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dc.contributor.authorKaklauskas, Artūras
dc.contributor.authorZavadskas, Edmundas Kazimieras
dc.contributor.authorSchuller, Bjoern
dc.contributor.authorLepkova, Natalija
dc.contributor.authorDzemyda, Gintautas
dc.contributor.authorŠliogerienė, Jūratė
dc.contributor.authorKurasova, Olga
dc.date.accessioned2023-09-18T20:22:51Z
dc.date.available2023-09-18T20:22:51Z
dc.date.issued2020
dc.identifier.issn1661-7827
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/149373
dc.description.abstractThe implementation of advertising for green housing usually involves consideration of individual differences among potential buyers, their desires for residential unit features as well as location impacts on a selected property. Much more rarely, there is consideration of the arousal and valence, affective behavior, emotional, and physiological states of possible buyers of green housing (AVABEPS) while they review the advertising. Yet, no integrated consideration of all these factors has been undertaken to date. The objective of this study was to consider, in an integrated manner, the AVABEPS, individual differences, and location impacts on property and desired residential unit features. During this research, the applications for the above data involved neuromarketing and multicriteria examination of video advertisements for diverse client segments by applying neuro decision tables. All of this can be performed by employing the method for planning and analyzing and by multiple criteria and customized video neuro-advertising green-housing variants (hereafter abbreviated as the ViNeRS Method), which the authors of this article have developed and present herein. The developed ViNeRS Method permits a compilation of as many as millions of alternative advertising variants. During the time of the ViNeRS project, we accumulated more than 350 million depersonalized AVABEPS data. The strong and average correlations determined in this research (over 35,000) and data examination by IBM SPSS tool support demonstrate the need to use AVABEPS in neuromarketing and neuro decision tables. The obtained dependencies constituted the basis for calculating and graphically submitting the ViNeRS circumplex model of affect, which the authors of this article developed. This model is similar to Russell’s well-known earlier circumplex model of affect. Real case studies with their related contextual conditions presented in this manuscript show a practical application of the ViNeRS Method.eng
dc.formatPDF
dc.format.extentp. 1-28
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbyCABI - CAB Abstracts
dc.relation.isreferencedbyChemical abstracts
dc.relation.isreferencedbyGEOBASE (Elsevier)
dc.relation.isreferencedbyDOAJ
dc.relation.isreferencedbyGenamics Journal Seek
dc.relation.isreferencedbyPubMed
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbySocial Sciences Citation Index (Web of Science)
dc.rightsLaisvai prieinamas internete
dc.source.urihttps://doi.org/10.3390/ijerph17072244
dc.source.urihttps://talpykla.elaba.lt/elaba-fedora/objects/elaba:55049508/datastreams/MAIN/content
dc.titleCustomized ViNeRS method for video neuro-advertising of green housing
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.accessRightsThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references60
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.institutionImperial College London
dc.contributor.institutionVilniaus universitetas
dc.contributor.facultyStatybos fakultetas / Faculty of Civil Engineering
dc.subject.researchfieldT 002 - Statybos inžinerija / Construction and engineering
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.researchfieldS 003 - Vadyba / Management
dc.subject.vgtuprioritizedfieldsSD0404 - Statinių skaitmeninis modeliavimas ir tvarus gyvavimo ciklas / BIM and Sustainable lifecycle of the structures
dc.subject.ltspecializationsL102 - Energetika ir tvari aplinka / Energy and a sustainable environment
dc.subject.engreen housing
dc.subject.enneuro decision matrix
dc.subject.enneuro correlation matrix
dc.subject.envideo neuro-advertising
dc.subject.enCOPRAS and ViNeRS Methods
dc.subject.enmultivariate design and multiple criteria analysis
dcterms.sourcetitleInternational journal of environmental research and public health: Special issue "Trends in sustainable buildings and infrastructure"
dc.description.issueiss. 7
dc.description.volumevol. 17
dc.publisher.nameMDPI
dc.publisher.cityBasel
dc.identifier.doi000530763300076
dc.identifier.doi10.3390/ijerph17072244
dc.identifier.elaba55049508


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