Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11779/703
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dc.contributor.authorCakir, Murat Perit-
dc.contributor.authorÇakar, Tuna-
dc.contributor.authorGirisken, Yener-
dc.contributor.authorYurdakul, Dicle-
dc.date.accessioned2019-02-28T13:04:26Z
dc.date.accessioned2019-02-28T11:08:19Z
dc.date.available2019-02-28T13:04:26Z
dc.date.available2019-02-28T11:08:19Z
dc.date.issued2018-
dc.identifier.citationÇakir, M. P., Çakar, T., Girisken, Y., & Yurdakul, D. (December, 2018). An investigation of the neural correlates of purchase behavior through fNIRS. (European journal of marketing.)en_US
dc.identifier.issn0309-0566-
dc.identifier.urihttp://dx.doi.org/10.1108/EJM-12-2016-0864-
dc.identifier.urihttps://hdl.handle.net/20.500.11779/703-
dc.descriptionTuna Çakar (MEF Author)en_US
dc.description.abstractPurpose This study aims to explore the plausibility of the functional near-infrared spectroscopy (fNIRS) methodology for neuromarketing applications and develop a neurophysiologically-informed model of purchasing behavior based on fNIRS measurements. Design/methodology/approach The oxygenation signals extracted from the purchase trials of each subject were temporally averaged to obtain average signals for buy and pass decisions. The obtained data were analyzed via both linear mixed models for each of the 16 optodes to explore their separate role in the purchasing decision process and a discriminant analysis to construct a classifier for buy/pass decisions based on oxygenation measures from multiple optodes. Findings Positive purchasing decisions significantly increase the neural activity through fronto-polar regions, which are closely related to OFC and vmPFC that modulate the computation of subjective values. The results showed that neural activations can be used to decode the buy or pass decisions with 85 per cent accuracy provided that sensitivity to the budget constraint is provided as an additional factor. Research limitations/implications The study shows that the fNIRS measures can provide useful biomarkers for improving the classification accuracy of purchasing tendencies and might be used as a main or complementary method together with traditional research methods in marketing. Future studies might focus on real-time purchasing processes in a more ecologically valid setting such as shopping in supermarkets. Originality/value This paper uses an emerging neuroimaging method in consumer neuroscience, namely, fNIRS. The decoding accuracy of the model is 85 per cent which presents an improvement over the accuracy levels reported in previous studies. The research also contributes to existing knowledge by providing insights in understanding individual differences and heterogeneity in consumer behavior through neural activities.en_US
dc.language.isoenen_US
dc.relation.ispartofEuropean Journal Of Marketingen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDecision-makingen_US
dc.subjectNeuromarketingen_US
dc.subjectPurchasing behavioren_US
dc.subjectPurchasing decisionen_US
dc.subjectfNIRSen_US
dc.subjectOptical brain imagingen_US
dc.titleAn investigation of the neural correlates of purchase behavior through fNIRSen_US
dc.typeArticleen_US
dc.identifier.doi10.1108/EJM-12-2016-0864-
dc.identifier.scopus2-s2.0-85042384807en_US
dc.authoridTuna Çakar / 0000-0001-8594-7399-
dc.description.woscitationindexSocial Science Citation Index-
dc.identifier.wosqualityQ3-
dc.description.WoSDocumentTypeArticle
dc.description.WoSInternationalCollaborationUluslararası işbirliği ile yapılmayan - HAYIRen_US
dc.description.WoSPublishedMonthŞubaten_US
dc.description.WoSIndexDate2018en_US
dc.description.WoSYOKperiodYÖK - 2017-18en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.endpage243en_US
dc.identifier.startpage224en_US
dc.identifier.issue1_2en_US
dc.identifier.volume52en_US
dc.departmentMühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.identifier.wosWOS:000425598600011en_US
dc.institutionauthorÇakar, Tuna-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextembargo_20890214-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.openairetypeArticle-
crisitem.author.dept02.02. Department of Computer Engineering-
Appears in Collections:Bilgisayar Mühendisliği Bölümü koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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