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dc.contributor.authorKaklauskas, Artūras
dc.contributor.authorZavadskas, Edmundas Kazimieras
dc.contributor.authorBanaitis, Audrius
dc.contributor.authorMeidutė-Kavaliauskienė, Ieva
dc.contributor.authorLiberman, Amir
dc.contributor.authorDzitac, Simona
dc.contributor.authorUbartė, Ieva
dc.contributor.authorBinkytė-Vėlienė, Arūnė
dc.contributor.authorČerkauskas, Justas
dc.contributor.authorKuzminskė, Agnė
dc.contributor.authorNaumčik, Andrej
dc.date.accessioned2023-09-18T17:00:53Z
dc.date.available2023-09-18T17:00:53Z
dc.date.issued2018
dc.identifier.issn0040-1625
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/118937
dc.description.abstractMany factors influence the identification of the best real estate alternatives, such as supply and demand and the social, cultural, psychological and personal factors affecting buyer behavior and the emotional state of a buyer. What are the most effective ways of choosing a property, when the selection is so vast and complex? An aid is developed here to accomplish this, based on a new advertising format, an iterative method and the NEuro-Advertising Property Video Recommendation System (NEAR). A known methodology involves behavioral operational research and the emotions involved in decision-making. Three advanced research contributions are unique to the proposed method and NEAR, in contrast to innovative behavioral operational research. Firstly, data are compiled for a neuro decision matrix, based on housing attributes and the valence, arousal, emotional state and physiological parameters of a potential real estate buyer. Secondly, the performance of a multiple criteria neuroanalysis occurs as well as the selection of the most personalized and effective video clip ad variants drawn from many alternatives. Finally, NEAR is found to present the most effective video clips ads for real estate buyers for as long a period as possible, according to Multiple Resource Theory.eng
dc.formatPDF
dc.format.extentp. 78-93
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbySociological Abstracts
dc.relation.isreferencedbyEngineering Index
dc.relation.isreferencedbyINSPEC
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyCurrent Contents / Social & Behavioral Sciences
dc.relation.isreferencedbySocial Sciences Citation Index (Web of Science)
dc.source.urihttp://dx.doi.org/10.1016/j.techfore.2017.07.011
dc.subjectSD04 - Tvarus statinių gyvavimo ciklas / Sustainable lifecycle of the buildings
dc.titleA neuro-advertising property video recommendation system
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.references68
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.institutionNemesysco, Kadima
dc.contributor.institutionUniversity of Oradea
dc.contributor.facultyStatybos fakultetas / Faculty of Civil Engineering
dc.contributor.facultyVerslo vadybos fakultetas / Faculty of Business Management
dc.contributor.departmentTvariosios statybos institutas / Institute of Sustainable Construction
dc.subject.researchfieldS 003 - Vadyba / Management
dc.subject.researchfieldT 002 - Statybos inžinerija / Construction and engineering
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.ltspecializationsL102 - Energetika ir tvari aplinka / Energy and a sustainable environment
dc.subject.enMCDA
dc.subject.enProperty
dc.subject.enMethods
dc.subject.enNeuro decision matrix
dc.subject.enAffective computing
dc.subject.enKnowledge-based real-world applications
dcterms.sourcetitleTechnological forecasting and social change
dc.description.volumeVol. 131
dc.publisher.nameElsevier
dc.publisher.cityNew York
dc.identifier.doi000430519300008
dc.identifier.doi2-s2.0-85025701897
dc.identifier.doi10.1016/j.techfore.2017.07.011
dc.identifier.elaba24482114


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