Abstract
Artificial intelligence-based bath bed reservation services signify a novel evaluation of consumer behavior in densely populated tourist destinations. The phenomenon of overcrowded beaches, particularly during the peak summer months at well-known public beaches in Europe, has increased demand during rush hours. The research aims to clarify the key factors that influence the use of these applications, primarily on mobile phones, by applying the Push-Pull-Mooring Theory, in addition to identifying the primary causes of the high demand and the importance of staying close to the shore when sunbathing. The study emphasizes the impact of perceived risk and enjoyment on user behavior, taking into account the influence of social factors in shaping these choices. Comprehending these factors is essential for enhancing user engagement and service adoption in the digital realm, offering insights not only for app owners, hotel managers, and beach bar managers but also contributing to the self-identification of consumers during their holidays. The emergence of reservations lacking genuine interaction with staff highlights a novel business opportunity that enhances the tourism experience.
Keywords
artificial intelligence-driven, push-pull-mooring theory, reservation services
ORCID Identifiers
Dimitra Skandali: https://orcid.org/0009-0008-1728-2821
Muhammad Ali Raza: https://orcid.org/0000-0002-1536-2245
DOI
10.5038/2771-5957.4.1.1059
Recommended Citation
Skandali, D., & Raza, M. (2025). The emergence of artificial intelligence-driven reservation services analyzed through push-pull-mooring theory and their potential to enhance tourism experiences. Journal of Global Hospitality and Tourism, 4(1), 10-28. https://www.doi.org/10.5038/2771-5957.4.1.1059
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Included in
Advertising and Promotion Management Commons, Business Administration, Management, and Operations Commons, Hospitality Administration and Management Commons, Social and Behavioral Sciences Commons, Tourism and Travel Commons
