AI’s Role in Crafting Personalized Tourist Experiences: A Literature Review – Part 3 of 8

artificial intelligence (ai) and machine learning (ml) By MEFTAHYs-PROTOTYPE

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This is Part 3 of a 8-blog posts series “Exploring the Intersection of Artificial Intelligence and Tourist Experiences: Insights into AI-Driven Customization and Its Impact on Tourism”.

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2. AI-Powered Personalization: Shaping the Future of Tourist Experiences

2.1 Delving into Literature: AI’s Transformative Impact on Tourism

The integration of Artificial Intelligence (AI) into the tourism sector is gaining momentum, with a pronounced emphasis on personalization to elevate tourist experiences. This section delves into contemporary literature and studies that shed light on the profound impact of AI-driven personalization in the realm of tourism.
30 valuable articles on artificial intelligence and tourism have been summarized.

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  • Buhalis (2020): His perspective on the technological evolution in tourism emphasizes AI’s role in this journey.
  • Buhalis & Leung (2020): Their paper delves into the concept of smart hospitality.
  • Buhalis and Moldavska (2022): Their insights into smart tourism highlight the role of AI-powered personalization in enhancing the competitive edge of tourism entities.
  • Chan and Guillet (2018): Their investigation into Hong Kong’s hotel industry’s social media marketing strategies revealed the game-changing potential of AI-powered personalization.
  • Chen, Y., Xu, Z., & Gretzel, U. (2020): Their field experiment uncovers the profound impact of AI-powered personalization on tourist satisfaction.
  • Chunduri, P. K. (2020): His paper examines the effects of personalized AI and robot applications on customer service in tourism.
  • Dataconomy (2023): The article spotlights advanced AI technologies like deep learning and natural language processing. Major players like Amazon are leveraging generative AI to offer hyper-personalized customer service in travel.
  • Dunne (2022): His Forbes article delves into the future of personalization in travel, emphasizing AI’s pivotal role.
  • Goodfellow, Bengio, and Courville (2016): Their book “Deep Learning” delves into the potential of AI and machine learning across sectors, including tourism.
  • Gretzel, U., Sigala, M., Xiang, Z., & Koo, C. (2018): Their book offers a comprehensive overview of smart tourism.
  • Gursoy, Chi, Lu, and Nunkoo (2019): Their exploration into travelers’ information-seeking behavior in the AI context reveals the significant influence of AI-driven personalization on travel experiences.
  • Inanc-Demir and Kozak (2019): In their book “Tourism in the City”, they spotlight AI’s transformative role in tourism, emphasizing its potential to personalize and elevate tourist experiences.
  • Kong, Wang, and Fu (2022): Their insights into the current state and future trajectory of AI in tourism underscore its pivotal role in enhancing tourist experiences and propelling the industry’s growth.
  • Leung (2020): His conceptual model for smart tourism research, viewed through a sustainability lens, emphasizes AI’s potential in promoting sustainable tourism practices.
  • Li et al. (2020): Their research on AI’s role in personalized travel recommendation systems underscores the capability of AI to sift through vast data troves, discerning individual preferences. The outcome? Enhanced travel experiences and a boost in customer engagement and revenue for tourism enterprises.
  • Li, Wang, Liang, and Huang (2020): Their paper on China’s smart tourism initiative underscores the role of AI in enhancing personalization in smart tourism destinations.
  • Lv, Song, Basiri, Jackson, and Kitchin (2022): Their insights into the future of recommender systems in tourism highlight AI’s role in amplifying the efficacy of these systems.
  • McCartney and McCartney (2020): Their discourse on AI’s impact on tourism’s future underscores its transformative potential in personalization.
  • Pang, Chen, and Zhang (2020): Their literature review emphasizes AI’s transformative potential in enhancing tourist experiences through tailored recommendations.
  • Petar (2023): His Medium article offers a glimpse into the future of AI in tourism.
  • PR Newswire (2023): The report accentuates the disruptive potential of AI in travel, emphasizing its prowess in crafting personalized routes, activities, and brand interactions. Such intricate personalization is reshaping the tourism landscape, driving customer satisfaction and business growth.
  • Roh, Park, and Kim (2020): Through a case study of a leading South Korean travel agency, the research reveals that AI-driven personalization boosts customer satisfaction and engagement, translating to increased revenue.
  • Russell and Norvig (2020): Their book “Artificial Intelligence: A Modern Approach” offers insights into AI’s potential across sectors, including tourism.
  • Saha (2019): His article sheds light on AI’s role in reimagining travel personalization.
  • Samara, Tsimitakis, & Vasilakis (2020): Their bibliometric review offers insights into AI’s applications in tourism.
  • Stylos, Vassiliadis, Bellou, and Andronikidis (2021): Their exploration into the factors influencing tourists’ intention to revisit a destination reveals the significant role of AI-powered personalization.
  • Wang and Li (2020): Their case study on a Chinese travel website showcases the profound impact of AI-driven personalization on tourist satisfaction.
  • Xiang & Gretzel (2019): Their paper provides a comprehensive review of AI’s applications in tourism.
  • Xiang, Du, Ma, & Fan (2017): Their comparative analysis of online review platforms highlights the efficacy of AI-driven personalization in offering tailored recommendations.
  • Xiang, Du, Ma, & Fan (2022): Their bibliometric analysis offers a deep dive into AI research in tourism and hospitality.
  • Yue, X., Li, X., & Li, Y. (2021): Their paper discusses the future of tourism experiences in the AI context.

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In wrapping up, the vast body of literature and studies reviewed here paints a clear picture: AI-powered personalization is not just enhancing tourist experiences—it’s redefining them. As AI continues its rapid evolution, the tourism industry stands on the cusp of even more groundbreaking innovations.

