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

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

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

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

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

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

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

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

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Previous posts:

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

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

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

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REFERENCES

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

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

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

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

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1.3 The AI-Driven Evolution of Personalized Tourist Experiences

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

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

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

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

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

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

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

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

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1.4 Charting the Course: Objectives and Research Queries

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

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

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

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

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

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

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References

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

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

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A person interacts with artificial intelligence By AndersonPiza

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

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1. Introduction to AI’s Transformative Role in Tourism

1.1. A Glimpse into AI and its Expanding Horizons

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

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

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

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

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

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

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

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1.2. AI’s Growing Footprint in Tourism

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

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

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

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

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

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

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

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REFERENCES

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

Destination Marketing Strategies: Spotlighting the Intrinsic Value of Tourism Locations

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Ayers Rock in the Northern Territory of Australia. UNESCO World Heritage Site. By SteveAllenPhoto999

The tourism industry has been confronted with evolving market conditions and shifting consumer preferences in recent years (Mariani et al., 2019). The rise in the demand for personalized and immersive experiences has compelled destination marketers to creatively promote the distinctive features of their locations. This article aims to shed light on inventive destination marketing strategies, drawing on recent examples from 2022, with a focus on local culture, history, natural wonders, and attractions.

The Essence of Destination Marketing

Destination marketing is a multifaceted concept that transcends the realms of mere promotion or advertising, encompassing the comprehensive set of strategies employed to manage and market a location or tourist destination (Hays, Page, & Buhalis, 2022). It is the art of leveraging the unique selling propositions (USPs) of a location to foster a compelling narrative that entices potential visitors.

Case Studies

Case Study 1: “What does a Belly do in Vienna?” – A Unique Approach to Destination Marketing
Overview
The Vienna Tourist Board launched a distinctive and whimsical campaign in 2022 titled “What does a Belly do in Vienna?” This campaign featured a nearly six-minute short film, showcasing a walking belly’s adventure in Vienna.

Concept
The campaign’s concept revolves around a rotund stomach that leaves its workout-obsessed human, Harry, feeling unwelcome. The belly embarks on a journey to Vienna, where it explores the streets, appreciates sublime artworks, and indulges in the famous Sacher torte. Eventually, Harry reunites with his belly, and they enjoy a delightful date in a Viennese restaurant.

Message
The underlying message of the campaign is the celebration of self-indulgence and self-love. The tagline, “The most beautiful way to love yourself is to indulge,” encapsulates the essence of the campaign. It encourages travelers to let loose and enjoy the pleasures that Vienna has to offer.

Impact
This campaign stood out for its creativity and cinematic quality. While it may have polarized opinions, its unique storytelling approach provided a fresh perspective on destination marketing. By personifying a belly and allowing it to explore the city, the campaign highlighted Vienna’s cultural richness and culinary delights in an engaging and memorable way.

Conclusion
“What does a Belly do in Vienna?” serves as an inspiring example of how destination marketing can transcend traditional boundaries. By embracing a bold and imaginative concept, Vienna’s campaign successfully spotlighted the intrinsic value of the city, inviting travelers to experience its charm and indulge in its pleasures. This case study illustrates the potential of creative storytelling in destination marketing, offering valuable insights for other locations looking to craft compelling and resonant campaigns.

Case Study 2: “G’day” – A Cinematic Journey with Tourism Australia
Overview
Tourism Australia launched a captivating campaign in 2022 titled “G’day,” featuring a nine-minute animated short film. This campaign was part of the broader “Come and say g’day” initiative, aimed at inviting travelers to explore the wonders of Australia.

Concept
The film stars Rose Byrne as Ruby, a toy kangaroo, and Will Arnett as Louie, a toy unicorn. The pair break out of a Great Barrier Reef gift shop and embark on an adventurous journey across Australia, visiting iconic locations such as Nitmiluk Gorge, Uluru, the Great Barrier Reef, and the Sydney Opera House.

