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dc.contributor.authorNaumčik, Andrej
dc.date.accessioned2023-09-18T20:31:31Z
dc.date.available2023-09-18T20:31:31Z
dc.date.issued2020
dc.identifier.issn2029-882X
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/150690
dc.description.abstractThe identification of the best housing alternatives is influenced by a wide variety of factors, including supply, demand, social, cultural, psychological, personal factors. All of these factors have an effect on the behavior and emotional state of a home buyer. What are the most effective ways to choose a home when there is a plethora of complex choices? To determine the most effective choice, neuroscience techniques can be used. These techniques are classified in the following main groups in the article: 1) momentary techniques for measuring changes in electronic neuronal activity, 2) techniques for measuring changes in metabolic neuronal activity, 3) techniques for measuring changes in psychological response to a stimulus. Article’s analysis, its identification of advantages and disadvantages of the techniques, representing these groups: electroencephalography, functional magnetic resonance imaging, functional semi-infrared spectroscopy, eye capture, and galvanic skin reactions, has revealed the potential of using latter techniques in making marketing decisions, while working with target audiences of different ages, life experiences, character traits who want to live where they feel best.eng
dc.formatPDF
dc.format.extentp. 15-24
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyICONDA
dc.relation.isreferencedbyGale's Academic OneFile
dc.relation.isreferencedbyDOAJ
dc.relation.isreferencedbyDimensions
dc.relation.isreferencedbyTOC Premier
dc.relation.isreferencedbyAcademic Search Complete
dc.source.urihttps://journals.vgtu.lt/index.php/EST/article/view/13399/10126
dc.source.urihttps://doi.org/10.3846/est.2020.13399
dc.titlePossibilities of neuroscience application in housing development
dc.typeStraipsnis kitoje DB / Article in other DB
dcterms.accessRightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unre-stricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references44
dc.type.pubtypeS3 - Straipsnis kitoje DB / Article in other DB
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyStatybos fakultetas / Faculty of Civil Engineering
dc.subject.researchfieldT 002 - Statybos inžinerija / Construction and engineering
dc.subject.vgtuprioritizedfieldsIK0303 - Dirbtinio intelekto ir sprendimų priėmimo sistemos / Artificial intelligence and decision support systems
dc.subject.ltspecializationsL104 - Nauji gamybos procesai, medžiagos ir technologijos / New production processes, materials and technologies
dc.subject.endeveloped environment
dc.subject.enhousing
dc.subject.enbuildings
dc.subject.enneuroscience
dc.subject.enelectroencephalography
dc.subject.eneye capture
dcterms.sourcetitleEngineering structures and technologies
dc.description.issueiss. 1
dc.description.volumevol. 12
dc.publisher.nameVGTU Press
dc.publisher.cityVilnius
dc.identifier.doi10.3846/est.2020.13399
dc.identifier.elaba68924946


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