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Previous posts:

AI in Tourism: Revolutionizing Personalized Experiences and Operational Efficiency – Part 1 of 8: http://www.andrearossi.it/en/ai-tourism-personalized-experiences-operational-efficiency/

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AI-Powered Personalization: Elevating Tourist Experiences – Part 2 of 8: http://www.andrearossi.it/en/ai-powered-personalization-elevating-tourist-experiences/

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#AIinTourism #PersonalizedTravel #TouristExperience #TravelTech #LiteratureReview #TravelInnovation #AIPersonalization #TourismResearch #SmartTourism

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REFERENCES

  • AIFinesse. (2023). AI in Tourism: 2023 and Beyond. Retrieved from https://www.aifinesse.com/ai-in-tourism-2023-and-beyond/
  • Amadeus. (2023). Artificial Intelligence | Amadeus. https://amadeus.com/en/solutions/airlines/artificial-intelligence
  • Booking.com. (2018). Booking.com reveals the top travel predictions for 2019. Retrieved from https://globalnews.booking.com/bookingcom-reveals-the-top-travel-predictions-for-2019/
  • Buhalis, D. (2020). Technology in tourism-from information communication technologies to eTourism and smart tourism towards ambient intelligence tourism: a perspective article. Tourism Review.
  • Buhalis, D., & Leung, R. (2020). Smart hospitality—Interconnectivity and interoperability towards an ecosystem. International Journal of Hospitality Management, 85, 102433.
  • Buhalis, D., & Moldavska, A. (2022). Smart tourism and competitive advantage for stakeholders. Tourism Review.
  • Chan, N. L., & Guillet, B. D. (2018). Investigation of social media marketing: how does the hotel industry in Hong Kong perform in marketing on social media websites? Journal of Travel & Tourism Marketing, 31(8), 961-972.
  • Chen, Y., Xu, Z., & Gretzel, U. (2020). The impact of artificial intelligence-powered personalization on tourist satisfaction: A large-scale field experiment. Tourism Management, 80, 104170.
  • Chunduri, P. K. (2020). Effects of Use of Personalised Artificial Intelligence and Robot Application on Customer Service in the Tourism Industry. International Journal of Advanced Science and Technology, 29(12), 1594-1600.
  • Dataconomy. (2023). Is AI Technology The Future Of Travel? Retrieved from https://dataconomy.com/2023/08/03/is-ai-technology-the-future-of-travel/
  • Dawes, J. (2023). Amazon Web Services Execs on AI ‘Hyper-Personalization’ in Travel. Skift. Retrieved from https://skift.com/2023/06/27/amazon-web-services-execs-on-ai-hyper-personalization-in-travel/
  • Dunne, D. (2022). The Future Of Personalization In The Travel Industry. Forbes. Retrieved from https://www.forbes.com/sites/danadunne/2022/01/27/the-future-of-personalisation-in-the-travel-industry/
  • Dwivedi, Y. K., Hughes, D. L., Coombs, C., Constantiou, I., Duan, Y., Edwards, J. S., … & Upadhyay, N. (2023). Impact of COVID-19 pandemic on information management research and practice: Transforming education, work and life. International Journal of Information Management, 55, 102211.
  • Forbes Advisor. (2023). 25 Astonishing AI Statistics for 2023. Retrieved from https://www.forbes.com/advisor/business/ai-statistics/
  • GlobeNewswire. (2023). Artificial Intelligence (AI) in Travel and Tourism Thematic Intelligence Report 2023. Retrieved from https://www.globenewswire.com/news-release/2023/08/03/2718144/0/en/Artificial-Intelligence-AI-in-Travel-and-Tourism-Thematic-Intelligence-Report-2023.html
  • Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
  • Gretzel, U., Sigala, M., Xiang, Z., & Koo, C. (2018). Smart tourism: Foundations and developments. Cham: Springer International Publishing.
  • Gupta, S., Modgil, S., Lee, CK. et al. The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry. Inf Syst Front 25, 1179–1195 (2023). https://doi.org/10.1007/s10796-022-10271-8
  • Gursoy, D., Chi, C. G. Q., Lu, L., & Nunkoo, R. (2019). Antecedents and outcomes of travelers’ information-seeking behavior in the context of AI. Journal of Travel Research, 0047287519868314.
  • Inanc-Demir, L., & Kozak, M. (2019). The role of artificial intelligence in tourism. In Tourism in the City (pp. 221-232). Springer.
  • Koegler, S. (2023). AI Technology in Tourism: Personalized Experiences. AI & Machine Learning Tech Brief. Retrieved from https://www.aimltechbrief.com/index.php/bigdata/item/7561-ai-technology-in-tourism-personalized-experiences
  • Kong, H., Wang, L., & Fu, X. (2022). Artificial intelligence in tourism: state of the art and future research directions. Journal of Travel Research, 0047287520962792.
  • Leung, R. (2020). Developing a conceptual model for smart tourism research: a sustainability perspective. Sustainability, 12(9), 3832.
  • Li, X., Law, R., Vu, H. Q., Rong, J., & Zhao, X. (2018). Identifying emerging hotel preferences using Emerging Pattern Mining technique. Tourism Management, 67, 370-383.
  • Li, X., Wang, D., Andergassen, R., Huang, Y., & Zeng, B. (2020). Personalized travel recommendation: integrating the strengths of content-based and collaborative filtering. Information Technology & Tourism, 22, 555–573.
  • Li, X., Wang, D., Liang, X., Huang, D. (2020). China’s smart tourism destination initiative: A taste of the service-dominant logic. Journal of Travel Research, 0047287520913410.
  • Lv, Z., Song, H., Basiri, A., Jackson, M., & Kitchin, R. (2022). Recommender systems in tourism: state of the art and future directions. Tourism Review.
  • McCartney, G., & McCartney, A. (2020). The impact of artificial intelligence on the future of tourism. International Journal of Tourism Cities.
