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Artificial Intelligence vs. Autonomous Decision-Making in Streaming Platforms

2024-06Artigo científico Acesso aberto
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dc.contributor.authorGonçalves, Ana Rita
dc.contributor.authorPinto, Diego Costa
dc.contributor.authorShuqair, Saleh
dc.contributor.authorDalmoro, Marlon
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.pblELSEVIER SCI LTD
dc.date.accessioned2025-03-10T21:08:27Z
dc.date.available2025-03-12T01:31:58Z
dc.date.embargoedUntil2025-03-11
dc.date.issued2024-06
dc.descriptionGonçalves, A. R., Pinto, D. C., Shuqair, S., Dalmoro, M., & Mattila, A. S. (2024). Artificial Intelligence vs. Autonomous Decision-Making in Streaming Platforms: a Mixed-Method Approach. International Journal Of Information Management, 76, 1-12. Article 102748. https://doi.org/10.1016/j.ijinfomgt.2023.102748 --- %ABS2% --- This work received partial support from national funds through FCT (Fundação para a Ciência e a Tecnologia), under the projects - UIDB/04152/2020 and DSAIPA/DS/0113/2019 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS.
dc.description.abstractAlthough the empowerment of technology is of great value to society, little is known about its downstream effects on consumers' decisions. This research draws on the expectation–confirmation theory and autonomy in artificial intelligence (AI) and investigates how AI (vs. autonomous choice) has detrimental effects on consumer outcomes, creating an autonomy-technology tension — i.e., the conflict arising from AI technology diminishing consumers' autonomy in their choices. Four studies using a mixed-method approach reveal that the use of AI recommendations in streaming platforms creates an autonomy-technology tension that reduces consumers' performance expectancy, thus lowering their satisfaction. However, such effects are contingent on the nature of the AI recommendations. While a mismatch between AI recommendations and consumer preferences might backfire, AI's negative effect is mitigated when choices match consumers' preferences. We make significant theoretical and practical contributions to empirical research on consumers' sense of autonomy while interacting with AI.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent12
dc.format.extent680128
dc.identifier.doi10.1016/j.ijinfomgt.2023.102748
dc.identifier.issn0268-4012
dc.identifier.otherPURE: 82084780
dc.identifier.otherPURE UUID: bd991e4a-e199-4925-9a8c-4c3d7009178d
dc.identifier.otherScopus: 85183563881
dc.identifier.otherWOS: 001218444700001
dc.identifier.otherORCID: /0000-0003-4418-9450/work/179772495
dc.identifier.urihttp://hdl.handle.net/10362/180395
dc.identifier.urlhttps://www.scopus.com/pages/publications/85183563881
dc.identifier.urlhttps://www.webofscience.com/wos/woscc/full-record/WOS:001218444700001
dc.language.isoeng
dc.peerreviewedyes
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04152%2F2020/PT
dc.relationInformation Management Research Center
dc.relationData Science and Over-Indebtedness: Use of Artificial Intelligence Algorithms in Credit Consumption and Indebtedness Conciliation in Portugal
dc.subjectArtificial Intelligence
dc.subjectAutonomy
dc.subjectDecision-Making
dc.subjectPerformance Expectancy
dc.subjectStreaming Platforms
dc.subjectManagement Information Systems
dc.subjectInformation Systems
dc.subjectComputer Networks and Communications
dc.subjectInformation Systems and Management
dc.subjectMarketing
dc.subjectLibrary and Information Sciences
dc.subjectArtificial Intelligence
dc.subjectSDG 8 - Decent Work and Economic Growth
dc.titleArtificial Intelligence vs. Autonomous Decision-Making in Streaming Platformsen
dc.title.subtitlea Mixed-Method Approachen
dc.typejournal article
degois.publication.firstPage1
degois.publication.lastPage12
degois.publication.titleInternational Journal Of Information Management
degois.publication.volume76
dspace.entity.typePublication
oaire.awardNumberUIDB/04152/2020
oaire.awardNumberDSAIPA/DS/0113/2019
oaire.awardTitleInformation Management Research Center
oaire.awardTitleData Science and Over-Indebtedness: Use of Artificial Intelligence Algorithms in Credit Consumption and Indebtedness Conciliation in Portugal
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04152%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/DSAIPA%2FDS%2F0113%2F2019/PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream3599-PPCDT
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccess
relation.isProjectOfPublication3274bdb3-4dd3-4bbe-8f74-d34190081f87
relation.isProjectOfPublicatione750f897-cfb5-46b7-84ff-3b768eeb44f6
relation.isProjectOfPublication.latestForDiscoverye750f897-cfb5-46b7-84ff-3b768eeb44f6

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NIMS: MagIC - Artigos em revista internacional com arbitragem científica (Peer-Review articles in international journals)