Message
The underlying message of the campaign is the warmth and friendliness encapsulated in the Australian greeting “G’day.” The film emphasizes that “G’day” is the start of every good adventure in Australia, symbolizing an invitation to friendship and exploration.

Impact
The “G’day” campaign was a massive success, racking up 19 million YouTube views in its first month alone. The blend of animation, storytelling, and the portrayal of Australia’s diverse landscapes resonated with audiences worldwide. The campaign’s tagline, “If you’re not a friend yet, you will be mate,” further reinforced the welcoming spirit of Australia.

Conclusion
The “G’day” campaign by Tourism Australia serves as a remarkable example of how destination marketing can leverage storytelling and creativity to create a compelling narrative. By using animated characters to guide viewers through Australia’s breathtaking scenery, the campaign successfully spotlighted the intrinsic value of the destination. This case study underscores the power of innovative storytelling in destination marketing, highlighting the potential to connect with audiences on an emotional level and inspire them to explore new horizons.

Conclusion

The growing demand for authentic and diverse experiences amongst today’s tourists necessitates innovative destination marketing strategies. The crux of this marketing approach lies in understanding the intrinsic value of the destination, extracting its unique aspects, and presenting them in a compelling narrative. Destination marketers can learn from successful contemporary campaigns, such as Vienna and Australia, and creatively engage potential tourists with alluring yet authentic portrayals of their location.

References

  • Hays, S., Page, S.J., & Buhalis, D. (2022). Social media as a destination marketing tool: Its use by national tourism organisations. Current Issues in Tourism, 25(1), 42-56.
  • Lepitak, S. (Date not specified). “What Does a Belly on Legs Do When It Goes on Holiday to Vienna?”. Adweek. Retrieved from https://www.adweek.com/brand-marketing/what-does-a-belly-on-legs-do-when-it-goes-on-holiday-to-vienna/
  • Mariani, M., Baggio, R., Fuchs, M., & Höepken, W. (2019). Business intelligence and big data in hospitality and tourism: A systematic literature review. International Journal of Contemporary Hospitality Management, 31(12), 2864-2902.
  • Rossi A. (2022) Comunicazione Digitale per il Turismo, Amazon KPD self-published, 2022
  • Tourism Australia (2022a). Come and Say G’day. Retrieved from https://www.tourism.australia.com/en/resources/campaign-resources/come-and-say-gday.html
  • Tourism Australia. (2022b). G’day, the short film. [Video]. Retrieved from https://www.youtube.com/watch?v=P3PdfWVk7h8
  • Vienna. (2022). What does a Belly do in Vienna? I Shortfilm [Video]. Retrieved from https://www.youtube.com/watch?v=RYjcIS-urbk

#DestinationMarketing; #TourismMarketing; #TravelIndustry; #MarketingStrategies; #TravelTrends; #TourismInnovation; #ViennaTourism; #WhatDoesABellyDoInVienna; #ViennaAdventure; #CulturalRichness; #CulinaryDelights; #TourismAustralia; #GdayAustralia; #AustralianAdventure; #GreatBarrierReef; #SydneyOperaHouse; #ExploreAustralia; #CreativeStorytelling; #InnovativeMarketing; #AuthenticExperience; #TravelInspiration; #ExploreTheWorld

The Digital Communication Plan for Tourism – Part XII: Measurements of the digital communication plan

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KPI Key Performance Indicator by fauziEv8

Key Performance Indicators (KPIs) are used by organizations of all sizes to measure their marketing or business results. KPIs are measurable values that business decision-makers use to evaluate the success of the company. In the context of digital communication, there are specific KPIs to monitor the effectiveness of the actions outlined in the communication plan and to improve areas where results fall below expectations.
For instance, the most common KPIs in Social Media Marketing include likes, followers, comments, and shares, but this is by no means an exhaustive list. The list of KPIs, if it were to encompass all possibilities, would exceed hundreds of items because each organization determines its own set of KPIs. Having too many KPIs does not lead to better control of communication but rather makes it difficult, if not impossible, to read performance reports. It is crucial to find the right number of KPIs that only provide measurements of the parameters that matter.
As a general guideline, having 20-30 KPIs can be sufficient to keep the situation under control. According to Karola Karlson from scoro.com [Karlson K., 2022], KPIs for digital communication can be divided into five main categories:

  1. Lead generation
  2. Website & traffic metrics
  3. SEO optimization
  4. Paid advertising
  5. Social media tracking

Karola Karlson identifies 37 possible KPIs to use within these five categories. Here are some examples.


