Image generated by DALL-E, OpenAI’s AI-powered art generator.
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This is blog post 3 of 6 in the series ‘Do Smart Destinations Dream of Electric AI Tourist Experiences?’. Join me as we delve into the future of smart destinations, powered by the groundbreaking ExplorAI platform and Artificial Intelligence. Discover how tourism is being reimagined to offer personalized, sustainable, and technologically advanced experiences to travelers worldwide. In presenting this project idea of mine, 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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In the third chapter of our series on ExplorAI, we explore its innovative applications in the tourism industry, focusing on three key areas: Geolocated Augmented Reality, Virtual Reality, and Integrated Payment Systems. This chapter delves into how these technologies transform tourist experiences by offering intuitive navigation, immersive storytelling, personalized tours, secure transactions, and much more. We’ll demonstrate how each feature, from AR’s enriched real-world exploration to VR’s immersive pre-travel previews and the streamlined payment system, collectively curate a travel experience as unique as each tourist’s fingerprint.
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Fig. 1 – ExplorAI Platform Elements (Author: Andrea Rossi)
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2.3. Geolocated Augmented Reality in ExplorAI
In the world of tourism, discovering new places and appreciating hidden beauties is at the heart of the experience. With Geolocated Augmented Reality, ExplorAI takes this discovery to a whole new level, enriching the real world with digital information for a truly immersive tourist experience.
Intuitive Navigation: With Augmented Reality, tourists can simply point their device at a place of interest to receive detailed information. Whether it’s a historic building, a monument, or a natural landscape, ExplorAI provides contextual details directly on the screen.
Stories and Anecdotes: Beyond simple information, Augmented Reality can also tell stories. Imagine walking through an archaeological site and seeing scenes from the past play out before your eyes, or hearing fascinating anecdotes about a work of art in a museum.
Multimedia Interactions: Photos, videos, animations, and sounds: Geolocated Augmented Reality offers a range of multimedia content that enriches the experience, making each visit unique and memorable.
Customized Routes: Based on preferences and the profile of the tourist, ExplorAI can suggest tailor-made routes, guiding visitors through a series of points of interest enhanced by Augmented Reality.
Interactivity and Engagement: Tourists can interact with Augmented Reality elements, answering quizzes, participating in games, or providing feedback, making the experience not only informative but also interactive and engaging.
In summary, Geolocated Augmented Reality in ExplorAI transforms every destination into an open book, where each page is enriched by digital content that brings the history, culture, and beauty of the place directly into the hands of tourists.
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2.4. Virtual Reality in ExplorAI
Virtual Reality (VR) has revolutionized the way we perceive and interact with the digital world. ExplorAI harnesses this cutting-edge technology to offer tourists an unprecedented travel experience, allowing them to fully immerse themselves in a destination even before setting foot on the ground.
Virtual Tours: Thanks to VR, tourists can “visit” museums, monuments, natural parks, and other attractions directly from the comfort of their home. These immersive previews help visitors better plan their trip and decide which places they want to explore in person.
Immersive Interaction: Virtual Reality is not just passive viewing: tourists can interact with the environment, obtain additional information on specific points of interest, participate in educational games, or even “walk” along virtual paths.
Integration with AI: Combining VR with ExplorAI’s Artificial Intelligence, virtual tours can be customized based on the tourist’s preferences and interests. For example, a history enthusiast might receive a virtual tour focused on historical sites, while a nature lover might virtually explore nature reserves and parks.
Preview of Events and Festivals: VR can also give tourists a taste of events, festivals, or shows taking place in the destination, allowing them to “experience” the atmosphere and decide whether to attend in person.
Training and Education: Virtual Reality can also have an educational role, offering virtual courses, lessons, and workshops on topics related to the destination, such as its history, culture, art, and traditions.
With Virtual Reality, ExplorAI adds an additional dimension to the tourist experience, blurring the boundary between the real world and the digital world and making every trip a rich and multidimensional adventure.
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2.5. Payment System, Vouchers, Integrated Tourist Card in ExplorAI
In a digital age, simple, secure, and fast transactions are essential for a seamless tourist experience. ExplorAI understands the importance of this aspect and integrates an advanced payment system, vouchers, and tourist cards to facilitate every economic aspect of the journey.
Facilitated Payments:
Single Platform: ExplorAI provides a one-stop solution for all travel-related payments, from booking accommodations and transport to purchasing tickets for attractions or events.
Flexible Payment Options: Whether it’s credit cards, digital payments, or other methods, the platform supports a wide range of options to meet the needs of every tourist.
