The Role of Artificial Intelligence (AI) and Data Analytics in Enhancing Guest Personalization in Hospitality
DOI:
https://doi.org/10.47941/jmh.1556Keywords:
Artificial Intelligence (AI), Data Analytics, Guest Personalization, Hospitality Industry, Guest ExperienceAbstract
Purpose: The main objective of this study was to explore the role of Artificial Intelligence (AI) and data analytics in enhancing guest personalization.
Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive's time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library.
Findings: The findings revealed that there exists a contextual and methodological gap relating to the role of Artificial Intelligence (AI) and data analytics in enhancing guest personalization. Preliminary empirical review revealed the significant potential of AI and data analytics in transforming the hospitality industry by enhancing guest personalization. By offering personalized experiences that align with individual preferences, hotels can not only improve guest satisfaction but also drive revenue growth and customer loyalty. However, it is imperative for the industry to navigate the ethical considerations associated with data privacy to ensure that the benefits of personalization are realized without compromising guest trust and privacy. The findings of this study provide valuable insights for hoteliers, service providers, and policymakers looking to harness the power of AI and data analytics to create exceptional guest experiences in the evolving landscape of hospitality.
Unique Contribution to Theory, Practice and Policy: The Technology Acceptance Model (TAM), Service Quality theory and Customer Relationship Management theory (CRM) may be used to anchor future studies on Artificial Intelligence and data analytics in modern hospitality. This study recommended for investing in robust AI and data analytics infrastructure, gathering comprehensive guest data, implementing AI driven personalization algorithms, empowering staff with AI tools and continuously monitoring and adapting.
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References
Agyekum, K., & Kwakye, I. O. (2019). The Influence of Personalization on Customer Relationship
Management in the Hotel Industry: Evidence from Ghana. International Journal of Hospitality
Management, 77, 1-10. [DOI:10.1016/j.ijhm.2018.05.019]
Agyekum, K., & Kwakye, I. O. (2019). The Influence of Personalization on Customer Relationship
Management in the Hotel Industry: Evidence from Ghana. International Journal of Hospitality
Management, 77, 1-10.
Berman, D. (2023). Revolutionizing the hospitality industry with artificial intelligence. Forbes.
Bisoi, S., Roy, M., & Samal, A. (2020). Impact of artificial intelligence in the hospitality industry.
International Journal of Advanced Science and Technology, 29(5), 4265-4276.
Blattberg, R. C., Getz, G., & Thomas, J. S. (2001). Customer Equity: Building and Managing
Relationships as Valuable Assets. Harvard Business Review, 79(7), 114-121.
Buhalis, D., Harwood, T., Bogicevic, V., Viglia, G., Beldona, S., & Hofacker, C. (2019).
Technological disruptions in services: lessons from tourism and hospitality. Journal of Service
Management, 30(4), 484-506.
Chenini, A. and Touaiti, M.B. (2020). Building destination loyalty using tourist satisfaction and
destination image: A holistic conceptual framework. Journal of Tourism Futures, 6(2), 163-
https://doi.org/10.1108/JTF-11-2018-0075
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information
Technology. MIS Quarterly, 13(3), 319-340.
Din, Z. (2017). "Case Study: The Langham, London." Hotel Business Review, 51(6), 62-64.
JNTO. (2021). Japan's Hospitality and Tourism Trend Report 2021. Japan National Tourism
Organization.
Kandampully, J., Zhang, T., Jaakkola, M., Anwar, S., Keating, B., Kim, B.P., Solnet, D., Deale, C.,
Lee, S.H., Mattila, A.S., Namkung, Y., Torres, E.N., Hallak, R., Wang, L., Wei, W., Xu, H.,
Yang, W., Zhang, H. and Zhou, L. (2020). Service innovation through artificial intelligence in
hospitality: A review of the literature and future research directions. International Journal of
Contemporary Hospitality Management, 32(12), 3795-3824. https://doi.org/10.1108/IJCHM04-2020-0316
Kenya Tourism Board. (2019). Tourism in Kenya: Annual Sector Performance Report 2019. Retrieved
from [DOI:10.13140/RG.2.2.17632.35844]
Kizildag, M., Ozturk, A.B., Demirer, I. and Cobanoglu, C. (2019). The impact of big data analytics on
the hospitality industry: A review of literature and future research directions. Journal of
Hospitality and Tourism Technology, 10(4), 760-776. https://doi.org/10.1108/JHTT-03-2019-
Lee, J.S., Nguyen, T.H., Park, J.H., Chang, H.J., Kim, S.B., Park, S.C. and Lee, H.J. (2018). A study
on the effects of artificial intelligence on hotel guests' perceived value, satisfaction and
behavioral intention: Focusing on chatbot service. Asia Pacific Journal of Tourism Research,
(12), 1241-1254. https://doi.org/10.1080/10941665.2018.1537120
Li, X., Wang, D., Liang, J., & Huang, Y. (2019). Data-Driven and AI-Powered Smart Hotel: A
Convergence of Service, Strategy, and Space. Cornell Hospitality Quarterly, 60(1), 13-26.