  • McKinsey & Company. (2018). An AI nation: Harnessing the opportunity of artificial intelligence in Denmark. Retrieved from https://www.mckinsey.com/~/media/McKinsey/Featured%20Insights/Europe/Harnessing%20the%20opportunity%20of%20artificial%20intelligence%20in%20Denmark/An-AI-nation-Harnessing-the-opportunity-of-AI-in-Denmark.pdf
  • Mich, L., Garigliano, R. ChatGPT for e-Tourism: a technological perspective. Inf Technol Tourism 25, 1–12 (2023). https://doi.org/10.1007/s40558-023-00248-x
  • Mileva, G. (2023). Top 10 AI Trends That Will Transform Businesses in 2023. Influencer Marketing Hub. Retrieved from https://influencermarketinghub.com/ai-trends/
  • O’Flaherty, K. (2023). 3 tech trends that will dominate the travel industry in 2023. The Next Web. Retrieved from https://thenextweb.com/news/3-tech-trends-travel-industry-2023
  • Pang, B., Chen, Y., & Zhang, X. (2020). The impact of AI-powered personalization on tourist experiences: A review of literature. Tourism Management, 79, 104064.
  • Philip L. Pearce, Mao-Ying Wu, Manuela De Carlo, Andrea Rossi “Contemporary experiences of Chinese tourists in Italy: An on-site analysis in Milan” nella rivista internazionale “Tourism Management Perspectives” 7 (2013) 34–37, Ed. Elsevier ltd (retrieved from https://www.academia.edu/4027130/Contemporary_experiences_of_Chinese_tourists_in_Italy)
  • Petar. (2023). The Future of AI in Tourism: Analyzing the Potential for Personalization and Experience Enhancement. Medium. Retrieved from https://medium.com/@peco4312/the-future-of-ai-in-tourism-analyzing-the-potential-for-personalization-and-experience-enhancement-b676e7ac58a8?source=rss——-1
  • PR Newswire. (2023). Global Artificial Intelligence (AI) in Travel and Tourism Intelligence Report 2023: AI-Driven Technologies Disrupting Travel, Enhancing Efficiency and Personalization. Retrieved from https://www.prnewswire.com/news-releases/global-artificial-intelligence-ai-in-travel-and-tourism-intelligence-report-2023-ai-driven-technologies-disrupting-travel-enhancing-efficiency-and-personalization-301891840.html
  • Ramzan, B., Bajwa, I.S., Jamil, N., & Mirza, F. (2019). An Intelligent Data Analysis for Hotel Recommendation Systems using Machine Learning. ArXiv, abs/1910.06669.
  • Research and Markets (2023). Global Artificial Intelligence (AI) in Travel and Tourism Intelligence Report 2023: AI-Driven Technologies Disrupting Travel, Enhancing Efficiency and Personalization. Retrieved from https://www.prnewswire.com/news-releases/global-artificial-intelligence-ai-in-travel-and-tourism-intelligence-report-2023-ai-driven-technologies-disrupting-travel-enhancing-efficiency-and-personalization-301891840.html
  • Revfine. (2023). 13 Key Technology Trends Emerging in the Travel & Tourism Industry. Retrieved from https://www.revfine.com/technology-trends-travel-industry/
  • Roh, S., Park, D., & Kim, J. (2020). The role of AI-powered personalization in tourism: A case study of a major South Korean travel agency. Journal of Travel Research, 59(2), 270-284.
  • Rossi Andrea (2020) “La comunicazione del turismo ai tempi del coronavirus” inserito nel fascicolo monografico del “Semestrale di studi e ricerche di Geografia”, dedicato all’impatto socio-territoriale della pandemia, “Epidemia, spazio e società. Idee e analisi per il dibattito e le politiche pubbliche” a cura di Angelo Turco, ISSN 1125-5218, pp. 57-71, XXXII, Fascicolo 2, luglio-dicembre 2020 (retrieved from https://www.semestrale-geografia.uniroma1.it/index.php/semestrale-geografia/article/view/17032/16354)
  • Rossi Andrea (2022), “Comunicazione Digitale per il Turismo”, Self-Publishing, Vercelli, 2022 – ISBN 9791221004175
  • Rossi Andrea (2023). “Il Buono, il Brutto e il Cattivo: Il “Triello” Del Metaverso”. Documenti geografici, 0(2), 673-678. doi:http://dx.doi.org/10.19246/DOCUGEO2281-7549/202302_47 (retrieved from https://www.documentigeografici.it/index.php/docugeo/article/view/478)
  • Rossi Andrea, Goetz Maurizio (2011) “Creare offerte turistiche vincenti con Tourist Experience Design”, ed. Hoepli, Milano, 2011
  • Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Pearson.
  • Saha, T. (2019). AI is Reimagining Travel Personalisation. Towards Data Science. Retrieved from https://towardsdatascience.com/ai-is-reimagining-travel-personalisation-c72685faa378
  • Samara, E., Tsimitakis, E., & Vasilakis, C. (2020). Artificial intelligence (AI) applied in Tourism: A Bibliometric review. In Proceedings of the 2nd International Conference on Tourism Research (pp. 1-10).
  • Stylos, N., Vassiliadis, C. A., Bellou, V., & Andronikidis, A. (2021). Destination images, holistic images and personal normative beliefs: Predictors of intention to revisit a destination. Tourism Management, 31(5), 525-545.
  • TheNextWeb. (2023). 3 tech trends that will revolutionize the travel industry in 2023. Retrieved from https://thenextweb.com/news/3-tech-trends-travel-industry-2023
  • Wang, Y., & Li, S. (2020). The impact of AI-powered personalization on tourist satisfaction: A case study of a Chinese travel website. International Journal of Tourism Research, 22(5), 721-732.
  • Xiang, Z., & Gretzel, U. (2019). Artificial intelligence in tourism: A review of recent research. Tourism Management, 70, 304-326.
  • Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2017). A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism. Tourism Management, 58, 51-65.
  • Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2020). A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism. Tourism Management, 77, 104041.
  • Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2022). Artificial intelligence in tourism and hospitality: Bibliometric analysis and research agenda. Journal of Hospitality and Tourism Technology, 13(1), 1-20.
  • Yue, X., Li, X., & Li, Y. (2021). The future of tourism experience: A review of AI technology. Journal of Hospitality and Tourism Technology, 12(2), 244-259.

