Image generated by DALL-E, OpenAI’s AI-powered art generator.
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This is blog 4 of 6 in the series ‘Do Smart Destinations Dream of Electric AI Tourist Experiences?’. Dive into the intricacies of practical application as we unveil how ExplorAI revolutionizes the journey of modern travelers. This chapter focuses on how ExplorAI leverages user-centric design, to offer a seamless, adaptive, and enriching travel experience. In presenting this project idea, my goal is to collaborate with public administrations, associations of tourism operators, and ICT companies to bring this vision to reality.
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As we progress into Chapter 4 of our comprehensive exploration into the ExplorAI platform, we transition from its innovative applications to the practical, hands-on experience of using ExplorAI. This chapter is dedicated to unraveling how tourists and destinations alike can navigate and maximize the benefits of the ExplorAI system. We will delve into the user-friendly interface of ExplorAI, its adaptability to various traveler needs, and its impact on enhancing the overall travel experience. From the meticulous planning before a trip to real-time assistance during the journey, and the insightful data it offers to destinations, Chapter 4 provides a holistic view of how ExplorAI integrates seamlessly into the fabric of modern travel. Join us as we journey through the many layers of ExplorAI, showcasing how it transforms not just travel, but the way we connect with the world around us.
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3. Using the ExplorAI Platform
In the digital age, ease of use and accessibility are crucial to ensure user adoption and satisfaction. The ExplorAI platform was not only designed with cutting-edge technologies but also with the user at the center of its architecture. This means that whether you are planning your trip from home or exploring a destination in real-time, ExplorAI is there to guide you, inform you, and enrich your experience at every stage of your journey. But how exactly does this usage work? And how does ExplorAI adapt to the different needs of tourists and destinations?
ExplorAI Usage Overview
The ExplorAI platform was designed to be a digital travel companion, always present and always available, to meet the needs of tourists at every stage of their journey.
Before the Trip: ExplorAI offers personalized planning tools, where Artificial Intelligence and Virtual Reality play a key role. You can discover the destination through virtual tours, plan custom itineraries based on your preferences, and receive dynamic suggestions.
During the Stay: Once at the destination, ExplorAI becomes your personal assistant. AI provides dynamic updates based on current conditions, while Geolocated Augmented Reality provides assisted navigation and contextual information. In addition, the integrated payment system facilitates all your transactions, making the travel experience seamless.
Benefits for the Territory: ExplorAI is not just a tool for tourists. The data collected by the platform offers valuable insights to the area, helping local authorities monitor tourist flows, assess economic impact, and plan effective tourism strategies.
In summary, ExplorAI is a holistic solution that synergizes advanced digital technologies, data analysis, and user experience, ensuring optimal usage both for tourists and destinations.
In Fig. 2 you can see the ExplorAI Usage and Tools
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Fig. 2 – ExplorAI Usage and Tools (Author: Andrea Rossi)
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3.1 Using ExplorAI Before the Trip
The planning phase is crucial for any trip. With ExplorAI, this phase becomes not only simpler but also more immersive and personalized.
Designing Customized Programs with Artificial Intelligence:
Preference Analysis: Based on your previous interactions, searches, and feedback, ExplorAI analyzes and understands your preferences to suggest activities and places that reflect your interests.
Creation of Custom Itineraries: Once your preferences are understood, the platform generates personalized itineraries, optimizing the route, timings, and activities based on the duration of your stay and your priorities.
Dynamic Suggestions: ExplorAI offers dynamic advice, showing you special events, seasonal offers, or new attractions that might interest you, based on the timing of your trip.
Experience Preview with Virtual Reality:
Virtual Tours: Before deciding which places to visit, you can “walk” virtually through museums, historical sites, natural parks, and other attractions, getting a clear idea of what awaits you.
Immersive Interaction: During these virtual tours, you can interact with elements, receiving additional information, listening to anecdotes, or viewing videos and photos.
Integration with AI: Virtual Reality and Artificial Intelligence work together to make virtual previews in line with your preferences, particularly highlighting aspects or places that might interest you the most.
