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The Augmentation Effect of Artificial Intelligence

dc.contributor.authorVorobeva, Darina
dc.contributor.authorPinto, Diego Costa
dc.contributor.authorAntónio, Nuno
dc.contributor.authorMattila, Anna S.
dc.contributor.institutionInformation Management Research Center (MagIC) - NOVA Information Management School
dc.contributor.institutionNOVA Information Management School (NOVA IMS)
dc.contributor.pblRoutledge Journals, Taylor & Francis Ltd
dc.date.accessioned2023-05-29T22:28:32Z
dc.date.available2025-02-06T01:31:50Z
dc.date.embargoedUntil2024-10-01
dc.date.issued2024-05-18
dc.descriptionVorobeva, D., Pinto, D. C., António, N., & Mattila, A. S. (2024). The Augmentation Effect of Artificial Intelligence: Can AI Framing Shape Customer Acceptance of AI-based Services? Current Issues in Tourism, 27(10), 1551-1571. https://doi.org/10.1080/13683500.2023.2214353 ---%ABS2% ---This work received partial support from national funds through FCT (Fundação para a Ciência e a Tecnologia) , under the project – UIDB/04152/2020 – Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS and 2021.09496.BD.
dc.description.abstractAlthough Artificial Intelligence is a big revolution in the tourism and hospitality industry, prior research provides little insight into how customers respond to AI replacement and how providers can mitigate AI aversion. Drawing on the Feeling Economy framework, three studies examine how customers react to a different framing of AI replacement (augmentation vs. substitution) compared to using only human employees, affecting their acceptance of AI-based services. The findings contribute to the tourism and hospitality literature by revealing that framing AI as augmentation (vs. substitution) can increase enjoyment and ease of use and improve AI acceptance. Consistent with the Feeling Economy account, the findings highlight the proposed mechanism of enjoyment and perceived ease of use underlying the AI framing effects. This research provides important theoretical and managerial implications for tourism and hospitality providers, helping them understand how to effectively introduce AI-based services to win customers’ acceptance.en
dc.description.versionauthorsversion
dc.description.versionpublished
dc.format.extent21
dc.format.extent499700
dc.identifier.doi10.1080/13683500.2023.2214353
dc.identifier.issn1368-3500
dc.identifier.otherPURE: 59475269
dc.identifier.otherPURE UUID: 021ce0cf-8ab5-4333-978a-590129b6a38a
dc.identifier.otherScopus: 85160222243
dc.identifier.otherWOS: 000995146100001
dc.identifier.otherORCID: /0000-0003-4418-9450/work/152551817
dc.identifier.urihttp://hdl.handle.net/10362/153315
dc.identifier.urlhttps://www.scopus.com/pages/publications/85160222243
dc.identifier.urlhttps://www.webofscience.com/wos/woscc/full-record/WOS:000995146100001
dc.language.isoeng
dc.peerreviewedyes
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04152%2F2020/PT
dc.relationInformation Management Research Center
dc.relationhttps://doi.org/10.54499/2021.09496.BD
dc.subjectartificial intelligence
dc.subjectfeeling economy
dc.subjecthospitality
dc.subjecttourism
dc.subjecttechnology acceptance
dc.subjectaugmentation
dc.subjectGeography, Planning and Development
dc.subjectTourism, Leisure and Hospitality Management
dc.subjectSDG 8 - Decent Work and Economic Growth
dc.titleThe Augmentation Effect of Artificial Intelligenceen
dc.title.subtitleCan AI Framing Shape Customer Acceptance of AI-based Services?en
dc.typejournal article
degois.publication.firstPage1551
degois.publication.issue10
degois.publication.lastPage1571
degois.publication.titleCurrent Issues in Tourism
degois.publication.volume27
dspace.entity.typePublication
oaire.awardNumberUIDB/04152/2020
oaire.awardTitleInformation Management Research Center
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04152%2F2020/PT
oaire.fundingStream6817 - DCRRNI ID
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccess
relation.isProjectOfPublication3274bdb3-4dd3-4bbe-8f74-d34190081f87
relation.isProjectOfPublication.latestForDiscovery3274bdb3-4dd3-4bbe-8f74-d34190081f87

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