Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/116340
DC FieldValueLanguage
dc.contributorSchool of Hotel and Tourism Managementen_US
dc.creatorHu, Jen_US
dc.creatorHuang, GQIen_US
dc.creatorWong, IKAen_US
dc.creatorWan, LCen_US
dc.date.accessioned2025-12-18T01:15:07Z-
dc.date.available2025-12-18T01:15:07Z-
dc.identifier.issn0160-7383en_US
dc.identifier.urihttp://hdl.handle.net/10397/116340-
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.subjectArtificial intelligence (AI)en_US
dc.subjectMotivated reasoningen_US
dc.subjectPersonnel decision-making agenten_US
dc.subjectQuasi-experimenten_US
dc.subjectScenario-based experimenten_US
dc.titleAI trust divide : how recruiter-candidate roles shape tourism personnel decision-makingen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume109en_US
dc.identifier.doi10.1016/j.annals.2024.103860en_US
dcterms.abstractThe artificial intelligence revolution has prompted tourism organizations to consider whether and how to use AI to improve efficiency and create value, particularly in areas such as personnel selection. Through five experimental studies (N = 2199), this paper first reveals that a trust divide exists between job candidates and recruiters in travel agencies. We then investigate how the consideration focus of personnel attributes mediates the impact of roles on trust through thought-listing (Study 1), mediation-by-moderation (Studies 2a & 2b), and self-reported measures (Study 3). To mitigate this misalignment, we examine the AI–human assemblage design and offer an optimal way to bridge the trust divide (Study 4). The current research extends motivated reasoning theory and provides novel insights into practice.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationAnnals of tourism research, Nov. 2024, v. 109, 103860en_US
dcterms.isPartOfAnnals of tourism researchen_US
dcterms.issued2024-11-
dc.identifier.eissn1873-7722en_US
dc.identifier.artn103860en_US
dc.description.validate202512 bcchen_US
dc.description.oaNot applicableen_US
dc.identifier.FolderNumbera4220-
dc.identifier.SubFormID52294-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis research is supported by the National Natural Science Foundation of China (No. 72004239, 72074230), PolyU (UGC) of the Hong Kong Special Administrative Region, China (Project No. P0048566, P0048183), and the Direct Research Grant from the School of Hotel and Tourism Management, CUHK (Grant No. 5501127).en_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2027-11-30en_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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Embargo End Date 2027-11-30
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