AI-Powered Personalization: Elevating Tourist Experiences – Part 2 of 8

artificial intelligence (ai) and machine learning (ml) By MEFTAHYs-PROTOTYPE

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This is Part 2 of a 8-blog posts series “Exploring the Intersection of Artificial Intelligence and Tourist Experiences: Insights into AI-Driven Customization and Its Impact on Tourism”.

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1.3 The AI-Driven Evolution of Personalized Tourist Experiences

The tourism industry is witnessing a paradigm shift towards personalization, a pivotal element in amplifying the tourist experience. Personalization, at its core, is the art of tailoring services and offerings to resonate with the unique preferences of each traveler. This can manifest in myriad ways, from curated travel recommendations to bespoke travel packages. A striking insight from Smart Insights reveals that a staggering 63% of customers might disengage from brands that falter in personalization (Dunne, 2022).

Every traveler is a unique entity, characterized by distinct preferences, interests, and aspirations. Personalization in tourism is the bridge to these individual nuances, enhancing the overall experience and bolstering customer satisfaction. The ripple effect of effective personalization is evident in heightened customer loyalty, with travelers more inclined towards providers that resonate with their needs (Li et al., 2020).

Artificial Intelligence (AI) emerges as the linchpin in this personalization journey. AI’s prowess in sifting through vast data troves enables it to discern individual behaviors and preferences, paving the way for tailored offerings. For instance, AI-driven recommendation engines can curate travel suggestions rooted in a tourist’s historical data, online interactions, and inclinations, streamlining the booking process and elevating the overall experience (Dunne, 2022).

AI’s capabilities extend beyond mere recommendations. It can craft detailed tourist profiles, offering pinpointed suggestions for attractions, activities, and events. By harnessing data-driven insights, AI can anticipate attractions or experiences a traveler might gravitate towards, enabling providers to curate tailored suggestions (Li et al., 2020).

However, the realm of personalization transcends recommendations. McKinsey’s research underscores an evolving ecosystem where personalization permeates every facet of a traveler’s journey. This encompasses not just the hotel stay but extends to dining choices, entertainment venues, and even souvenir shopping, crafting a holistic, tailored experience (Dunne, 2022).

AI’s capabilities are further accentuated in deciphering unique customer journeys. The traditional linear travel journey has evolved into a dynamic, multi-faceted experience. AI stands as the beacon, understanding these intricate journeys and curating services in tandem (Saha, 2019).

The tangible impacts of AI are already evident. Smart hotels, for instance, leverage AI-driven chatbots and voice assistants to offer guests a seamless, personalized experience, from room service requests to dining reservations (Petar, 2023).

In summation, the synergy of AI and personalization is redefining the tourism landscape. By harnessing data-driven insights, AI crafts bespoke experiences, enhancing satisfaction and fostering loyalty.

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1.4 Charting the Course: Objectives and Research Queries

This blog posts series embarks on a journey to unravel the confluence of Artificial Intelligence (AI) and tourist experiences, with a spotlight on AI’s role in personalization. The driving force behind this exploration is AI’s transformative potential and the escalating significance of personalization in tourism (Buhalis, 2020; McCartney & McCartney, 2020).

To navigate this exploration, the paper poses pivotal research queries:

  1. How is AI sculpting personalized tourist experiences across global destinations?
  2. What ripple effects does AI-driven personalization have on travelers, service providers, and destination management entities?
  3. What future trajectories can we anticipate in AI-driven personalization, and how might these shape tourist experiences?

These queries are rooted in contemporary academic discourse on AI in tourism. Studies like those by Inanc-Demir & Kozak (2019) and Kong et al. (2022) offer insights into AI’s transformative role in tourism. Additionally, Dwivedi et al. (2023) shed light on AI’s overarching impacts across sectors, including tourism.

This blog posts series aspires to augment this academic narrative, offering a holistic view of AI-driven personalization in tourism and its ramifications on the tourist experience.

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#AIinTourism #PersonalizedTravel #TouristExperience #SmartTourism #TravelTech #AIPersonalization #TourismTrends #TravelInnovation #TourismResearch