Lead generation:

  • Monthly new leads/prospects
  • Qualified leads per month
  • Cost-per-lead generated
  • Cost per conversion
  • Average time of conversion
  • Retention rate
  • Attrition rate
  • Net promoter score

Website & traffic metrics:

  • Returning vs. new visitors
  • Visits per channel
  • Average time on page
  • Website conversion rate
  • The conversion rate for call-to-action content
  • Click-through rate (CTR) on web pages
  • Pages per visit

SEO optimization:

  • Inbound links to a website
  • Traffic from organic search
  • New leads from organic search
  • Conversions from organic search
  • Page authority
  • Google PageRank
  • Keywords in the top 10 SERP
  • Rank increase of target keywords
  • Conversion rate per keyword
  • Number of unique keywords that drive traffic
  • Volume of traffic from video content

Paid advertising:

  • Leads & conversions from paid advertising
  • Cost per acquisition (CPA) & cost per conversion
  • Click-through rate on PPC advertising

Social media tracking:

  • Traffic from social media
  • Leads and conversions from social media
  • Conversion rate
  • Managed audience size
  • Engagement rate
  • Mentions
  • Social media ROI

These 37 KPIs provided by Karola Kalrson are examples, and each organization will need to decide which KPIs are relevant to their specific case. Some of the KPIs on this list are easily understood, while others may be more complex.

Click here for Part I ; Click here for Part II ; Click here for part III; Click here for Part IV

Click here for Part V ; Click here for Part VI ; Click here for Part VII ; Click here for Part VIII

Click here for Part IX ; Click here for Part X ; Click here for Part XI

Sources:

#Measurements; #digitalcommunicationplan; #KPIs; #marketingresults; #businessresults; #effectiveness; #communicationplan; #improvement; #SocialMediaMarketing; #likes; #followers; #comments; #shares; #KPIlist; #control; #parameters; #leadgeneration; #websitetrafficmetrics; #SEOoptimization; #paidadvertising; #socialmediatracking; #leadgeneration; #monthlynewleads; #qualifiedleads; #costperlead; #costperconversion; #averagetimeofconversion; #retentionrate; #attritionrate; #netpromoterscore; #websitetrafficmetrics; #monthlywebsitetraffic; #returningvsnewvisitors; #visitsperchannel; #averagetimeonpage; #websiteconversionrate; #conversionrate; #clickthroughrate; #pagespervisit; #SEOoptimization; #inboundlinks; #trafficfromorganicsearch; #newleadsfromorganicsearch; #conversionsfromorganicsearch; #pageauthority; #GooglePageRank; #keywordstop10SERP; #rankincreaseoftargetkeywords; #conversionrateperkeyword; #numberofuniquekeywords; #volumeoftrafficfromvideocontent; #paidadvertising; #leadsandconversions; #costperacquisition; #clickthroughrate; #socialmediatracking; #trafficfromsocialmedia; #leadsandconversionsfromsocialmedia; #conversionrate; #managedaudiencesize; #engagementrate; #mentions; #socialmediaROI

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The Digital Communication Plan for Tourism – Part XI: Actions for maximizing impact and effectiveness

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Idea, Plan, Action by Tatiana_Mara

The digital communication plan is a strategic document that requires careful planning and precise management to achieve positive results. Not only does it define the actions to be taken over time, but it also fulfills a crucial role in honoring the commitment to the destination’s stakeholders by adhering to a specific course of action..

