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Predicting decision-making in virtual environments: an eye movement analysis with household products

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Predicting decision-making in virtual environments: an eye movement analysis with household products

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dc.contributor.author Palacios-Ibáñez, Almudena es_ES
dc.contributor.author Marín-Morales, Javier es_ES
dc.contributor.author Contero, Manuel es_ES
dc.contributor.author Alcañiz Raya, Mariano Luis es_ES
dc.date.accessioned 2024-05-23T18:06:08Z
dc.date.available 2024-05-23T18:06:08Z
dc.date.issued 2023-06 es_ES
dc.identifier.uri http://hdl.handle.net/10251/204403
dc.description.abstract [EN] Understanding consumer behavior is crucial for increasing the likelihood of product success. Virtual Reality head-mounted displays incorporating physiological techniques such as eye-tracking offer novel opportunities to study user behavior in decision-making tasks. These methods reveal unconscious or undisclosed consumer responses. Yet, research into gaze patterns during virtual product evaluations remains scarce. In this context, an experiment was conducted to investigate users¿ gaze behavior when evaluating their preferences for 64 virtual prototypes of a bedside table. Here, 24 participants evaluated and selected their preferred design through eight repeated tasks of an 8-AFC, with individual evaluations conducted for each design to ensure the reliability of the findings. Several eye-tracking metrics were computed (i.e., gaze time, visits, and time to first gaze), statistical tests were applied, and a Long Short-Term Memory model was created to recognize decisions based on attentional patterns. Our results revealed that the Gaze Cascade Model was replicated in virtual environments and that a correlation between product liking and eye-tracking metrics exists. We recognize subjects¿ decisions with a 90% accuracy, based on their eye patterns during the three seconds before their decision. The results suggest that eye-tracking can be an effective tool for decision-making prediction during product assessment in virtual environments. es_ES
dc.description.sponsorship This work was funded by: (1) Spanish Ministry of Education and Vocational Training [FPU19/03878]; (2) Universitat Politècnica de València, grant for mobility of doctoral students [call for applications 2021]; and (3) Universitat Politècnica de València [PAID-10-20]. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Applied Sciences es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Virtual reality es_ES
dc.subject Extended reality es_ES
dc.subject User experience es_ES
dc.subject Eye movements es_ES
dc.subject Gaze bias es_ES
dc.subject Decision making es_ES
dc.subject Product evaluation es_ES
dc.subject Statistical learning es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.subject.classification EXPRESION GRAFICA EN LA INGENIERIA es_ES
dc.title Predicting decision-making in virtual environments: an eye movement analysis with household products es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/app13127124 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/ //FPU19%2F03878//AYUDA PREDOCTORAL FPU-PALACIOS IBAÑEZ. PROYECTO: REALIDADES MIXTAS Y PERCEPCIÓN DEL PRODUCTO: ANÁLISIS EXPERIMENTAL DE LA RELACIÓN ENTRE CALIDAD VISUAL E INTERACCIÓN Y LA RESPUESTA PERCEPTUAL Y EMOCIONAL DEL USUARIO./ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UPV-VIN//PAID-10-20//Reconocimiento emocional utilizando biomarcadores e inteligencia artificial en entornos de realidad virtual/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials 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 Palacios-Ibáñez, A.; Marín-Morales, J.; Contero, M.; Alcañiz Raya, ML. (2023). Predicting decision-making in virtual environments: an eye movement analysis with household products. Applied Sciences. 13(12). https://doi.org/10.3390/app13127124 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/app13127124 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 13 es_ES
dc.description.issue 12 es_ES
dc.identifier.eissn 2076-3417 es_ES
dc.relation.pasarela S\495424 es_ES
dc.contributor.funder UNIVERSIDAD POLITECNICA DE VALENCIA es_ES
dc.contributor.funder MINISTERIO DE UNIVERSIDADES E INVESTIGACION es_ES


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