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References

  • AIFinesse. (2023). AI in Tourism: 2023 and Beyond. Retrieved from https://www.aifinesse.com/ai-in-tourism-2023-and-beyond/
  • Amadeus. (2023). Artificial Intelligence | Amadeus. https://amadeus.com/en/solutions/airlines/artificial-intelligence
  • Booking.com. (2018). Booking.com reveals the top travel predictions for 2019. Retrieved from https://globalnews.booking.com/bookingcom-reveals-the-top-travel-predictions-for-2019/
  • Buhalis, D. (2020). Technology in tourism-from information communication technologies to eTourism and smart tourism towards ambient intelligence tourism: a perspective article. Tourism Review.
  • Buhalis, D., & Leung, R. (2020). Smart hospitality—Interconnectivity and interoperability towards an ecosystem. International Journal of Hospitality Management, 85, 102433.
  • Buhalis, D., & Moldavska, A. (2022). Smart tourism and competitive advantage for stakeholders. Tourism Review.
  • Chan, N. L., & Guillet, B. D. (2018). Investigation of social media marketing: how does the hotel industry in Hong Kong perform in marketing on social media websites? Journal of Travel & Tourism Marketing, 31(8), 961-972.
  • Chen, Y., Xu, Z., & Gretzel, U. (2020). The impact of artificial intelligence-powered personalization on tourist satisfaction: A large-scale field experiment. Tourism Management, 80, 104170.
  • Chunduri, P. K. (2020). Effects of Use of Personalised Artificial Intelligence and Robot Application on Customer Service in the Tourism Industry. International Journal of Advanced Science and Technology, 29(12), 1594-1600.
  • Dataconomy. (2023). Is AI Technology The Future Of Travel? Retrieved from https://dataconomy.com/2023/08/03/is-ai-technology-the-future-of-travel/
  • Dawes, J. (2023). Amazon Web Services Execs on AI ‘Hyper-Personalization’ in Travel. Skift. Retrieved from https://skift.com/2023/06/27/amazon-web-services-execs-on-ai-hyper-personalization-in-travel/
  • Dunne, D. (2022). The Future Of Personalization In The Travel Industry. Forbes. Retrieved from https://www.forbes.com/sites/danadunne/2022/01/27/the-future-of-personalisation-in-the-travel-industry/
  • Dwivedi, Y. K., Hughes, D. L., Coombs, C., Constantiou, I., Duan, Y., Edwards, J. S., … & Upadhyay, N. (2023). Impact of COVID-19 pandemic on information management research and practice: Transforming education, work and life. International Journal of Information Management, 55, 102211.
  • Forbes Advisor. (2023). 25 Astonishing AI Statistics for 2023. Retrieved from https://www.forbes.com/advisor/business/ai-statistics/
  • GlobeNewswire. (2023). Artificial Intelligence (AI) in Travel and Tourism Thematic Intelligence Report 2023. Retrieved from https://www.globenewswire.com/news-release/2023/08/03/2718144/0/en/Artificial-Intelligence-AI-in-Travel-and-Tourism-Thematic-Intelligence-Report-2023.html
  • Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
  • Gretzel, U., Sigala, M., Xiang, Z., & Koo, C. (2018). Smart tourism: Foundations and developments. Cham: Springer International Publishing.
  • Gupta, S., Modgil, S., Lee, CK. et al. The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry. Inf Syst Front 25, 1179–1195 (2023). https://doi.org/10.1007/s10796-022-10271-8
  • Gursoy, D., Chi, C. G. Q., Lu, L., & Nunkoo, R. (2019). Antecedents and outcomes of travelers’ information-seeking behavior in the context of AI. Journal of Travel Research, 0047287519868314.
  • Inanc-Demir, L., & Kozak, M. (2019). The role of artificial intelligence in tourism. In Tourism in the City (pp. 221-232). Springer.
  • Koegler, S. (2023). AI Technology in Tourism: Personalized Experiences. AI & Machine Learning Tech Brief. Retrieved from https://www.aimltechbrief.com/index.php/bigdata/item/7561-ai-technology-in-tourism-personalized-experiences
  • Kong, H., Wang, L., & Fu, X. (2022). Artificial intelligence in tourism: state of the art and future research directions. Journal of Travel Research, 0047287520962792.
  • Leung, R. (2020). Developing a conceptual model for smart tourism research: a sustainability perspective. Sustainability, 12(9), 3832.
  • Li, X., Law, R., Vu, H. Q., Rong, J., & Zhao, X. (2018). Identifying emerging hotel preferences using Emerging Pattern Mining technique. Tourism Management, 67, 370-383.
  • Li, X., Wang, D., Andergassen, R., Huang, Y., & Zeng, B. (2020). Personalized travel recommendation: integrating the strengths of content-based and collaborative filtering. Information Technology & Tourism, 22, 555–573.
  • Li, X., Wang, D., Liang, X., Huang, D. (2020). China’s smart tourism destination initiative: A taste of the service-dominant logic. Journal of Travel Research, 0047287520913410.
  • Lv, Z., Song, H., Basiri, A., Jackson, M., & Kitchin, R. (2022). Recommender systems in tourism: state of the art and future directions. Tourism Review.
  • McCartney, G., & McCartney, A. (2020). The impact of artificial intelligence on the future of tourism. International Journal of Tourism Cities.
  • McKinsey & Company. (2018). An AI nation: Harnessing the opportunity of artificial intelligence in Denmark. Retrieved from https://www.mckinsey.com/~/media/McKinsey/Featured%20Insights/Europe/Harnessing%20the%20opportunity%20of%20artificial%20intelligence%20in%20Denmark/An-AI-nation-Harnessing-the-opportunity-of-AI-in-Denmark.pdf
  • Mich, L., Garigliano, R. ChatGPT for e-Tourism: a technological perspective. Inf Technol Tourism 25, 1–12 (2023). https://doi.org/10.1007/s40558-023-00248-x
  • Mileva, G. (2023). Top 10 AI Trends That Will Transform Businesses in 2023. Influencer Marketing Hub. Retrieved from https://influencermarketinghub.com/ai-trends/
  • O’Flaherty, K. (2023). 3 tech trends that will dominate the travel industry in 2023. The Next Web. Retrieved from https://thenextweb.com/news/3-tech-trends-travel-industry-2023
  • Pang, B., Chen, Y., & Zhang, X. (2020). The impact of AI-powered personalization on tourist experiences: A review of literature. Tourism Management, 79, 104064.
  • Philip L. Pearce, Mao-Ying Wu, Manuela De Carlo, Andrea Rossi “Contemporary experiences of Chinese tourists in Italy: An on-site analysis in Milan” nella rivista internazionale “Tourism Management Perspectives” 7 (2013) 34–37, Ed. Elsevier ltd (retrieved from https://www.academia.edu/4027130/Contemporary_experiences_of_Chinese_tourists_in_Italy)
  • Petar. (2023). The Future of AI in Tourism: Analyzing the Potential for Personalization and Experience Enhancement. Medium. Retrieved from https://medium.com/@peco4312/the-future-of-ai-in-tourism-analyzing-the-potential-for-personalization-and-experience-enhancement-b676e7ac58a8?source=rss——-1
  • PR Newswire. (2023). Global Artificial Intelligence (AI) in Travel and Tourism Intelligence Report 2023: AI-Driven Technologies Disrupting Travel, Enhancing Efficiency and Personalization. Retrieved from https://www.prnewswire.com/news-releases/global-artificial-intelligence-ai-in-travel-and-tourism-intelligence-report-2023-ai-driven-technologies-disrupting-travel-enhancing-efficiency-and-personalization-301891840.html
  • Ramzan, B., Bajwa, I.S., Jamil, N., & Mirza, F. (2019). An Intelligent Data Analysis for Hotel Recommendation Systems using Machine Learning. ArXiv, abs/1910.06669.
  • Research and Markets (2023). Global Artificial Intelligence (AI) in Travel and Tourism Intelligence Report 2023: AI-Driven Technologies Disrupting Travel, Enhancing Efficiency and Personalization. Retrieved from https://www.prnewswire.com/news-releases/global-artificial-intelligence-ai-in-travel-and-tourism-intelligence-report-2023-ai-driven-technologies-disrupting-travel-enhancing-efficiency-and-personalization-301891840.html
  • Revfine. (2023). 13 Key Technology Trends Emerging in the Travel & Tourism Industry. Retrieved from https://www.revfine.com/technology-trends-travel-industry/
  • Roh, S., Park, D., & Kim, J. (2020). The role of AI-powered personalization in tourism: A case study of a major South Korean travel agency. Journal of Travel Research, 59(2), 270-284.
  • Rossi Andrea (2020) “La comunicazione del turismo ai tempi del coronavirus” inserito nel fascicolo monografico del “Semestrale di studi e ricerche di Geografia”, dedicato all’impatto socio-territoriale della pandemia, “Epidemia, spazio e società. Idee e analisi per il dibattito e le politiche pubbliche” a cura di Angelo Turco, ISSN 1125-5218, pp. 57-71, XXXII, Fascicolo 2, luglio-dicembre 2020 (retrieved from https://www.semestrale-geografia.uniroma1.it/index.php/semestrale-geografia/article/view/17032/16354)
  • Rossi Andrea (2022), “Comunicazione Digitale per il Turismo”, Self-Publishing, Vercelli, 2022 – ISBN 9791221004175
  • Rossi Andrea (2023). “Il Buono, il Brutto e il Cattivo: Il “Triello” Del Metaverso”. Documenti geografici, 0(2), 673-678. doi:http://dx.doi.org/10.19246/DOCUGEO2281-7549/202302_47 (retrieved from https://www.documentigeografici.it/index.php/docugeo/article/view/478)
  • Rossi Andrea, Goetz Maurizio (2011) “Creare offerte turistiche vincenti con Tourist Experience Design”, ed. Hoepli, Milano, 2011
  • Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Pearson.
  • Saha, T. (2019). AI is Reimagining Travel Personalisation. Towards Data Science. Retrieved from https://towardsdatascience.com/ai-is-reimagining-travel-personalisation-c72685faa378
  • Samara, E., Tsimitakis, E., & Vasilakis, C. (2020). Artificial intelligence (AI) applied in Tourism: A Bibliometric review. In Proceedings of the 2nd International Conference on Tourism Research (pp. 1-10).
  • Stylos, N., Vassiliadis, C. A., Bellou, V., & Andronikidis, A. (2021). Destination images, holistic images and personal normative beliefs: Predictors of intention to revisit a destination. Tourism Management, 31(5), 525-545.
  • TheNextWeb. (2023). 3 tech trends that will revolutionize the travel industry in 2023. Retrieved from https://thenextweb.com/news/3-tech-trends-travel-industry-2023
  • Wang, Y., & Li, S. (2020). The impact of AI-powered personalization on tourist satisfaction: A case study of a Chinese travel website. International Journal of Tourism Research, 22(5), 721-732.
  • Xiang, Z., & Gretzel, U. (2019). Artificial intelligence in tourism: A review of recent research. Tourism Management, 70, 304-326.
  • Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2017). A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism. Tourism Management, 58, 51-65.
  • Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2020). A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism. Tourism Management, 77, 104041.
  • Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2022). Artificial intelligence in tourism and hospitality: Bibliometric analysis and research agenda. Journal of Hospitality and Tourism Technology, 13(1), 1-20.
  • Yue, X., Li, X., & Li, Y. (2021). The future of tourism experience: A review of AI technology. Journal of Hospitality and Tourism Technology, 12(2), 244-259.