In short, the planning phase with ExplorAI becomes an engaging and tailor-made experience, ensuring that you arrive at your destination with a clear vision of what you want to do and see.
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In the next post, I will delve deeper into the on-site functionalities of ExplorAI. This includes dynamic program updates, immersive AR support, and how ExplorAI adapts to evolving needs once the traveler has reached their destination, ensuring that every moment is optimized and enriching. The chapter will also cover the platform’s innovative approach to managing payments and vouchers, enhancing the convenience and security of financial transactions during travel. Finally, we will explore the benefits of ExplorAI for the territory, including monitoring tourist flows and enabling sustainable management of tourist destinations. Stay tuned for a deep dive into the practical, real-time applications of ExplorAI that make every travel experience more intuitive, engaging, and memorable.
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Previous posts:
ExplorAI: Ushering in a New Era of Smart Tourism – Part 1 of 6
http://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttp://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.pngAndrea2023-11-28 08:21:362023-11-28 08:22:23Mastering the Journey – Harnessing the Power of ExplorAI in Travel – Part 4 of 6
Smiling robot assistant with artificial intelligence By yanaiskayeva
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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”.
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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:
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).
Generative AI: Technologies like GANs are crafting content and experiences, from virtual destination tours to tailored itineraries (TheNextWeb, 2023).
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).
Voice Tech: Voice search and control are gaining traction, simplifying trip planning and execution (Revfine, 2023).
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.
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)
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.
http://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttp://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.pngAndrea2023-10-24 07:23:022023-10-24 07:22:14AI’s Horizon in Tourism: Future Trends and Transformations – Part 7 of 8
A man chats with artificial intelligence from his smartphone By AndersonPiza
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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”.
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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.
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.
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.
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.
Frictionless Payments: The tech facilitates swift, seamless payments, enabling experiences like automatic restaurant billing or staff-free check-outs.
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.
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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.
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)
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.
http://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttp://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.pngAndrea2023-10-17 07:17:212023-10-17 07:17:22AI in Tourism: Facial Recognition and Beyond – Part 6 of 8
Circuit board and AI micro processor by By MegiasD
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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”.
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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.
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)
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.
http://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttp://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.pngAndrea2023-10-10 07:39:102023-10-10 07:39:10AI in Tourism: Case Studies on ChatGPT and Amazon Web Services – Part 5 of 8
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”.
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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.
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)
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.
http://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttp://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.pngAndrea2023-10-02 15:03:412023-10-02 15:03:42Revolutionizing Tourism with AI: Case Studies on Hotel Recommendations and Smart City Experiences – Part 4 of 8
artificial intelligence (ai) and machine learning (ml) By MEFTAHYs-PROTOTYPE
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This is Part 3 of a 8-blog posts series “Exploring the Intersection of Artificial Intelligence and Tourist Experiences: Insights into AI-Driven Customization and Its Impact on Tourism”.
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2. AI-Powered Personalization: Shaping the Future of Tourist Experiences
2.1 Delving into Literature: AI’s Transformative Impact on Tourism
The integration of Artificial Intelligence (AI) into the tourism sector is gaining momentum, with a pronounced emphasis on personalization to elevate tourist experiences. This section delves into contemporary literature and studies that shed light on the profound impact of AI-driven personalization in the realm of tourism. 30 valuable articles on artificial intelligence and tourism have been summarized.
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Buhalis (2020): His perspective on the technological evolution in tourism emphasizes AI’s role in this journey.
Buhalis & Leung (2020): Their paper delves into the concept of smart hospitality.
Buhalis and Moldavska (2022): Their insights into smart tourism highlight the role of AI-powered personalization in enhancing the competitive edge of tourism entities.
Chan and Guillet (2018): Their investigation into Hong Kong’s hotel industry’s social media marketing strategies revealed the game-changing potential of AI-powered personalization.
Chen, Y., Xu, Z., & Gretzel, U. (2020): Their field experiment uncovers the profound impact of AI-powered personalization on tourist satisfaction.
Chunduri, P. K. (2020): His paper examines the effects of personalized AI and robot applications on customer service in tourism.
