Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/11000/34516
Registro completo de metadatos
Campo DC Valor Lengua/Idioma
dc.contributor.authorJuárez-Varón, David-
dc.contributor.authorTur-Viñes, Victoria-
dc.contributor.authorRabasa, Alejandro-
dc.contributor.authorPolotskaya, Kristina-
dc.contributor.otherDepartamentos de la UMH::Estadística, Matemáticas e Informáticaes_ES
dc.date.accessioned2025-01-15T19:33:45Z-
dc.date.available2025-01-15T19:33:45Z-
dc.date.created2020-09-
dc.identifier.citationSocial Sciences Volume 9 Issue 9es_ES
dc.identifier.issn2076-0760-
dc.identifier.urihttps://hdl.handle.net/11000/34516-
dc.description.abstractThis research is in response to the question of which aspects of package design are more relevant to consumers, when purchasing educational toys. Neuromarketing techniques are used, and we propose a methodology for predicting which areas attract the attention of potential customers. The aim of the present study was to propose a model that optimizes the communication design of educational toys’ packaging. The data extracted from the experiments was studied using new analytical models, based on machine learning techniques, to predict which area of packaging is observed in the first instance and which areas are never the focus of attention of potential customers. The results suggest that the most important elements are the graphic details of the packaging and the methodology fully analyzes and segments these areas, according to social circumstance and which consumer type is observing the packaginges_ES
dc.formatapplication/pdfes_ES
dc.format.extent23es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectpackaginges_ES
dc.subjectdesignes_ES
dc.subjecttoyes_ES
dc.subjectneuromarketinges_ES
dc.subjecteye trackinges_ES
dc.subjectmachine learninges_ES
dc.subjectpredictive modelses_ES
dc.subjectconsumerses_ES
dc.subjectmethodologyes_ES
dc.subjectcommunicationes_ES
dc.subject.otherCDU::5 - Ciencias puras y naturales::50 - Generalidades sobre las ciencias purases_ES
dc.titleAn Adaptive Machine Learning Methodology Applied to Neuromarketing Analysis: Prediction of Consumer Behaviour Regarding the Key Elements of the Packaging Design of an Educational Toyes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://doi.org/10.3390/socsci9090162es_ES
Aparece en las colecciones:
Artículos Estadística, Matemáticas e Informática


Vista previa

Ver/Abrir:
 _8 Neuromarketing.pdf

10,78 MB
Adobe PDF
Compartir:


Creative Commons La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.