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

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.