Browsing by Author "Girişken, Yener"

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An Exploratory Study on the Effect of Contour Types on Decision Making Via Optic Brain Imaging Method (fnirs)
(eScholarship, 2023) Demircioglu, Esin Tuna; Girişken, Yener; Çakar, Tuna
Decision-making is a combination of our positive anticipations from the future with the contribution of our past experiences, emotions, and what we perceive at the moment. Therefore, the cues perceived from the environment play an important role in shaping the decisions. Contours, which are the hidden identity of the objects, are among these cues. Aesthetic evaluation, on the other hand, has been shown to have a profound impact on decision-making, both as a subjective experience of beauty and as having an evolutionary background. The aim of this empirical study is to explain the effect of contour types on preference decisions in the prefrontal cortex through risk-taking and aesthetic appraisal. The obtained findings indicated a relation between preference decision, contour type, and PFC subregion. The results of the current study suggest that contour type is an effective cue in decision-making, furthermore, left OFC and right dlPFC respond differently to contour types.
Analyzing Consumer Behavior: the Impact of Retro Music in Advertisements on a Chocolate Brand and Consumer Engagement
(IEEE, 2023) Girişken, Yener; Soyaltın, Tuğçe Ezgi; Filiz, Gözde; Çakar, Tuna; Türkyılmaz, Ceyda Aysuna
This study presents research utilizing binary classification models to analyze consumer behaviors such as chocolate consumption and retro music ad viewing. Retro music, with its potential to evoke nostalgic feelings in consumers, is used in advertisements, which can have a significant impact on brand perception and consumer engagement. Firstly, a model focusing on chocolate consumption was developed and tested. The model yields significant outcomes. Secondly, a model based on retro music ad viewing status was developed and tested. Significant potential findings were obtained. This study emphasizes the applicability of effective classification models that can be used to understand and predict consumer behaviors, yielding significant outcomes.
Citation - Scopus: 1
Consumer Neuroscience Perspective for Brands: How Do Brands Influence Our Brains?
(IGI Global, 2020) Çakar, Tuna; Girişken, Yener
Neuroscientific tools have increasingly been used by marketing practitioners and researchers to understand and explain several different questions that have been issued for a specific company or a general understanding. In this respect, the neuroscientific approach has been evaluated as a potential tool for understanding the neural mechanisms directly related to marketing with its contribution to providing novel perspectives. The chapter addresses one of the most relevant subjects, brands, for issuing the strategic role of applied neuroscience in marketing and consumer behavior. The first section of this chapter focuses on a novel definition of brand, and the next section covers the brand image, brand perception, and brand loyalty. The second section summarizes the main findings regarding the neuroscience of brands. In the final section, the findings from a related experiment have been provided for the potential roles of neuromarketing for developing marketing strategies for brands.
Curvature Effect on Aesthetic Perception
(Cognitive Science Society, 2022) Demircioğlu, Tuna Esin; Çakar, Tuna; Girişken, Yener
Aesthetic perception is an inseparable part of the decision-making process in daily life. It also is an important partof the beauty and therefore tastes. The determination of preferences is directly related to the subregions of the PFC.The contour is the essential visual attribute for accurately perceiving the form of an object. It has been known thatsharp angles cause an implicit perception of threat, and perceived security is related to aesthetic pleasure. The aim ofthe study is to investigate the effect of contour type on decision making and aesthetic perception in PFC. The studyusing the fNIRS method has shown that there is a marginal significant relation between liking, contour type, and PFCareas (F(3.81)=2.225, p>.092, η2=.076). Current findings suggest that left mPFC, FPC, and right dlPFC have a significantcontribution to the liking of curved objects.