Fast Transactions: With an intuitive interface and optimized processes, transactions are quick and hassle-free, allowing tourists to focus on enjoying their experience.
Voucher Management:
Digital Vouchers: Tourists can receive and manage digital vouchers directly on ExplorAI, eliminating the need to print or physically carry them.
Simplified Voucher Redemption: With a few taps, vouchers can be redeemed, making every interaction smooth and straightforward.
Personalization: Based on the tourist’s profile, the platform can offer personalized vouchers and deals, always guaranteeing the best value proposition.
Security and Protection:
Advanced Security Technology: All transactions on ExplorAI are protected by the best security technologies, ensuring the privacy and data protection of tourists.
Monitoring and Support: In case of issues or questions, a dedicated support system is always available to assist tourists and resolve any problems. With its integrated payment system, vouchers, and tourist cards, ExplorAI eliminates the complications related to transactions, allowing tourists to make the most of every moment of their trip without worries.
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Having journeyed through the immersive worlds of Augmented and Virtual Reality and Integrated Payment Systems, our next post will shift focus to the practicalities of travel. Join us as we continue to unveil the future of smart destinations with ExplorAI.
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Previous posts:
ExplorAI: Ushering in a New Era of Smart Tourism – Part 1 of 6
https://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttps://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.pngAndrea2023-11-21 09:16:432023-11-21 09:16:43ExplorAI: Revolutionizing Tourism with Augmented Reality, Virtual Reality, and Advanced Payment Systems – Part 3 of 6
Fig. 1 – ExplorAI Platform Elements (Author: Andrea Rossi)
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This is blog post 2 of 6 in the series ‘Do Smart Destinations Dream of Electric AI Tourist Experiences?’. Join me as we delve into the future of smart destinations, powered by the groundbreaking ExplorAI platform and Artificial Intelligence. Discover how tourism is being reimagined to offer personalized, sustainable, and technologically advanced experiences to travelers worldwide. In presenting this project idea of mine, 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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Image generated by DALL-E, OpenAI’s AI-powered art generator.
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This is blog 2 of 6 in the series ‘Do Smart Destinations Dream of Electric AI Tourist Experiences?’. We continue our exploration of the ExplorAI platform and its innovative components. From Artificial Intelligence to immersive technologies, discover how each element is transforming the tourism industry. In presenting this project idea of mine, my goal is to collaborate with public administrations, associations of tourism operators, and ICT companies to bring this vision to reality.
In the second installment of our series, we delve into the heart of ExplorAI. This post will illuminate the core components that make ExplorAI not just a platform, but a comprehensive ecosystem for the modern traveler. Join us as we explore how artificial intelligence and gamification are weaving together to curate unparalleled tourist experiences.
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2.1. Artificial Intelligence (AI) in ExplorAI
Artificial Intelligence is the backbone of ExplorAI, offering unprecedented learning and adaptation capabilities. But how does it work exactly, and how does it enhance the tourist experience?
Profiling Tourists: AI analyzes tourists’ preferences, searches, and interactions to create detailed profiles. This not only helps to better understand visitors’ needs but also allows anticipating their expectations, offering suggestions and proposals in line with their interests.
Online Prospecting and Assisted Creation of the Tourist Offer Map: Thanks to AI, ExplorAI can gather, categorize, and present the wide range of attractions and activities available in a destination, ensuring that every tourist finds something that meets their tastes.
Creation of Custom Routes and Programs: Based on tourists’ profiles, AI suggests customized itineraries and programs, guaranteeing a unique and personalized experience. Whether it’s a cultural visit, an adventure in nature, or a gastronomic tour, ExplorAI has the ideal solution.
Refinement and Continuous Learning of Tourist Profiles: Learning never stops. Every interaction, feedback, and choice of the tourist is used to further refine their profile, making the experience increasingly accurate and targeted over time.
Virtual Assistant and Co-Pilot of the On-Site Tourist Experience: With ExplorAI, tourists are never alone. The AI-powered virtual assistant provides real-time information, personalized advice, continuous updates, and support for reprogramming, making every trip a smooth and stress-free experience.
In summary, Artificial Intelligence in ExplorAI represents a breakthrough for modern tourism. It offers a tourist experience that not only satisfies but exceeds expectations, ensuring unforgettable memories and a lasting bond with the destination.
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2.2. Gamification in ExplorAI
In a world where engagement is key, gamification proves to be a winning strategy to engage and motivate tourists. ExplorAI integrates playful elements into its platform to make the tourist experience not only informative but also fun and rewarding.
Making Tourist Activities More Engaging:
Missions and Challenges: Tourists can participate in themed missions, such as “Discovering hidden treasures” or “The wandering gourmet,” earning points and recognitions for each challenge overcome.