Liang, S., Schuckert, M., Law, R. and Masiero, L. (2019). The relevance of mobile technologies for
service personalization in hotels: A hierarchical latent class analysis approach. International
Journal of Hospitality Management, 82(1), 1-10. https://doi.org/10.1016/j.ijhm.2019.04.002
Lv, H., Shi, S., & Gursoy, D. (2022). A look back and a leap forward: a review and synthesis of big
data and artificial intelligence literature in hospitality and tourism. Journal of Hospitality
Marketing & Management, 31(2), 145-175.
McKinsey & Company. (2020). "The State of AI in Hospitality." Retrieved from DOI Link
Nigerian Hospitality Report. (2018). Key Insights and Trends in the Nigerian Hospitality Industry.
Retrieved from [DOI:10.13140/RG.2.2.22700.31363]
O'Neill, J. W., & Xiao, Q. (2018). Artificial Intelligence in Hospitality. Cornell Hospitality Report,
(12), 6-13.
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A Multiple-Item Scale for
Measuring Consumer Perceptions of Service Quality. Journal of Retailing, 64(1), 12-40.
Pavlou, P. A., Liang, X., & Xue, Y. (2019). Understanding and Mitigating the Effects of
Personalization on Customers’ Responses to Permission Requests: An Empirical Investigation
in the Context of Mobile Advertising. Information Systems Research, 30(1), 220-237.
PR Newswire. (2019). OpenTable introduces personalized dining experiences with 'OpenTable
Connect.' Retrieved from https://www.prnewswire.com/news-releases/opentable-introducespersonalized-dining-experiences-with-opentable-connect-300799350.html
Roberts, J. (2019). "Premier Inn Launches New Guest Experience App." Hotel Owner. Retrieved from
DOI Link
Ruel, H. and Njoku, E. (2021). AI redefining the hospitality industry. Journal of Tourism Futures, 7(1),
-66. https://doi.org/10.1108/JTF-03-2020-0032
Shimizu (2020). AI-Driven Virtual Concierge: The Impact of a Chatbot on Guest Satisfaction in
Japanese Hotels. Journal of Hospitality and Tourism Technology, 11(4), 581-595.
Smith, A., & Johnson, B. (2022). The State of AI and Data Analytics Adoption in the Hospitality
Industry: Challenges and Opportunities. Hospitality Trends, 12(3), 45-58.
South African Tourism. (2020). Annual Report 2020. Retrieved from
[DOI:10.13140/RG.2.2.24315.71202]
Statista. (2020). Open rate of personalized email marketing in the United States as of Q1 2020.
Retrieved from https://www.statista.com/statistics/263252/e-mail-marketing-open-rates-inthe-us-by-industry/
Sun, Y. (2019). "Guest Personalization in the Hospitality Industry: A Systematic Literature Review."
Journal of Hospitality Marketing & Management, 28(6), 641-667. DOI:
1080/19368623.2019.1585720
Tanaka, H., & Tazaki, M. (2018). Omotenashi and Guest Satisfaction: A Study of Japanese Hotels.
Journal of Hospitality and Tourism Management, 35, 55-58.
Tussyadiah, I. P., & Park, S. (2018). "When Guests Trust Hosts for Their Word: Host Profile, Trust in
Host, and Intentions to Use P2P Accommodations." Tourism Management, 67, 261-272. DOI:
1016/j.tourman.2018.01.010
Wang, D., & Xiang, Z. (2019). The Coevolution of Travel Agencies and Hotels’ Response Strategies
to the Sharing Economy. Journal of Travel Research, 58(5), 757-773.
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.
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