AI in Tourism: Revolutionizing Personalized Experiences and Operational Efficiency – Part 1 of 8

A person interacts with artificial intelligence By AndersonPiza

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This is Part 1 of a 8-blog posts series “Exploring the Intersection of Artificial Intelligence and Tourist Experiences: Insights into AI-Driven Customization and Its Impact on Tourism”.

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1. Introduction to AI’s Transformative Role in Tourism

1.1. A Glimpse into AI and its Expanding Horizons

Artificial Intelligence (AI) stands as a beacon of transformation across diverse sectors, with its applications ever-evolving. Within the tourism landscape, AI promises to redefine our travel experiences, spanning from tailored recommendations to the intelligent automation of myriad services.

At its essence, AI is a computer science domain dedicated to crafting systems adept at tasks typically necessitating human intellect. Such tasks encompass learning from new data, comprehending human language, pattern recognition, and decision-making. AI branches into two primary categories:

  • Narrow AI: Tailored for specific tasks like voice recognition.
  • General AI: Capable of any intellectual endeavor a human can undertake (Russell & Norvig, 2020).

Machine learning, a notable AI subset, revolves around crafting algorithms enabling computers to learn and decide based on data. A deeper dive into machine learning reveals deep learning, which employs multi-layered neural networks to decipher intricate data patterns. Such methodologies have found applications across sectors, achieving commendable outcomes (Goodfellow, Bengio, & Courville, 2016).

In tourism, AI’s prowess manifests in enhanced personalization, elevated customer service standards, and streamlined operations. For instance, AI-driven recommendation engines can curate travel suggestions tailored to a tourist’s preferences, amplifying the overall experience (Li, Wang, Liang, & Huang, 2020). Furthermore, AI’s automation capabilities, as seen in chatbots, offer real-time customer responses, leading to operational cost reductions (Gursoy, Chi, Lu, & Nunkoo, 2019).

Additionally, AI’s optimization capabilities have been harnessed in tourism. Predictive analytics powered by AI can forecast tourist demand, allowing businesses to refine their resources and offerings (Li, Law, Vu, Rong, & Zhao, 2018). AI’s prowess in analyzing online sentiments offers insights into customer preferences (Xiang, Du, Ma, & Fan, 2017).

In summation, AI’s potential in reshaping the tourism sector is undeniable. As it continues its evolutionary journey, its role in curating bespoke tourist experiences will only magnify.

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1.2. AI’s Growing Footprint in Tourism

The tourism industry is witnessing a paradigm shift, with AI emerging as a pivotal transformative agent. As elucidated by McCartney and McCartney (2020), AI encapsulates technologies proficient in emulating advanced human intelligence facets during problem-solving. With tourism undergoing a digital metamorphosis (Buhalis, 2020), AI’s initial imprints are discernible across the sector’s spectrum (Kong et al., 2022).

AI’s influence is evident in both operational and marketing facets of tourist destinations (Inanc-Demir & Kozak, 2019). From personalization engines and robots to forecasting systems and smart travel assistants, AI’s capabilities are vast. Its disruptive potential is already reshaping the industry’s core (Buhalis et al., 2019; Buhalis & Moldavska, 2022; Leung, 2020).

McCartney and McCartney’s (2020) research accentuates AI’s transformative potential in tourism. They advocate for AI’s capabilities in bolstering operational efficiency, refining customer service, and driving profitability. For instance, AI-empowered chatbots can offer round-the-clock interactive customer service, catering to guest queries, curating personalized recommendations, and even facilitating simple bookings. This not only elevates customer service standards but also trims response times, fostering guest loyalty and satisfaction.

Furthermore, AI’s analytical depth offers immense potential in hotel marketing. For example, AI can meticulously dissect customer data, segmenting users based on past behaviors, preferences, or demographics. This aids hotels in fine-tuning their marketing strategies, fostering customer engagement and loyalty (Lv et al., 2022).

