AI in Tourism: The Future of Personalized Travel – Part 8 of 8

/0 Comments/in , , , , , , , , , , /by

Artificial intelligence by 9_fingers_

.

This is Part 8 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”.

.

4.2 AI’s Transformative Role in Shaping Tourist Experiences

The confluence of AI and tourism is set to redefine the travel landscape, emphasizing personalization, convenience, and immersive virtual experiences.

  • Machine Learning’s Predictive Power:

Machine learning is revolutionizing how tourism businesses cater to their clientele. Companies like Amadeus are leveraging AI for solutions such as revenue management and merchandising (Amadeus, 2023). By anticipating tourist inclinations, businesses can craft bespoke experiences, fostering loyalty and satisfaction (Chen, Xu, & Gretzel, 2020).

  • Virtual Reality (VR) Tours:

VR tours offer a novel way for tourists to virtually traverse destinations, promoting locales and training tourism professionals (Gretzel, Sigala, Xiang, & Koo, 2018).

  • AI-Powered Travel Assistants:

Digital travel assistants, like chatbots, are streamlining travel planning, with Amadeus leading the charge in refining the travel journey (Amadeus, 2023).

  • Extended Reality (XR) and Generative AI:

XR is crafting immersive experiences for company retreats, while Generative AI is enhancing content and experiences in tourism (TheNextWeb, 2023).

  • AI-Human Synergy and Voice Tech:

AI’s collaboration with humans is enhancing decision-making and customer service. Concurrently, voice technologies and AI chatbots are simplifying interactions and providing round-the-clock service (Revfine, 2023).

In essence, AI’s integration, spearheaded by pioneers like Amadeus, is revolutionizing tourism operations and enhancing tourist experiences. These trends herald a transformative era for global tourism, emphasizing AI’s diverse applications and its potential for future innovations.

.

5. Concluding Thoughts and Future Research Avenues

This series delved into AI’s intersection with tourism, emphasizing AI-driven personalization.

From an AI overview to its real-world applications in tourism, the series showcased AI’s potential to craft hyper-personalized, efficient, and seamless travel experiences.

The literature review and case studies underscored AI’s transformative role, from recommendation systems to facial recognition.

Emerging trends, from predictive analytics to voice services, highlighted AI’s expansive influence, with industry leaders like Amadeus at the forefront.

Yet, as AI’s footprint grows, a nuanced understanding of its ethical and societal ramifications is paramount.

Balancing AI’s prowess with human oversight is crucial, ensuring responsible and ethical applications.

Future research could delve into AI’s specific applications across tourism sectors, from hotel management to transportation.

Ethical considerations, like data privacy, warrant in-depth exploration.

A mix of case studies, surveys, and experimental designs could offer a holistic view of AI’s impact on tourism.

In summation, this series posits that AI, with its promise of personalization, will be pivotal for tourism’s future competitiveness. Far from replacing human touchpoints, AI augments them, promising a new era of hyper-personalized and enriched travel experiences.

.

Previous posts:

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

.

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

.

AI’s Role in Crafting Personalized Tourist Experiences: A Literature Review – Part 3 of 8:
https://www.andrearossi.it/en/ai-tourist-experiences-literature-review/

.

Revolutionizing Tourism with AI: Case Studies on Hotel Recommendations and Smart City Experiences – Part 4 of 8
https://www.andrearossi.it/en/tourism-ai-case-studies-hotel-smart-city-experiences/
.
AI in Tourism: Case Studies on ChatGPT and Amazon Web Services – Part 5 of 8
https://www.andrearossi.it/en/ai-in-tourism-case-studies-on-chatgpt-and-amazon-web-services/

.

AI in Tourism: Facial Recognition and Beyond – Part 6 of 8

https://www.andrearossi.it/en/ai-in-tourism-facial-recognition/

.

AI’s Horizon in Tourism: Future Trends and Transformations – Part 7 of 8

https://www.andrearossi.it/en/ai-tourism-future-trends/

.

#TourismTech #AIFuture #TravelTrends #VirtualTours #AIPersonalization #EthicalAI #TravelInnovation #DigitalDisruption #TourismResearch

.

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’s Horizon in Tourism: Future Trends and Transformations – Part 7 of 8

/0 Comments/in , , , , , , , , , , /by

Smiling robot assistant with artificial intelligence By yanaiskayeva

.

This is Part 7 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”.

.

4. AI’s New Dawn in Tourism: Trends and Transformations

The tourism landscape is undergoing a seismic shift, driven by the innovative integration of Artificial Intelligence (AI). As we look ahead, several pivotal trends promise to redefine the industry’s contours.

