Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/89891

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Campo DCValorIdioma
dc.contributor.authorGonçalves, Patríciapor
dc.contributor.authorMartins, Helenapor
dc.contributor.authorSaraiva, Pedropor
dc.contributor.authorCarneiro, Joãopor
dc.contributor.authorNovais, Paulopor
dc.contributor.authorMarreiros, Goretipor
dc.date.accessioned2024-03-22T16:14:52Z-
dc.date.issued2023-
dc.identifier.citationAlves, P., Martins, H., Saraiva, P. et al. Group recommender systems for tourism: how does personality predict preferences for attractions, travel motivations, preferences and concerns?. User Model User-Adap Inter 33, 1141–1210 (2023). https://doi.org/10.1007/s11257-023-09361-2-
dc.identifier.issn0924-1868-
dc.identifier.urihttps://hdl.handle.net/1822/89891-
dc.description.abstractTo travel in leisure is an emotional experience, and therefore, the more the information about the tourist is known, the more the personalized recommendations of places and attractions can be made. But if to provide recommendations to a tourist is complex, to provide them to a group is even more. The emergence of personality computing and personality-aware recommender systems (RS) brought a new solution for the cold-start problem inherent to the conventional RS and can be the leverage needed to solve conflicting preferences in heterogenous groups and to make more precise and personalized recommendations to tourists, as it has been evidenced that personality is strongly related to preferences in many domains, including tourism. Although many studies on psychology of tourism can be found, not many predict the tourists’ preferences based on the Big Five personality dimensions. This work aims to find how personality relates to the choice of a wide range of tourist attractions, traveling motivations, and travel-related preferences and concerns, hoping to provide a solid base for researchers in the tourism RS area to automatically model tourists in the system without the need for tedious configurations, and solve the cold-start problem and conflicting preferences. By performing Exploratory and Confirmatory Factor Analysis on the data gathered from an online questionnaire, sent to Portuguese individuals from different areas of formation and age groups (n = 1035), we show all five personality dimensions can help predict the choice of tourist attractions and travel-related preferences and concerns, and that only neuroticism and openness predict traveling motivations.por
dc.description.sponsorshipOpen access funding provided by FCT|FCCN (b-on). This work was supported by the GrouPlanner and smarTravel Projects under the European Regional Development Fund POCI-01-0145-FEDER-29178 and POCI-01-0247-FEDER-179946, respectively, and by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UIDB/00319/2020 and UIDB/00760/2020.por
dc.language.isoengpor
dc.publisherSpringer-
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00319%2F2020/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00760%2F2020/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00319%2F2020/PT-
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00760%2F2020/PT-
dc.rightsopenAccesspor
dc.subjectAffective computingpor
dc.subjectGroup recommender systemspor
dc.subjectPersonalitypor
dc.subjectTourist preferencespor
dc.subjectTravel concernspor
dc.subjectTravel motivationspor
dc.titleGroup recommender systems for tourism: how does personality predict preferences for attractions, travel motivations, preferences and concerns?por
dc.typearticlepor
dc.peerreviewedyespor
dc.relation.publisherversionhttps://link.springer.com/article/10.1007/s11257-023-09361-2-
oaire.citationStartPage1141por
oaire.citationEndPage1210por
oaire.citationIssue5por
oaire.citationVolume33por
dc.date.updated2024-03-14T11:43:44Z-
dc.identifier.doi10.1007/s11257-023-09361-2por
dc.date.embargo10000-01-01-
sdum.export.identifier13461-
sdum.journalUser Modeling and User-Adapted Interactionpor
Aparece nas coleções:CAlg - Artigos em revistas internacionais / Papers in international journals

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