However, it is important to note that the editorial plan must be executed punctually unless unexpected events occur that, depending on their severity, may require partial or total revision of the plan. For example, the recent Covid-19 pandemic has forced many to rethink and adapt previously defined plans.

Regardless of the circumstances, the fundamental principles of good project management applied to digital communication include a precise understanding of timing, costs, and expected quality, as well as the flexibility to make changes during the implementation of the plan. It is also essential to periodically evaluate the results achieved in order to make necessary adjustments and improvements.

Following the planning flow described in this series of posts provides a solid foundation for optimally managing digital communication activities. However, it is important to emphasize that the success of the plan will also depend on adaptability and responsiveness to the changing dynamics of the digital context. Maintaining constant attention to trends, new opportunities, and stakeholder needs is essential to maximize the overall impact and effectiveness of the digital communication plan.

Click here for Part I ; Click here for Part II ; Click here for part III; Click here for Part IV

Click here for Part V ; Click here for Part VI ; Click here for Part VII ; Click here for Part VIII

Click here for Part IX ; Click here for Part X

Sources:

#digitalcommunication; #timing; #costs; #expectedquality; #flexibility; #changes; #implementation; #results; #planningflow; #adaptability; #responsiveness; #digitalcontext; #attention; #trends; #newopportunities; #stakeholderneeds; #impact; #effectiveness

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The Digital Communication Plan for Tourism – Part X: Budget

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Budget by formatoriginal

Any communication activity entails a series of economic costs and human resources that need to be estimated during the planning phase to ensure that the necessary resources are available to carry out the activity.

There is no one-size-fits-all communication budget template, but the main items typically include:

  • Human resources costs (organizational structure, agencies, and external collaborators)
  • Costs for content creation (text, translations, photos, videos, printed materials, etc.)
  • Expenses for hospitality and transportation for press, operators, influencers
  • Costs for ICT services
  • Advertising campaigns and special communication projects
  • (if applicable) Costs for info points and tourists assistance activities in the area

Click here for Part I ; Click here for Part II ; Click here for part III; Click here for Part IV

Click here for Part V ; Click here for Part VI ; Click here for Part VII ; Click here for Part VIII

Click here for Part IX

Sources:

#Budget; #CommunicationCosts; #HumanResources; #ContentCreation; #HospitalityExpenses; #TransportationExpenses; #ICTServices; #AdvertisingCampaigns; #CommunicationProjects; #TouristsAssistanceCosts; #InformationActivities

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The Digital Communication Plan for Tourism – Part IX: Timing

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Gantt chart By leungchopan

The aspect of timing is of fundamental importance in the implementation of the digital communication plan and must be addressed from different perspectives:

  • Phase of the customer journey
  • Seasonality and events
  • Booking window

The phases of the customer journey are those seen in this post (Dreaming, Researching, Booking, Experiencing, Sharing), and for each of these phases, it is crucial to convey the most appropriate message and distribute it where tourists obtain their information.

The most important phase, as tourists have not yet chosen a destination and therefore where we have the most influence, is the Dreaming phase. It is crucial to understand when and where our tourist audiences seek inspiration for their vacations.

A second aspect of timing choices concerns the communication of seasons, events, and recurring occasions. The communication plan must therefore gather information related to these moments to plan effective communication campaigns well in advance.

The third aspect of timing to consider in communication is the useful booking window, which varies from one geographic market to another and from one target audience to another (for example, vacation planning). This is based on factors such as age, family size, lifestyle, and other factors.

Click here for Part I ; Click here for Part II ; Click here for part III; Click here for Part IV

Click here for Part V ; Click here for Part VI ; Click here for Part VII ; Click here for Part VIII

Sources:

#Timing; #CustomerJourney; #Seasonality; #Events; #BookingWindow; #DigitalCommunication; #Influence; #Inspiration; #CommunicationPlan; #EffectiveCampaigns; #GeographicMarket; #TargetAudience; #VacationPlanning

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The Digital Communication Plan for Tourism – Part VIII: Channels

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Media By wanaktek

The destination or operator can choose whether and what to communicate directly (e.g., through their own website and blog) and what to communicate using other media (e.g., professional bloggers, online magazines, customers, residents, etc.).