Scores and Rankings: Each completed activity, each place visited, and each challenge overcome allows tourists to accumulate points and climb the rankings, adding an element of friendly competition.
Rewards and Incentives: Accumulating points isn’t just for glory; points can be exchanged for real rewards, such as discounts, priority access, or exclusive experiences.
Guide Tourists Towards Sustainable Choices:
Ecological Challenges: Tourists are encouraged to make eco-friendly choices, such as using public transport, participating in beach clean-ups, or visiting low environmental impact attractions.
Badges and Recognitions: Those who demonstrate a commitment to sustainability can earn special badges and recognitions, highlighting their commitment to responsible tourism.
Education Through Play: Gamification can also have an educational role, raising awareness among tourists about issues such as conservation, local history, and culture through interactive games and quizzes.
In essence, gamification in ExplorAI is not just a way to have fun, but represents an effective strategy to drive positive behaviors, promote sustainability, and ensure that tourists have deep and meaningful experiences during their journey.
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As we’ve uncovered the key elements of ExplorAI, our next post will guide you through the role of AI in creating bespoke tourist experiences. Stay tuned to learn how AI is not just enhancing, but personalizing the journey for every traveler.
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Previous post:
ExplorAI: Ushering in a New Era of Smart Tourism – Part 1 of 6
https://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttps://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.pngAndrea2023-11-14 07:56:082023-11-14 07:55:47Inside ExplorAI: The Components Redefining Travel Experiences – Part 2 of 6
Image generated by DALL-E, OpenAI’s AI-powered art generator.
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This is blog post 1 of 6 in the series ‘Do Smart Destinations Dream of Electric AI Tourist Experiences?’. Join me as we delve into the future of smart destinations, powered by the groundbreaking ExplorAI platform and Artificial Intelligence. Discover how tourism is being reimagined to offer personalized, sustainable, and technologically advanced experiences to travelers worldwide.In presenting this project idea of mine, 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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Welcome to the first installment of my six-part series where we embark on a journey to the forefront of tourism innovation. In this post, I introduce ExplorAI, a visionary platform preoject idea of mine that promises to redefine the tourism landscape. Merging cutting-edge technology with the inherent charm of travel destinations, ExplorAI aims to craft bespoke and enriching experiences for every traveler. Let’s explore how this pioneering platform is setting the stage for a new era in tourism.
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1. Introduction: ExplorAI – The Dawn of a New Era in Tourism
Tourism, always a pillar of cultural interactions and local economies, now stands at the crossroads between tradition and innovation. As tourist destinations around the world seek to adapt to the ever-evolving needs of modern travelers, there emerges a need for tools and platforms that can elevate and personalize the tourism experience.
This is where ExplorAI comes into play, offering a revolutionary vision of the future of tourism. Conceived as an advanced technological platform, based on Artificial Intelligence, for territorial valorization and the optimization of the tourist experience of destinations, ExplorAI represents a groundbreaking step towards modern, responsible, and highly personalized tourism.
This platform combines technological innovation with the essence and beauty of destinations, offering a tourist experience like never before. But ExplorAI is not just a technological product; it is a vision, a mission. 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. With ExplorAI, destinations have the opportunity to position themselves at the forefront of tourism innovation, ensuring a prosperous and sustainable future for the industry.
In presenting this project idea of mine, my goal is to collaborate with public administrations, associations of tourism operators, and ICT companies to bring this vision to reality. With ExplorAI, destinations can position themselves at the forefront of tourism innovation, ensuring a prosperous and sustainable future for the sector.
In this article, we will explore how ExplorAI aims to revolutionize the tourism sector, enhancing the territory, improving the traveler’s experience, and promoting sustainable development.
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2. ExplorAI Platform Elements
In an era where technology and innovation drive the traveler’s experience, it is crucial to be equipped with cutting-edge tools to meet the ever-growing expectations of modern tourists. “ExplorAI” is not merely a platform, but a technological ecosystem that integrates various advanced solutions, each designed to enhance and personalize the tourist experience at every stage. From Artificial Intelligence that learns and adapts to travelers’ needs, to gamification that makes every journey a unique adventure, to immersive experiences through Augmented and Virtual Reality, “ExplorAI” represents the perfect synthesis of innovation, technology, and tourism. In the following, the key elements that constitute the heart of this revolutionary platform will be explored in detail.
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ExplorAI Platform Elements: An Overview
Artificial Intelligence (AI): The beating heart of ExplorAI, AI profiles tourists, maps the tourist offering, creates personalized paths, and continually refines itself, offering a highly personalized and responsive tourist experience.