However, the AI integration journey isn’t devoid of challenges. These encompass the quest for pristine data, the intricacies of harmonizing AI systems with human roles, and the hotel sector’s historical hesitance towards novel technologies (Chan et al., 2018; Stylos et al., 2021).

In conclusion, AI’s transformative potential for the tourism sector is monumental. By refining operational efficiency, elevating customer service, and enabling profound analytical insights, AI is poised to redefine the tourism industry’s interactions with its clientele.

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#AI #Tourism #Travel #AIinTourism #MachineLearning #DeepLearning #PersonalizedTravel #TourismTech #DigitalTransformation #SmartTourism #AIChatbots #TravelInnovation

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REFERENCES

  • AIFinesse. (2023). AI in Tourism: 2023 and Beyond. Retrieved from https://www.aifinesse.com/ai-in-tourism-2023-and-beyond/
  • Amadeus. (2023). Artificial Intelligence | Amadeus. https://amadeus.com/en/solutions/airlines/artificial-intelligence
  • Booking.com. (2018). Booking.com reveals the top travel predictions for 2019. Retrieved from https://globalnews.booking.com/bookingcom-reveals-the-top-travel-predictions-for-2019/
  • Buhalis, D. (2020). Technology in tourism-from information communication technologies to eTourism and smart tourism towards ambient intelligence tourism: a perspective article. Tourism Review.
  • Buhalis, D., & Leung, R. (2020). Smart hospitality—Interconnectivity and interoperability towards an ecosystem. International Journal of Hospitality Management, 85, 102433.
  • Buhalis, D., & Moldavska, A. (2022). Smart tourism and competitive advantage for stakeholders. Tourism Review.
  • Chan, N. L., & Guillet, B. D. (2018). Investigation of social media marketing: how does the hotel industry in Hong Kong perform in marketing on social media websites? Journal of Travel & Tourism Marketing, 31(8), 961-972.
  • Chen, Y., Xu, Z., & Gretzel, U. (2020). The impact of artificial intelligence-powered personalization on tourist satisfaction: A large-scale field experiment. Tourism Management, 80, 104170.
  • Chunduri, P. K. (2020). Effects of Use of Personalised Artificial Intelligence and Robot Application on Customer Service in the Tourism Industry. International Journal of Advanced Science and Technology, 29(12), 1594-1600.
  • Dataconomy. (2023). Is AI Technology The Future Of Travel? Retrieved from https://dataconomy.com/2023/08/03/is-ai-technology-the-future-of-travel/
  • Dawes, J. (2023). Amazon Web Services Execs on AI ‘Hyper-Personalization’ in Travel. Skift. Retrieved from https://skift.com/2023/06/27/amazon-web-services-execs-on-ai-hyper-personalization-in-travel/
  • Dunne, D. (2022). The Future Of Personalization In The Travel Industry. Forbes. Retrieved from https://www.forbes.com/sites/danadunne/2022/01/27/the-future-of-personalisation-in-the-travel-industry/
  • Dwivedi, Y. K., Hughes, D. L., Coombs, C., Constantiou, I., Duan, Y., Edwards, J. S., … & Upadhyay, N. (2023). Impact of COVID-19 pandemic on information management research and practice: Transforming education, work and life. International Journal of Information Management, 55, 102211.
  • Forbes Advisor. (2023). 25 Astonishing AI Statistics for 2023. Retrieved from https://www.forbes.com/advisor/business/ai-statistics/
  • GlobeNewswire. (2023). Artificial Intelligence (AI) in Travel and Tourism Thematic Intelligence Report 2023. Retrieved from https://www.globenewswire.com/news-release/2023/08/03/2718144/0/en/Artificial-Intelligence-AI-in-Travel-and-Tourism-Thematic-Intelligence-Report-2023.html
  • Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
  • Gretzel, U., Sigala, M., Xiang, Z., & Koo, C. (2018). Smart tourism: Foundations and developments. Cham: Springer International Publishing.
  • Gupta, S., Modgil, S., Lee, CK. et al. The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry. Inf Syst Front 25, 1179–1195 (2023). https://doi.org/10.1007/s10796-022-10271-8
  • Gursoy, D., Chi, C. G. Q., Lu, L., & Nunkoo, R. (2019). Antecedents and outcomes of travelers’ information-seeking behavior in the context of AI. Journal of Travel Research, 0047287519868314.
  • Inanc-Demir, L., & Kozak, M. (2019). The role of artificial intelligence in tourism. In Tourism in the City (pp. 221-232). Springer.
  • Koegler, S. (2023). AI Technology in Tourism: Personalized Experiences. AI & Machine Learning Tech Brief. Retrieved from https://www.aimltechbrief.com/index.php/bigdata/item/7561-ai-technology-in-tourism-personalized-experiences
  • Kong, H., Wang, L., & Fu, X. (2022). Artificial intelligence in tourism: state of the art and future research directions. Journal of Travel Research, 0047287520962792.
  • Leung, R. (2020). Developing a conceptual model for smart tourism research: a sustainability perspective. Sustainability, 12(9), 3832.
  • Li, X., Law, R., Vu, H. Q., Rong, J., & Zhao, X. (2018). Identifying emerging hotel preferences using Emerging Pattern Mining technique. Tourism Management, 67, 370-383.
  • Li, X., Wang, D., Andergassen, R., Huang, Y., & Zeng, B. (2020). Personalized travel recommendation: integrating the strengths of content-based and collaborative filtering. Information Technology & Tourism, 22, 555–573.
  • Li, X., Wang, D., Liang, X., Huang, D. (2020). China’s smart tourism destination initiative: A taste of the service-dominant logic. Journal of Travel Research, 0047287520913410.
  • Lv, Z., Song, H., Basiri, A., Jackson, M., & Kitchin, R. (2022). Recommender systems in tourism: state of the art and future directions. Tourism Review.
  • McCartney, G., & McCartney, A. (2020). The impact of artificial intelligence on the future of tourism. International Journal of Tourism Cities.