In the digital world, there are numerous channels for communication. A classification, called the PESO™ model (Fig. 4), introduced by Gini Dietrich of Spinsucks [Spinsucks, 2020], helps us identify four types of online media:

  • (P) Paid Media
  • (E) Earned Media
  • (S) Shared Media
  • (O) Owned Media

Fig. 4 PESO™ Model – ©Gini Dietrich, spinsucks.com [Spinsucks, 2020]

  • Owned Media refers to media owned by a destination or a tourism operator, such as the website, blog, and social media channels through which the destination or operators communicate. They are “owned” as the control over the content lies entirely in the hands of the communicators (destination/operators). This is true for websites and blogs hosted on owned domains, while it partially applies to social media platforms where communicators must adhere to their rules and evolutions over time, although in general, destinations and operators have significant control over the published content.
  • Paid Media includes paid advertising channels. The internet provides various forms of advertising, such as sponsored posts on Instagram or Facebook, paid search engine ads, banners, and videos on third-party websites, and more. Therefore, in the case of social media, they become paid media when used for sponsored posts.
  • Shared Media refers to media shared by others (typically tourists, but also operators, etc.) where they share our content. This aspect is crucial for generating digital word-of-mouth and referrals (recommendations to family and friends)
  • Earned Media refers to earned media coverage, such as influential media outlets (online publications, influencers, etc.) that feature our content or mention our communication messages (proposals, themes, experiences, products, unique features, etc.). The difference between Shared Media and Earned Media lies in the level of influence of the media: typically, Shared Media consists of individuals who communicate within their circles of friends and acquaintances, while Earned Media includes professional or semi-professional communicators who reach their reference communities, with a more pronounced amplification effect.

Click here for Part I ; Click here for Part II ; Click here for part III; Click here for Part IV

Click here for Part V ; Click here for Part VI ; Click here for Part VII

Sources:

#Channels; #DigitalCommunication; #OwnedMedia; #PaidMedia; #EarnedMedia; #SharedMedia; #OnlineMarketing; #InfluencerMarketing; #ContentStrategy; #TourismCommunication

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The Digital Communication Plan for Tourism – Part VII: Senders, Styles, and Tones

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Follow us By formatoriginal

In digital communication for tourism, the main sender is the destination itself, but it should rely on other voices besides its official voice. In fact, the destination is responsible for institutional communication, but it is crucial for communication to be enriched by the voices of tourists, residents (who work in tourism or simply live in the destination), as well as influencers who are invited by or are present in the destination. Messages on the internet have a greater potential for dissemination when they are amplified by multiple entities, generating digital word of mouth.

Clearly, the increased message penetration associated with a multi-voiced communication is achieved when there is agreement on the content to be communicated. It is even better if the destination shares strategies, plans, guidelines, and communication logic. Otherwise, there is a risk that tourists will receive conflicting or even opposing messages. Of course, in a free world, it is neither possible nor advantageous to control the communication of all entities in the area. Instead, it is important to define and share themes, messages, formats, and graphics used in communication in a participatory manner, working together like a symphony orchestra.

In digital communication, in addition to traditional media relations that manage relationships with the traditional press, the communication team benefits from digital media relations. Therefore, the Destination Management Organization (DMO) manages relationships not only with traditional media (print, radio, TV, etc.) but also with digital creators and influencers to generate greater online engagement and targeted message dissemination.

Click here for Part I ; Click here for Part II ; Click here for part III; Click here for Part IV

Click here for Part V ; Click here for Part VI

Sources:

#DigitalCommunication; #Tourism; #DestinationMarketing; #Influencers; #WordOfMouth; #OnlineEngagement; #MediaRelations; #ContentStrategy; #CommunicationGuidelines; #TravelMarketing

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