Machine Learning: The Crystal Ball of Tourism

Machine learning, an AI subset, is carving a niche in predictive analytics within tourism. By analyzing past data to discern patterns, these algorithms can predict future inclinations and behaviors. Leading the charge is Amadeus, integrating AI to bolster areas like revenue management, merchandising, and more (Amadeus, 2023). Such foresight enables businesses to craft data-informed strategies, offering tourists bespoke experiences. By predicting tourist inclinations—from favored destinations to spending habits—businesses can refine their offerings and bolster operational efficiency (Chen, Xu, & Gretzel, 2020).

Virtual Reality (VR) Tours: Travel Without Moving

VR tours are gaining traction, offering users a chance to traverse destinations without actual travel. This immersive technology can promote locales, train tourism professionals, and present a novel way for tourists to experience places (Gretzel, Sigala, Xiang, & Koo, 2018).

AI-Powered Travel Assistants: Your Digital Concierge

The rise of AI-driven travel assistants, manifesting as chatbots or conversational AI platforms, is undeniable. They aid tourists in tasks ranging from booking to travel advice. Amadeus’s focus encapsulates understanding travelers, predicting their behaviors, and refining the travel journey, aiming for a seamless experience (Amadeus, 2023).

Beyond the Obvious: AI’s Expanding Footprint

AI’s influence isn’t limited to the aforementioned trends. It’s enhancing customer service, fine-tuning pricing strategies, and bolstering risk management. As AI matures, its footprint in tourism is set to expand.

Other Noteworthy Trends:

  1. Extended Reality in Holidays and Retreats: XR, a blend of VR, AR, and MR, is making waves. It’s crafting immersive experiences for holidays and company retreats, letting participants virtually explore and bond (TheNextWeb, 2023).
  2. Generative AI: Technologies like GANs are crafting content and experiences, from virtual destination tours to tailored itineraries (TheNextWeb, 2023).
  3. AI-Human Synergy: A growing trend is the symbiotic relationship between AI and humans, with AI offering insights that human operators leverage (Forbes Advisor, 2023).
  4. Voice Tech: Voice search and control are gaining traction, simplifying trip planning and execution (Revfine, 2023).
  5. AI Chatbots for Customer Care: These digital assistants are enhancing customer service, answering queries, and aiding bookings (Revfine, 2023).

In summation, AI’s integration is elevating the tourist experience and redefining tourism operations. With trailblazers like Amadeus leading the way, the horizon looks promising, teeming with innovation and opportunities.

.

Previous posts:

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

.

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

.

AI’s Role in Crafting Personalized Tourist Experiences: A Literature Review – Part 3 of 8:
https://www.andrearossi.it/en/ai-tourist-experiences-literature-review/

.

Revolutionizing Tourism with AI: Case Studies on Hotel Recommendations and Smart City Experiences – Part 4 of 8
https://www.andrearossi.it/en/tourism-ai-case-studies-hotel-smart-city-experiences/
.
AI in Tourism: Case Studies on ChatGPT and Amazon Web Services – Part 5 of 8
https://www.andrearossi.it/en/ai-in-tourism-case-studies-on-chatgpt-and-amazon-web-services/

.

AI in Tourism: Facial Recognition and Beyond – Part 6 of 8

https://www.andrearossi.it/en/ai-in-tourism-facial-recognition/

.

#TourismTech #FutureOfTravel #AIEvolution #VirtualTours #AIPredictiveAnalytics #TravelAssistants #ExtendedReality #GenerativeAI #VoiceTech #AIChatbots

.

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: Facial Recognition and Beyond – Part 6 of 8

/0 Comments/in , , , , , , , , , /by

A man chats with artificial intelligence from his smartphone By AndersonPiza

.

This is Part 6 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”.

.

3.5 AI’s New Frontier in Tourism: Facial Recognition and Its Impacts

The fusion of Artificial Intelligence (AI) with the travel and tourism sector is ushering in an era of enhanced customer experiences and heightened security. Among the myriad AI innovations, facial recognition emerges as a game-changer. Drawing insights from Gupta et al.’s (2023) study, “The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry,” we delve into the transformative role of this technology.