Dataconomy (2023): The article spotlights advanced AI technologies like deep learning and natural language processing. Major players like Amazon are leveraging generative AI to offer hyper-personalized customer service in travel.
Dunne (2022): His Forbes article delves into the future of personalization in travel, emphasizing AI’s pivotal role.
Goodfellow, Bengio, and Courville (2016): Their book “Deep Learning” delves into the potential of AI and machine learning across sectors, including tourism.
Gretzel, U., Sigala, M., Xiang, Z., & Koo, C. (2018): Their book offers a comprehensive overview of smart tourism.
Gursoy, Chi, Lu, and Nunkoo (2019): Their exploration into travelers’ information-seeking behavior in the AI context reveals the significant influence of AI-driven personalization on travel experiences.
Inanc-Demir and Kozak (2019): In their book “Tourism in the City”, they spotlight AI’s transformative role in tourism, emphasizing its potential to personalize and elevate tourist experiences.
Kong, Wang, and Fu (2022): Their insights into the current state and future trajectory of AI in tourism underscore its pivotal role in enhancing tourist experiences and propelling the industry’s growth.
Leung (2020): His conceptual model for smart tourism research, viewed through a sustainability lens, emphasizes AI’s potential in promoting sustainable tourism practices.
Li et al. (2020): Their research on AI’s role in personalized travel recommendation systems underscores the capability of AI to sift through vast data troves, discerning individual preferences. The outcome? Enhanced travel experiences and a boost in customer engagement and revenue for tourism enterprises.
Li, Wang, Liang, and Huang (2020): Their paper on China’s smart tourism initiative underscores the role of AI in enhancing personalization in smart tourism destinations.
Lv, Song, Basiri, Jackson, and Kitchin (2022): Their insights into the future of recommender systems in tourism highlight AI’s role in amplifying the efficacy of these systems.
McCartney and McCartney (2020): Their discourse on AI’s impact on tourism’s future underscores its transformative potential in personalization.
Pang, Chen, and Zhang (2020): Their literature review emphasizes AI’s transformative potential in enhancing tourist experiences through tailored recommendations.
Petar (2023): His Medium article offers a glimpse into the future of AI in tourism.
PR Newswire (2023): The report accentuates the disruptive potential of AI in travel, emphasizing its prowess in crafting personalized routes, activities, and brand interactions. Such intricate personalization is reshaping the tourism landscape, driving customer satisfaction and business growth.
Roh, Park, and Kim (2020): Through a case study of a leading South Korean travel agency, the research reveals that AI-driven personalization boosts customer satisfaction and engagement, translating to increased revenue.
Russell and Norvig (2020): Their book “Artificial Intelligence: A Modern Approach” offers insights into AI’s potential across sectors, including tourism.
Saha (2019): His article sheds light on AI’s role in reimagining travel personalization.
Samara, Tsimitakis, & Vasilakis (2020): Their bibliometric review offers insights into AI’s applications in tourism.
Stylos, Vassiliadis, Bellou, and Andronikidis (2021): Their exploration into the factors influencing tourists’ intention to revisit a destination reveals the significant role of AI-powered personalization.
Wang and Li (2020): Their case study on a Chinese travel website showcases the profound impact of AI-driven personalization on tourist satisfaction.
Xiang & Gretzel (2019): Their paper provides a comprehensive review of AI’s applications in tourism.
Xiang, Du, Ma, & Fan (2017): Their comparative analysis of online review platforms highlights the efficacy of AI-driven personalization in offering tailored recommendations.
Xiang, Du, Ma, & Fan (2022): Their bibliometric analysis offers a deep dive into AI research in tourism and hospitality.
Yue, X., Li, X., & Li, Y. (2021): Their paper discusses the future of tourism experiences in the AI context.
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In wrapping up, the vast body of literature and studies reviewed here paints a clear picture: AI-powered personalization is not just enhancing tourist experiences—it’s redefining them. As AI continues its rapid evolution, the tourism industry stands on the cusp of even more groundbreaking innovations.
