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dc.contributor.author | Khatri, Jaikishan | es_ES |
dc.contributor.author | Marín-Morales, Javier | es_ES |
dc.contributor.author | Moghaddasi, Masoud | es_ES |
dc.contributor.author | Guixeres Provinciale, Jaime | es_ES |
dc.contributor.author | Chicchi Giglioli, Irene Alice | es_ES |
dc.contributor.author | Alcañiz Raya, Mariano Luis | es_ES |
dc.date.accessioned | 2023-02-17T19:00:15Z | |
dc.date.available | 2023-02-17T19:00:15Z | |
dc.date.issued | 2022-03-11 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/191898 | |
dc.description.abstract | [EN] Virtual reality (VR) is a useful tool to study consumer behavior while they are immersed in a realistic scenario. Among several other factors, personality traits have been shown to have a substantial influence on purchasing behavior. The primary objective of this study was to classify consumers based on the Big Five personality domains using their behavior while performing different tasks in a virtual shop. The personality recognition was ascertained using behavioral measures received from VR hardware, including eye-tracking, navigation, posture and interaction. Responses from 60 participants were collected while performing free and directed search tasks in a virtual hypermarket. A set of behavioral features was processed, and the personality domains were recognized using a statistical supervised machine learning classifier algorithm via a support vector machine. The results suggest that the open-mindedness personality type can be classified using eye gaze patterns, while extraversion is related to posture and interactions. However, a combination of signals must be exhibited to detect conscientiousness and negative emotionality. The combination of all measures and tasks provides better classification accuracy for all personality domains. The study indicates that a consumer's personality can be recognized using the behavioral sensors included in commercial VR devices during a purchase in a virtual retail store. | es_ES |
dc.description.sponsorship | This work was supported by the European Commission (Project RHUMBO H2020-MSCA-ITN-2018-813234), by the Generalitat Valenciana funded project 'Rebrand', grant number PROMETEU/2019/105, and by the European Regional Development Fund programme of the Valencian Community 2014-2020 project 'Interfaces de Realidad Mixta Aplicada a Salud y Toma de Decisiones', grant number IDIFEDER/2018/029. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Frontiers Media SA | es_ES |
dc.relation.ispartof | Frontiers in Psychology | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Big Five personality | es_ES |
dc.subject | Consumer behavior | es_ES |
dc.subject | Eye-tracking (ET) | es_ES |
dc.subject | Navigation | es_ES |
dc.subject | Machine learning | es_ES |
dc.subject | Statistical learning | es_ES |
dc.subject | Virtual store | es_ES |
dc.subject | Virtual reality | es_ES |
dc.subject.classification | EXPRESION GRAFICA EN LA INGENIERIA | es_ES |
dc.title | Recognizing Personality Traits Using Consumer Behavior Patterns in a Virtual Retail Store | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3389/fpsyg.2022.752073 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/813234/EU | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/GVA//PROMETEO%2F2019%2F105//REBRAND (MIXED REALITY AND BRAIN DECISION)/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/GVA//IDIFEDER%2F2018%2F029//INTERFACES DE REALIDAD MIXTA APLICADA A SALUD Y TOMA DE DECISIONES/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural - Escola Tècnica Superior d'Enginyeria Agronòmica i del Medi Natural | es_ES |
dc.description.bibliographicCitation | Khatri, J.; Marín-Morales, J.; Moghaddasi, M.; Guixeres Provinciale, J.; Chicchi Giglioli, IA.; Alcañiz Raya, ML. (2022). Recognizing Personality Traits Using Consumer Behavior Patterns in a Virtual Retail Store. Frontiers in Psychology. 13:1-17. https://doi.org/10.3389/fpsyg.2022.752073 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3389/fpsyg.2022.752073 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 17 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 13 | es_ES |
dc.identifier.eissn | 1664-1078 | es_ES |
dc.identifier.pmid | 35360568 | es_ES |
dc.identifier.pmcid | PMC8962833 | es_ES |
dc.relation.pasarela | S\458461 | es_ES |
dc.contributor.funder | Generalitat Valenciana | es_ES |
dc.contributor.funder | COMISION DE LAS COMUNIDADES EUROPEA | es_ES |