  1. Introduction to the Tech: While facial recognition isn’t novel, its integration into travel and tourism is groundbreaking. The technology functions by identifying facial features, cross-referencing them with stored data for purposes ranging from identification to security.
  2. Personalization: AI-empowered facial recognition paves the way for tailored trip planning, efficient email and calendar integrations, and concise bill summaries. Recognizing returning customers, it can personalize services, such as adjusting room temperatures or suggesting meals based on past preferences.
  3. Security Enhancements: Widely adopted across industries, facial recognition in travel and tourism ensures heightened security. It’s instrumental at border checkpoints, airports, and hotels, verifying identities and streamlining access.
  4. Frictionless Payments: The tech facilitates swift, seamless payments, enabling experiences like automatic restaurant billing or staff-free check-outs.
  5. Eco-friendly Approach: By eliminating the need for paper-based boarding passes, facial recognition contributes to environmental sustainability.

However, the technology’s rise isn’t without challenges. Ethical and privacy concerns loom large, emphasizing the need for meticulous data handling to safeguard individual privacy and consent. Additionally, system accuracy remains a concern, with potential misidentifications posing risks.

Gupta et al.’s (2023) study enriches the tourism discourse, spotlighting AI-driven facial recognition’s role in amplifying value. Through in-depth interviews, the study identifies core themes, emphasizing the tech’s potential in tailoring services and enhancing security. This case underscores facial recognition’s transformative capacity in the industry, from personalization to security. Yet, it’s imperative to navigate ethical and privacy challenges responsibly.

.

Concluding, the five case studies in this segment illuminate AI’s profound impact on crafting personalized, immersive, and streamlined tourist experiences. From machine learning’s prowess in hotel recommendations to the synergy of deep learning and IoT, and the capabilities of models like ChatGPT, AI is redefining the tourism landscape. As showcased, while AI offers unparalleled advantages, it’s crucial to address ethical concerns and potential limitations. Continued research, emphasizing human-AI collaboration and specialized techniques for tourism, will be pivotal. With responsible evolution, AI stands ready to sculpt the future of tourist experiences.

.

Previous posts:

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

.

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

.

AI’s Role in Crafting Personalized Tourist Experiences: A Literature Review – Part 3 of 8:
https://www.andrearossi.it/en/ai-tourist-experiences-literature-review/

.

Revolutionizing Tourism with AI: Case Studies on Hotel Recommendations and Smart City Experiences – Part 4 of 8
https://www.andrearossi.it/en/tourism-ai-case-studies-hotel-smart-city-experiences/
.
AI in Tourism: Case Studies on ChatGPT and Amazon Web Services – Part 5 of 8
https://www.andrearossi.it/en/ai-in-tourism-case-studies-on-chatgpt-and-amazon-web-services/

.

#TourismTech #FacialRecognition #TravelInnovation #AIEthics #PersonalizedTravel #AISecurity #TravelTrends #FutureOfTourism #AIDrivenTourism #CaseStudies

.

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: Case Studies on ChatGPT and Amazon Web Services – Part 5 of 8

/0 Comments/in , , , , , , , , , /by

Circuit board and AI micro processor by By MegiasD

.

This is Part 5 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”.

.

3.3 ChatGPT: A Game-Changer for e-Tourism

The digital age has ushered in a new era for the tourism industry, with AI and conversational systems like ChatGPT leading the transformation. Drawing from the insights of Luisa Mich & Roberto Garigliano (Mich. L. et al., 2023), this case study delves into ChatGPT’s potential in e-tourism.

While traditional chatbots have their limitations, ChatGPT, developed by OpenAI, offers a fresh perspective. Its capabilities range from writing and translating to creating multimedia content. In e-tourism, its applications span from identifying new markets to innovating business processes.

Implementation Highlights:

  • Integration with existing databases and digital technologies.
  • Specialization for specific domains.
  • Leveraging OpenAI resources and other AI tools.
  • Developing new use cases for a competitive edge.

Results & Evaluation:

While ChatGPT’s integration in e-tourism is nascent, its potential is undeniable. Its human-like content creation capability offers avenues for innovation in tourism.

Challenges & Limitations:

  • Semantic understanding limitations.
  • Potential for inaccurate outputs.
  • Lack of transparency in results.
  • Ethical concerns.

In essence, ChatGPT’s role in e-tourism is transformative, offering unparalleled personalization and efficiency. However, its ethical and operational challenges necessitate careful implementation.

3.4 Amazon Web Services: Pioneering AI-Driven Hyper-Personalization in Travel

The travel industry is undergoing a seismic shift towards hyper-personalization, with AI as the catalyst. Amazon Web Services (AWS) is spearheading this change, partnering with major players in the travel sector.

AWS’s vision for AI in travel is clear: a revolution in hyper-personalized customer service. Their collaboration with Hyatt exemplifies this, resulting in a staggering $40 million revenue boost within half a year (Dawes, 2023).

