Information & Management 61(5). https://doi.org/10.1016/j.im.2024.103970
  23. Liberati, M., Tetzlaff, J., & Altman, D. G. (2009). Preferred Reporting items for systematic reviews and meta analyses: THE PRISMA statement. Plos Medicine, 6(7), 1-6. https://doi.org/10.1371/journal.pmed.1000097
  24. Lopes, A. I., Malthouse, E. C., Dens, N., & De Pelsmacker, P. (2024). Is webcare good for business? A study of the effect of managerial response strategies to online reviews on hotel bookings. Journal of Service Management, 35(6), 22-41. https://doi.org/10.1108/JOSM-05-2023-0219
  25. Manrai, L. A., Manrai, A. K., & Friedeborn, S. (2020). Environmental determinants of destination competitiveness and its tourism attractions-basics-context, ABC, indicators: a review, conceptual model and propositions. Journal of Economics, Finance and Administrative Science, 25, 425-449. https://doi.org/10.1108/JEFAS-01-2018-0010
  26. Mariani, M., & Borghi, M. (2024). Online reviews, customer satisfaction and competitive positioning in hospitality. International Journal of Contemporary Hospitality Management, 36(1), 154-178. https://doi.org/10.1108/IJCHM-09-2022-1144
  27. Marine-Roig, E., & Anton Clavé, S. (2016). A detailed method for destination image analysis using user-generated content. Information Technology & Tourism, 15, 341-364. https://doi.org/10.1007/s40558-015-0040-1
  28. Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., & Galstyan, A. (2021). A survey on bias and fairness in machine learning. ACM Computing Surveys, 54(6), Article 115:1-115:35. https://doi.org/10.1145/3457607
  29. Moher, D., Shamsere, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., & Stewart, L. A. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic Reviews, 4(1), 1. https://doi.org/10.1186/2046-4053-4-1
  30. Morini-Marrero, S., Ramos-Henriquez, J. M., & Bilgihan, A. (2025). Analyzing the concordance and consistency of AI and human ratings in hospitality reviews. Journal of Hospitality and Tourism Technology. https://doi.org/10.1108/JHTT-04-2024-0251
  31. Nadeem, A., Missen, M. M. S., Reshan, M. S. A., Memon, M. A., Asiri, Y., Nizamani, M. A., Alsalami, M., & Shaikh, A. (2025). Resolving ambiguity in natural language for enhancement of aspect-based sentiment analysis of hotel reviews. PeerJ Computer Science, 11, e2635. https://doi.org/10.7717/peerj-cs.2635
  32. Nguyen, H. T. T., & Nguyen, T. X. (2023). Understanding customer experience with Vietnamese hotels by analyzing online reviews. Humanities and Social Sciences Communications, 10, 618. https://doi.org/10.1057/s41599-023-02098-8
  33. Nicolau, J. L., Xiang, Z., & Wang, D. (2024). Daily online review sentiment and hotel performance. International Journal of Contemporary Hospitality Management, 36(3), pp. 790-811. https://doi.org/10.1108/IJCHM-05-2022-0594
  34. Paulose, D., & Shakeel, A. (2022) Perceived experience, perceived value and customer satisfaction as antecedents to loyalty among hotel guests. Journal of Quality Assurance in Hospitality & Tourism, 23(2), 447-481. https://doi.org/10.1080/1528008x.2021.1884930
  35. Polli, C., & Santonocito, C. S. (2024). Reputation at Risk: Sentiment Analysis and Social Media Listening Tools under the Lens of Critical Multimodal Discourse Studies. HERMES - Journal of Language and Communication in Business, (64), 331-352. https://doi.org/10.7146/hjclb.v64.145480
  36. Shamsere, L., Moher, D., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., & Stewart, L. A. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. Bmj, 349. https://doi.org/10.1136/bmj.g7647
  37. Shin, J., Joung, J., & Lim, C. (2024). Determining directions of service quality management using online review mining with interpretable machine learning. International Journal of Hospitality Management, 118. https://doi.org/10.1016/j.ijhm.2023.103684
  38. Song, B., Xia, H., Law, R., Muskat, B., & Li, G. (2024). Discovery of smart hotels' competitiveness based on online reviews. International Journal of Hospitality Management, 123(4). https://doi.org/10.1016/j.ijhm.2024.103926
  39. Stylidis, D., Woosnam, K. M., Ivkov, M., & Kim, S. S. (2020). Destination loyalty explained through place attachment, destination familiarity and destination image. International Journal of Tourism Research, 22(5), 604-616. https://doi.org/10.1002/jtr.2359
  40. Tan, K. P. S., Liu, Y. V., & Litvin, S. W. (2025). ChatGPT and online service recovery: How potential customers react to managerial responses of negative reviews. Tourism Management, 107(3). https://doi.org/10.1016/j.tourman.2024.105057
  41. Torres, E. N., Wei, W., & Ridderstaat, J. (2024). Generative AI in the hospitality industry: An analysis of its impact on operational efficiency and customer experience. Tourism Management Perspectives, 51, 101235. https://doi.org/10.1016/j.tmp.2023.101235
  42. Van Nguyen, N., & Ngoc, T. B. (2024). Enhancing destination competitiveness through hotel service quality and destination image. Journal of Destination Marketing & Management, 31, 100852. https://doi.org/10.1016/j.jdmm.2023.100852
  43. Wang, Y., Wang, L., & Li, X. (2021). Algorithmic fairness in reputation systems: A review and research agenda. Journal of Management Information Systems, 38(3), 812-845. https://doi.org/10.1080/07421222.2021.1952291
  44. Weru, J. N., & Njoroge, J. M. (2021). MICE tourism and destination competitiveness: The role of hotel infrastructure and service quality. Tourism and Hospitality Research, 21(4), 462-478. https://doi.org/10.1177/14673584211019342
  45. Xie, K. L., So, K. K. F., & Wang, W. (2023). Online reputation and hotel pricing strategies: An empirical analysis. International Journal of Hospitality Management, 108, 103354. https://doi.org/10.1016/j.ijhm.2022.103354
  46. Yang, S., Ying, Y., & Liu, Y. (2025). Voice assistants in hospitality: Enhancing guest experience and electronic word-of-mouth. Journal of Travel Research, 64(1), 112-128. https://doi.org/10.1177/00472875241234567
  47. Zhang, Y., & Ha, H. Y. (2025). Continuous service innovation and its impact on customer retention: A latent growth model approach. Tourism Management, 102, 104876. https://doi.org/10.1016/j.tourman.2024.104876
  48. Zhang, Z., Xiang, Z., & Zuo, Y. (2025). Generative AI for online review management: Performance comparison with human responses. Annals of Tourism Research, 110, 103845. https://doi.org/10.1016/j.annals.2024.103845
  49. Zheng, X., Liu, Y., & Zhang, J. (2021). The role of online reviews in reducing perceived risk in tourism decision-making. Journal of Travel Research, 60(5), 1021-1035. https://doi.org/10.1177/0047287520921234
SciMeTech · Volume 2, Special Issue (FR) · 2026 · ISSN 3085-5284