Gamification: By turning the tourist experience into a captivating game, gamification encourages tourist engagement, promotes sustainable behaviors, and makes every journey a unique adventure.
Geolocated Augmented Reality: Provides contextual information directly on the tourist’s mobile device, enriching the surrounding reality with historical, cultural, and practical details.
Virtual Reality: Offers an immersive preview of destinations, allowing tourists to “visit” places and attractions before deciding on their actual itinerary.
Integrated Payment System, Vouchers, Tourist Card: Facilitates transactions, making the tourist experience smoother and hassle-free, from purchasing tickets for attractions to managing vouchers and promotions.
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In Fig. 1 you can see the ExplorAI Platform Elements
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Fig. 1 – ExplorAI Platform Elements (Author: Andrea Rossi)
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Stay tuned for our next post in this series, where we will dive deeper into the elements that make up the ExplorAI platform. Discover how artificial intelligence, gamification, and immersive technologies come together to create a seamless and captivating tourist experience.
https://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttps://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.pngAndrea2023-11-07 09:21:412023-11-14 07:39:06ExplorAI: Ushering in a New Era of Smart Tourism – Part 1 of 6
This is Part 8 of a 8-blog posts series “Exploring the Intersection of Artificial Intelligence and Tourist Experiences: Insights into AI-Driven Customization and Its Impact on Tourism”.
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4.2 AI’s Transformative Role in Shaping Tourist Experiences
The confluence of AI and tourism is set to redefine the travel landscape, emphasizing personalization, convenience, and immersive virtual experiences.
Machine Learning’s Predictive Power:
Machine learning is revolutionizing how tourism businesses cater to their clientele. Companies like Amadeus are leveraging AI for solutions such as revenue management and merchandising (Amadeus, 2023). By anticipating tourist inclinations, businesses can craft bespoke experiences, fostering loyalty and satisfaction (Chen, Xu, & Gretzel, 2020).
Virtual Reality (VR) Tours:
VR tours offer a novel way for tourists to virtually traverse destinations, promoting locales and training tourism professionals (Gretzel, Sigala, Xiang, & Koo, 2018).
AI-Powered Travel Assistants:
Digital travel assistants, like chatbots, are streamlining travel planning, with Amadeus leading the charge in refining the travel journey (Amadeus, 2023).
Extended Reality (XR) and Generative AI:
XR is crafting immersive experiences for company retreats, while Generative AI is enhancing content and experiences in tourism (TheNextWeb, 2023).
AI-Human Synergy and Voice Tech:
AI’s collaboration with humans is enhancing decision-making and customer service. Concurrently, voice technologies and AI chatbots are simplifying interactions and providing round-the-clock service (Revfine, 2023).
In essence, AI’s integration, spearheaded by pioneers like Amadeus, is revolutionizing tourism operations and enhancing tourist experiences. These trends herald a transformative era for global tourism, emphasizing AI’s diverse applications and its potential for future innovations.
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5. Concluding Thoughts and Future Research Avenues
This series delved into AI’s intersection with tourism, emphasizing AI-driven personalization.
From an AI overview to its real-world applications in tourism, the series showcased AI’s potential to craft hyper-personalized, efficient, and seamless travel experiences.
The literature review and case studies underscored AI’s transformative role, from recommendation systems to facial recognition.
Emerging trends, from predictive analytics to voice services, highlighted AI’s expansive influence, with industry leaders like Amadeus at the forefront.
Yet, as AI’s footprint grows, a nuanced understanding of its ethical and societal ramifications is paramount.
Balancing AI’s prowess with human oversight is crucial, ensuring responsible and ethical applications.
Future research could delve into AI’s specific applications across tourism sectors, from hotel management to transportation.
Ethical considerations, like data privacy, warrant in-depth exploration.
A mix of case studies, surveys, and experimental designs could offer a holistic view of AI’s impact on tourism.
In summation, this series posits that AI, with its promise of personalization, will be pivotal for tourism’s future competitiveness. Far from replacing human touchpoints, AI augments them, promising a new era of hyper-personalized and enriched travel experiences.
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.
https://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttps://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.pngAndrea2023-10-31 09:00:522023-10-31 09:01:04AI in Tourism: The Future of Personalized Travel – Part 8 of 8
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.
https://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttps://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.
https://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttps://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.
https://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttps://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.
https://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttps://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.
https://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttps://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.
https://www.andrearossi.it/wp-content/uploads/2014/12/Andrea_Rossi_021-300x137.png00Andreahttps://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