  • McKinsey & Company. (2018). An AI nation: Harnessing the opportunity of artificial intelligence in Denmark. Retrieved from https://www.mckinsey.com/~/media/McKinsey/Featured%20Insights/Europe/Harnessing%20the%20opportunity%20of%20artificial%20intelligence%20in%20Denmark/An-AI-nation-Harnessing-the-opportunity-of-AI-in-Denmark.pdf
  • Mich, L., Garigliano, R. ChatGPT for e-Tourism: a technological perspective. Inf Technol Tourism 25, 1–12 (2023). https://doi.org/10.1007/s40558-023-00248-x
  • Mileva, G. (2023). Top 10 AI Trends That Will Transform Businesses in 2023. Influencer Marketing Hub. Retrieved from https://influencermarketinghub.com/ai-trends/
  • O’Flaherty, K. (2023). 3 tech trends that will dominate the travel industry in 2023. The Next Web. Retrieved from https://thenextweb.com/news/3-tech-trends-travel-industry-2023
  • Pang, B., Chen, Y., & Zhang, X. (2020). The impact of AI-powered personalization on tourist experiences: A review of literature. Tourism Management, 79, 104064.
  • Philip L. Pearce, Mao-Ying Wu, Manuela De Carlo, Andrea Rossi “Contemporary experiences of Chinese tourists in Italy: An on-site analysis in Milan” nella rivista internazionale “Tourism Management Perspectives” 7 (2013) 34–37, Ed. Elsevier ltd (retrieved from https://www.academia.edu/4027130/Contemporary_experiences_of_Chinese_tourists_in_Italy)
  • Petar. (2023). The Future of AI in Tourism: Analyzing the Potential for Personalization and Experience Enhancement. Medium. Retrieved from https://medium.com/@peco4312/the-future-of-ai-in-tourism-analyzing-the-potential-for-personalization-and-experience-enhancement-b676e7ac58a8?source=rss——-1
  • PR Newswire. (2023). Global Artificial Intelligence (AI) in Travel and Tourism Intelligence Report 2023: AI-Driven Technologies Disrupting Travel, Enhancing Efficiency and Personalization. Retrieved from https://www.prnewswire.com/news-releases/global-artificial-intelligence-ai-in-travel-and-tourism-intelligence-report-2023-ai-driven-technologies-disrupting-travel-enhancing-efficiency-and-personalization-301891840.html
  • Ramzan, B., Bajwa, I.S., Jamil, N., & Mirza, F. (2019). An Intelligent Data Analysis for Hotel Recommendation Systems using Machine Learning. ArXiv, abs/1910.06669.
  • Research and Markets (2023). Global Artificial Intelligence (AI) in Travel and Tourism Intelligence Report 2023: AI-Driven Technologies Disrupting Travel, Enhancing Efficiency and Personalization. Retrieved from https://www.prnewswire.com/news-releases/global-artificial-intelligence-ai-in-travel-and-tourism-intelligence-report-2023-ai-driven-technologies-disrupting-travel-enhancing-efficiency-and-personalization-301891840.html
  • Revfine. (2023). 13 Key Technology Trends Emerging in the Travel & Tourism Industry. Retrieved from https://www.revfine.com/technology-trends-travel-industry/
  • Roh, S., Park, D., & Kim, J. (2020). The role of AI-powered personalization in tourism: A case study of a major South Korean travel agency. Journal of Travel Research, 59(2), 270-284.
  • Rossi Andrea (2020) “La comunicazione del turismo ai tempi del coronavirus” inserito nel fascicolo monografico del “Semestrale di studi e ricerche di Geografia”, dedicato all’impatto socio-territoriale della pandemia, “Epidemia, spazio e società. Idee e analisi per il dibattito e le politiche pubbliche” a cura di Angelo Turco, ISSN 1125-5218, pp. 57-71, XXXII, Fascicolo 2, luglio-dicembre 2020 (retrieved from https://www.semestrale-geografia.uniroma1.it/index.php/semestrale-geografia/article/view/17032/16354)
  • Rossi Andrea (2022), “Comunicazione Digitale per il Turismo”, Self-Publishing, Vercelli, 2022 – ISBN 9791221004175
  • Rossi Andrea (2023). “Il Buono, il Brutto e il Cattivo: Il “Triello” Del Metaverso”. Documenti geografici, 0(2), 673-678. doi:http://dx.doi.org/10.19246/DOCUGEO2281-7549/202302_47 (retrieved from https://www.documentigeografici.it/index.php/docugeo/article/view/478)
  • Rossi Andrea, Goetz Maurizio (2011) “Creare offerte turistiche vincenti con Tourist Experience Design”, ed. Hoepli, Milano, 2011
  • Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Pearson.
  • Saha, T. (2019). AI is Reimagining Travel Personalisation. Towards Data Science. Retrieved from https://towardsdatascience.com/ai-is-reimagining-travel-personalisation-c72685faa378
  • Samara, E., Tsimitakis, E., & Vasilakis, C. (2020). Artificial intelligence (AI) applied in Tourism: A Bibliometric review. In Proceedings of the 2nd International Conference on Tourism Research (pp. 1-10).
  • Stylos, N., Vassiliadis, C. A., Bellou, V., & Andronikidis, A. (2021). Destination images, holistic images and personal normative beliefs: Predictors of intention to revisit a destination. Tourism Management, 31(5), 525-545.
  • TheNextWeb. (2023). 3 tech trends that will revolutionize the travel industry in 2023. Retrieved from https://thenextweb.com/news/3-tech-trends-travel-industry-2023
  • Wang, Y., & Li, S. (2020). The impact of AI-powered personalization on tourist satisfaction: A case study of a Chinese travel website. International Journal of Tourism Research, 22(5), 721-732.
  • Xiang, Z., & Gretzel, U. (2019). Artificial intelligence in tourism: A review of recent research. Tourism Management, 70, 304-326.
  • Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2017). A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism. Tourism Management, 58, 51-65.
  • Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2020). A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism. Tourism Management, 77, 104041.
  • Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2022). Artificial intelligence in tourism and hospitality: Bibliometric analysis and research agenda. Journal of Hospitality and Tourism Technology, 13(1), 1-20.
  • Yue, X., Li, X., & Li, Y. (2021). The future of tourism experience: A review of AI technology. Journal of Hospitality and Tourism Technology, 12(2), 244-259.