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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 |