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)
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.
http://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttp://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.pngAndrea2023-09-26 06:52:012023-09-26 06:58:59AI’s Role in Crafting Personalized Tourist Experiences: A Literature Review – Part 3 of 8
artificial intelligence (ai) and machine learning (ml) By MEFTAHYs-PROTOTYPE
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This is Part 2 of a 8-blog posts series “Exploring the Intersection of Artificial Intelligence and Tourist Experiences: Insights into AI-Driven Customization and Its Impact on Tourism”.
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1.3 The AI-Driven Evolution of Personalized Tourist Experiences
The tourism industry is witnessing a paradigm shift towards personalization, a pivotal element in amplifying the tourist experience. Personalization, at its core, is the art of tailoring services and offerings to resonate with the unique preferences of each traveler. This can manifest in myriad ways, from curated travel recommendations to bespoke travel packages. A striking insight from Smart Insights reveals that a staggering 63% of customers might disengage from brands that falter in personalization (Dunne, 2022).
Every traveler is a unique entity, characterized by distinct preferences, interests, and aspirations. Personalization in tourism is the bridge to these individual nuances, enhancing the overall experience and bolstering customer satisfaction. The ripple effect of effective personalization is evident in heightened customer loyalty, with travelers more inclined towards providers that resonate with their needs (Li et al., 2020).
Artificial Intelligence (AI) emerges as the linchpin in this personalization journey. AI’s prowess in sifting through vast data troves enables it to discern individual behaviors and preferences, paving the way for tailored offerings. For instance, AI-driven recommendation engines can curate travel suggestions rooted in a tourist’s historical data, online interactions, and inclinations, streamlining the booking process and elevating the overall experience (Dunne, 2022).
AI’s capabilities extend beyond mere recommendations. It can craft detailed tourist profiles, offering pinpointed suggestions for attractions, activities, and events. By harnessing data-driven insights, AI can anticipate attractions or experiences a traveler might gravitate towards, enabling providers to curate tailored suggestions (Li et al., 2020).
However, the realm of personalization transcends recommendations. McKinsey’s research underscores an evolving ecosystem where personalization permeates every facet of a traveler’s journey. This encompasses not just the hotel stay but extends to dining choices, entertainment venues, and even souvenir shopping, crafting a holistic, tailored experience (Dunne, 2022).
AI’s capabilities are further accentuated in deciphering unique customer journeys. The traditional linear travel journey has evolved into a dynamic, multi-faceted experience. AI stands as the beacon, understanding these intricate journeys and curating services in tandem (Saha, 2019).
The tangible impacts of AI are already evident. Smart hotels, for instance, leverage AI-driven chatbots and voice assistants to offer guests a seamless, personalized experience, from room service requests to dining reservations (Petar, 2023).
In summation, the synergy of AI and personalization is redefining the tourism landscape. By harnessing data-driven insights, AI crafts bespoke experiences, enhancing satisfaction and fostering loyalty.
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1.4 Charting the Course: Objectives and Research Queries
This blog posts series embarks on a journey to unravel the confluence of Artificial Intelligence (AI) and tourist experiences, with a spotlight on AI’s role in personalization. The driving force behind this exploration is AI’s transformative potential and the escalating significance of personalization in tourism (Buhalis, 2020; McCartney & McCartney, 2020).
To navigate this exploration, the paper poses pivotal research queries:
How is AI sculpting personalized tourist experiences across global destinations?
What ripple effects does AI-driven personalization have on travelers, service providers, and destination management entities?
What future trajectories can we anticipate in AI-driven personalization, and how might these shape tourist experiences?
These queries are rooted in contemporary academic discourse on AI in tourism. Studies like those by Inanc-Demir & Kozak (2019) and Kong et al. (2022) offer insights into AI’s transformative role in tourism. Additionally, Dwivedi et al. (2023) shed light on AI’s overarching impacts across sectors, including tourism.
This blog posts series aspires to augment this academic narrative, offering a holistic view of AI-driven personalization in tourism and its ramifications on the tourist experience.