The industry’s trajectory is towards abundant hyper-personalized content, tailored to individual customer data. Greg Land of AWS envisions this as the norm by year-end (Dawes, 2023).

However, the challenge lies in data quality. Many companies grapple with inconsistent data. AWS’s solution? A dedicated platform for hospitality companies to capture high-quality data (Dawes, 2023).

In conclusion, AWS’s foray into AI-driven hyper-personalization paints a promising picture for the future of travel. Their collaboration with the travel sector promises a new age of travel experiences, tailored to every individual’s unique preferences.

.

Previous posts:

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

.

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

.

AI’s Role in Crafting Personalized Tourist Experiences: A Literature Review – Part 3 of 8:
https://www.andrearossi.it/en/ai-tourist-experiences-literature-review/

.

Revolutionizing Tourism with AI: Case Studies on Hotel Recommendations and Smart City Experiences – Part 4 of 8

https://www.andrearossi.it/en/tourism-ai-case-studies-hotel-smart-city-experiences/

.

#TourismTech #ChatGPT #AmazonWebServices #AIinTourism #HyperPersonalization #eTourism #TravelInnovation #CaseStudies #DigitalTransformation #FutureOfTravel

.

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.

Revolutionizing Tourism with AI: Case Studies on Hotel Recommendations and Smart City Experiences – Part 4 of 8

/0 Comments/in , , , , , , , , , , , /by

AI By AndersonPiza

.

This is Part 4 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”.

.

3. AI-Driven Innovations in Tourism: A Deep Dive into Case Studies

This segment delves into the first two of five compelling case studies, showcasing the transformative power of cutting-edge AI in reshaping tourist experiences. From machine learning-enhanced hotel recommendations to the synergy of deep learning and IoT in smart cities, these cases spotlight the future of personalized, efficient, and seamless travel experiences.

3.1 Intelligent Hotel Recommendations: A Machine Learning Approach

The hospitality sector constantly seeks to refine personalization, ensuring guests receive the most relevant recommendations. Drawing from “An Intelligent Data Analysis for Hotel Recommendation Systems using Machine Learning” by Ramzan, B. et al. (2019), this case study highlights a groundbreaking solution to this challenge.

Traditional systems often falter with vast, varied data, leading to generic suggestions. The paper introduces a unique Collaborative Filtering (CF) recommendation method, integrating sentiment analysis to offer tailored hotel suggestions.

Solution Highlights:

  • Sentiment Analysis: Extracting insights from customer reviews to gauge preferences.
  • Guest Profiling: Segmenting guests for tailored recommendations.
  • Big Data Management: Leveraging the Hadoop platform for efficient data handling.
  • Fuzzy Rule-Based Classification: Classifying hotel types based on guest profiles.

Upon testing with real-world hotel website datasets, the system showcased superior performance, emphasizing the potential of machine learning in redefining hotel recommendation systems. This case underscores the significance of harnessing technologies like machine learning and big data in hospitality, heralding a new era of innovation and customer-centricity.

3.2 Smart Tourism: Merging Deep Learning and IoT for Enhanced Experiences

As smart cities evolve, the tourism sector grapples with delivering real-time, personalized experiences. This case study unveils a pioneering solution that marries deep learning and the Internet of Things (IoT) to redefine tourist attraction suggestions.

Traditional models often lack adaptability to real-time factors and individual preferences. Addressing this, researchers introduced a system that synergizes deep learning and IoT for dynamic tourist recommendations.

System Features:

  • Personalized Suggestions: Incorporating travel details, user data, and real-time context.
  • IoT Integration: Harnessing IoT devices for real-time data collection.
  • Deep Learning Classifier: Processing data to curate personalized recommendations.

Implementation Overview:

  • Data Collection: Gathering real-time data via IoT and user inputs.
  • Model Training: Equipping the deep learning model to process data and curate recommendations.
  • Real-time Functionality: Adapting to dynamic factors like location and weather.

The system’s performance, tested in pre-travel planning and in-city activity scenarios, surpassed traditional models. This fusion of deep learning and IoT marks a pivotal moment in smart tourism, enhancing tourist experiences and setting the stage for future innovations.

.

Previous posts:

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

.

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

.

AI’s Role in Crafting Personalized Tourist Experiences: A Literature Review – Part 3 of 8:
https://www.andrearossi.it/en/ai-tourist-experiences-literature-review/

.

#TourismTech #MachineLearning #DeepLearning #IoT #SmartTourism #HotelRecommendations #IntelligentSystems #TravelInnovation #CaseStudies #AIinTourism

.

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.