Repository logo
 

Generational Engagement With AI in Hospitality: Human–AI Interaction Perspectives Across the Service Process

aut.relation.endpage14
aut.relation.issueahead-of-print
aut.relation.journalCurrent Issues in Tourism
aut.relation.startpage1
aut.relation.volumeahead-of-print
dc.contributor.authorWang, Pola Q
dc.contributor.authorYan, Liwei
dc.contributor.authorSantoso, Carolin
dc.date.accessioned2025-07-28T21:40:18Z
dc.date.available2025-07-28T21:40:18Z
dc.date.issued2025-07-04
dc.description.abstractAs artificial intelligence (AI) becomes increasingly integrated into hospitality and tourism operations, it is essential to understand how employees from different generational cohorts engage with AI technologies in the workplace. This conceptual study introduces a generationally responsive framework to examine human AI engagement across three key service phases: pre-arrival, mid-arrival, and post-arrival. It distinguishes between two overarching modes of engagement: interaction, which includes coexistence, cooperation, and collaboration, and collaboration itself, which involves complementarity and augmentation models. Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT), the framework applies four key dimensions: performance expectancy, effort expectancy, social influence, and facilitating conditions to explain how generational characteristics influence AI perceptions and behaviours. A unique contribution of this study is the identification of an emerging autonomous decision support model, especially relevant for Generation Z, in which AI makes and implements service decisions independently with minimal human involvement. These generational patterns vary across service tasks and reflect broader differences in digital fluency, workplace expectations, and trust in technology. The study concludes that effective AI integration in hospitality requires alignment with the values, preferences, and interaction styles of a multigeneration workforce.
dc.identifier.citationCurrent Issues in Tourism, ISSN: 1368-3500 (Print); 1747-7603 (Online), Informa UK Limited, ahead-of-print, 1-14. doi: 10.1080/13683500.2025.2528981
dc.identifier.doi10.1080/13683500.2025.2528981
dc.identifier.issn1368-3500
dc.identifier.issn1747-7603
dc.identifier.urihttp://hdl.handle.net/10292/19610
dc.languageen
dc.publisherInforma UK Limited
dc.relation.urihttps://www.tandfonline.com/doi/full/10.1080/13683500.2025.2528981
dc.rights© 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
dc.rights.accessrightsOpenAccess
dc.subject35 Commerce, Management, Tourism and Services
dc.subject3504 Commercial Services
dc.subjectMachine Learning and Artificial Intelligence
dc.subject3 Good Health and Well Being
dc.subject1503 Business and Management
dc.subject1505 Marketing
dc.subject1506 Tourism
dc.subjectSport, Leisure & Tourism
dc.subject3506 Marketing
dc.subject3508 Tourism
dc.subject4406 Human geography
dc.subjectArtificial intelligence
dc.subjectgenerational differences
dc.subjecthospitality workforce
dc.subjecthuman–AI interaction
dc.subjectservice process
dc.subjecttechnology adoption
dc.titleGenerational Engagement With AI in Hospitality: Human–AI Interaction Perspectives Across the Service Process
dc.typeJournal Article
pubs.elements-id614960

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Generational engagement with AI in hospitality human AI interaction perspectives across the service process.pdf
Size:
815.82 KB
Format:
Adobe Portable Document Format
Description:
Journal article