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)
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.
http://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttp://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.pngAndrea2023-09-18 15:37:312023-09-18 15:46:25AI-Powered Personalization: Elevating Tourist Experiences – Part 2 of 8
A person interacts with artificial intelligence By AndersonPiza
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This is Part 1 of a 8-blog posts series “Exploring the Intersection of Artificial Intelligence and Tourist Experiences: Insights into AI-Driven Customization and Its Impact on Tourism”.
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1. Introduction to AI’s Transformative Role in Tourism
1.1. A Glimpse into AI and its Expanding Horizons
Artificial Intelligence (AI) stands as a beacon of transformation across diverse sectors, with its applications ever-evolving. Within the tourism landscape, AI promises to redefine our travel experiences, spanning from tailored recommendations to the intelligent automation of myriad services.
At its essence, AI is a computer science domain dedicated to crafting systems adept at tasks typically necessitating human intellect. Such tasks encompass learning from new data, comprehending human language, pattern recognition, and decision-making. AI branches into two primary categories:
Narrow AI: Tailored for specific tasks like voice recognition.
General AI: Capable of any intellectual endeavor a human can undertake (Russell & Norvig, 2020).
Machine learning, a notable AI subset, revolves around crafting algorithms enabling computers to learn and decide based on data. A deeper dive into machine learning reveals deep learning, which employs multi-layered neural networks to decipher intricate data patterns. Such methodologies have found applications across sectors, achieving commendable outcomes (Goodfellow, Bengio, & Courville, 2016).
In tourism, AI’s prowess manifests in enhanced personalization, elevated customer service standards, and streamlined operations. For instance, AI-driven recommendation engines can curate travel suggestions tailored to a tourist’s preferences, amplifying the overall experience (Li, Wang, Liang, & Huang, 2020). Furthermore, AI’s automation capabilities, as seen in chatbots, offer real-time customer responses, leading to operational cost reductions (Gursoy, Chi, Lu, & Nunkoo, 2019).
Additionally, AI’s optimization capabilities have been harnessed in tourism. Predictive analytics powered by AI can forecast tourist demand, allowing businesses to refine their resources and offerings (Li, Law, Vu, Rong, & Zhao, 2018). AI’s prowess in analyzing online sentiments offers insights into customer preferences (Xiang, Du, Ma, & Fan, 2017).
In summation, AI’s potential in reshaping the tourism sector is undeniable. As it continues its evolutionary journey, its role in curating bespoke tourist experiences will only magnify.
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1.2. AI’s Growing Footprint in Tourism
The tourism industry is witnessing a paradigm shift, with AI emerging as a pivotal transformative agent. As elucidated by McCartney and McCartney (2020), AI encapsulates technologies proficient in emulating advanced human intelligence facets during problem-solving. With tourism undergoing a digital metamorphosis (Buhalis, 2020), AI’s initial imprints are discernible across the sector’s spectrum (Kong et al., 2022).
AI’s influence is evident in both operational and marketing facets of tourist destinations (Inanc-Demir & Kozak, 2019). From personalization engines and robots to forecasting systems and smart travel assistants, AI’s capabilities are vast. Its disruptive potential is already reshaping the industry’s core (Buhalis et al., 2019; Buhalis & Moldavska, 2022; Leung, 2020).
McCartney and McCartney’s (2020) research accentuates AI’s transformative potential in tourism. They advocate for AI’s capabilities in bolstering operational efficiency, refining customer service, and driving profitability. For instance, AI-empowered chatbots can offer round-the-clock interactive customer service, catering to guest queries, curating personalized recommendations, and even facilitating simple bookings. This not only elevates customer service standards but also trims response times, fostering guest loyalty and satisfaction.
Furthermore, AI’s analytical depth offers immense potential in hotel marketing. For example, AI can meticulously dissect customer data, segmenting users based on past behaviors, preferences, or demographics. This aids hotels in fine-tuning their marketing strategies, fostering customer engagement and loyalty (Lv et al., 2022).
However, the AI integration journey isn’t devoid of challenges. These encompass the quest for pristine data, the intricacies of harmonizing AI systems with human roles, and the hotel sector’s historical hesitance towards novel technologies (Chan et al., 2018; Stylos et al., 2021).
In conclusion, AI’s transformative potential for the tourism sector is monumental. By refining operational efficiency, elevating customer service, and enabling profound analytical insights, AI is poised to redefine the tourism industry’s interactions with its clientele.
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)
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.
http://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttp://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.pngAndrea2023-09-12 06:37:332023-09-14 15:49:29AI in Tourism: Revolutionizing Personalized Experiences and Operational Efficiency – Part 1 of 8
Key Performance Indicators (KPIs) are used by organizations of all sizes to measure their marketing or business results. KPIs are measurable values that business decision-makers use to evaluate the success of the company. In the context of digital communication, there are specific KPIs to monitor the effectiveness of the actions outlined in the communication plan and to improve areas where results fall below expectations. For instance, the most common KPIs in Social Media Marketing include likes, followers, comments, and shares, but this is by no means an exhaustive list. The list of KPIs, if it were to encompass all possibilities, would exceed hundreds of items because each organization determines its own set of KPIs. Having too many KPIs does not lead to better control of communication but rather makes it difficult, if not impossible, to read performance reports. It is crucial to find the right number of KPIs that only provide measurements of the parameters that matter. As a general guideline, having 20-30 KPIs can be sufficient to keep the situation under control. According to Karola Karlson from scoro.com [Karlson K., 2022], KPIs for digital communication can be divided into five main categories:
Lead generation
Website & traffic metrics
SEO optimization
Paid advertising
Social media tracking
Karola Karlson identifies 37 possible KPIs to use within these five categories. Here are some examples.
Lead generation:
Monthly new leads/prospects
Qualified leads per month
Cost-per-lead generated
Cost per conversion
Average time of conversion
Retention rate
Attrition rate
Net promoter score
Website & traffic metrics:
Returning vs. new visitors
Visits per channel
Average time on page
Website conversion rate
The conversion rate for call-to-action content
Click-through rate (CTR) on web pages
Pages per visit
SEO optimization:
Inbound links to a website
Traffic from organic search
New leads from organic search
Conversions from organic search
Page authority
Google PageRank
Keywords in the top 10 SERP
Rank increase of target keywords
Conversion rate per keyword
Number of unique keywords that drive traffic
Volume of traffic from video content
Paid advertising:
Leads & conversions from paid advertising
Cost per acquisition (CPA) & cost per conversion
Click-through rate on PPC advertising
Social media tracking:
Traffic from social media
Leads and conversions from social media
Conversion rate
Managed audience size
Engagement rate
Mentions
Social media ROI
These 37 KPIs provided by Karola Kalrson are examples, and each organization will need to decide which KPIs are relevant to their specific case. Some of the KPIs on this list are easily understood, while others may be more complex.
http://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttp://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.pngAndrea2023-07-24 06:49:192023-07-24 06:49:20The Digital Communication Plan for Tourism – Part XII: Measurements of the digital communication plan
The digital communication plan is a strategic document that requires careful planning and precise management to achieve positive results. Not only does it define the actions to be taken over time, but it also fulfills a crucial role in honoring the commitment to the destination’s stakeholders by adhering to a specific course of action..
However, it is important to note that the editorial plan must be executed punctually unless unexpected events occur that, depending on their severity, may require partial or total revision of the plan. For example, the recent Covid-19 pandemic has forced many to rethink and adapt previously defined plans.
Regardless of the circumstances, the fundamental principles of good project management applied to digital communication include a precise understanding of timing, costs, and expected quality, as well as the flexibility to make changes during the implementation of the plan. It is also essential to periodically evaluate the results achieved in order to make necessary adjustments and improvements.
Following the planning flow described in this series of posts provides a solid foundation for optimally managing digital communication activities. However, it is important to emphasize that the success of the plan will also depend on adaptability and responsiveness to the changing dynamics of the digital context. Maintaining constant attention to trends, new opportunities, and stakeholder needs is essential to maximize the overall impact and effectiveness of the digital communication plan.
http://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttp://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.pngAndrea2023-07-17 06:43:042023-07-17 06:42:12The Digital Communication Plan for Tourism – Part XI: Actions for maximizing impact and effectiveness