Prediction of Loan Decisions With Optical Neuroimaging (fnirs) and Machine Learning
(IEEE, 2023) Girişken, Yener; Son Turan, Semen; Çakar, Tuna; Ertuğrul, Seyit; Sayar, Alperen
The successful applications of neuroscientific methods and artificial learning approaches have increased in applied fields such as economics, marketing, and finance in the last decade. In this study, a prediction model was developed using the output of optical neuroimaging (fNIRS) measurements from the prefrontal brain regions while 40 participants made decisions for 35 credit offers. The aim was to predict participants' responses to credit offers using artificial learning methods based on four metrics obtained over time from the optical neuroimaging system. The findings of the study indicate that the first 6 seconds (prior to the response entry) are particularly critical. While the performance rate in the developed prediction models is found to be higher, especially in tree-based algorithms, this paper includes a performance comparison of 5 models specifically.
Siyasal Parti Liderlerine İlişkin Seçmen Algısının Beyin Görüntüleme Yöntemiyle Ölçülmesi Üzerine Pilot Bir Araştırma
(2021) Çakar, Tuna; Erdoğan, Çağdan; Girişken, Yener
Siyasi partilerin ve parti liderlerinin seçmen tarafından nasıl algılandığı sorusu siyasi pazarlama araştırma konularının başında gelen sorulardan biridir. Son dönemde pazarlama araştırmalarında beyin görüntüleme yöntemleri ölçülebilirlik ve objektiflik özellikleri dolayısıyla daha sık kullanılmaya başlanmıştır. Bu çalışmanın temel amacı, seçmenlerin liderlere ilişkin algısını, üyesi oldukları siyasi partiyi olumlu algılayacakları öngörüsünden yola çıkarak, beyin görüntüleme yöntemi kullanarak saptayabilmek ve ayrıştırabilmektir. Bu amaçla bu araştırmada, hem kullanım kolaylığı hem de akademik literatürdeki güvenilirliği nedeniyle işlevsel yakın kızıl ötesi spektrometre (fNIR) yöntemi tercih edilmiştir. Bu çerçevede Türkiye’de 2011 seçimlerinde en yüksek oy alan iki partinin aktif çalışma hayatı olan toplam 30 parti meclisi üyesi (30 erkek; Yaş ort.: 34.76) gönüllülük esasına dayanılarak çalışmaya davet edilmiştir. Katılımcılara siyasi parti liderleri ve sıfatlardan oluşan slaytlar gösterilmiş ve 3'lü Likert ölçeği ile tutumları sorulmuştur. Olası bir karşıtlık etkisini gözlemleyebilmek adına katılımcılar karşıt siyasi partilerden seçilmiştir. Çalışma sonunda katılımcıların tutumları beyanlarına dayandırılmadan, sadece nörofizyolojik verilerden yola çıkarak analiz edilmiştir. Elde edilen bulgular katılımcıların beklenen tutumlarının 5 kanal (V1, V5, V7, V9, V11) üzerinden istatistiksel olarak anlamlı seviyede ayrıştığını göstermektedir. Ampirik bir içeriğe sahip olan bu çalışmada elde edilen bulgular, hem özel olarak siyasal pazarlama, hem de daha genelinde pazarlama araştırmalarında yeni yöntemlerin geliştirilmesi ve uygulanması açısından önemlidir.
Citation - WoS: 2
Citation - Scopus: 3
Unlocking the Neural Mechanisms of Consumer Loan Evaluations: an Fnirs and Mlbased Consumer Neuroscience Study
(2024) Girişken, Yener; Son, Semen; Demircioğlu, Esin Tuna; Filiz, Gözde; Çakar, Tuna; Ertuğrul, Seyit; Sayar, Alperen
This study conducted a comprehensive exploration of the neurocognitive processes underlying consumer credit decision-making using cutting-edge techniques from neuroscience and artificial intelligence (AI). Employing functional Near-Infrared Spectroscopy (fNIRS), the research examines the hemodynamic responses of participants while evaluating diverse credit offers. The study integrates fNIRS data with advanced AI algorithms, specifically Extreme Gradient Boosting, CatBoost, and Light Gradient Boosted Machine, to predict participants' credit decisions based on prefrontal cortex (PFC) activation patterns. Findings reveal distinctive PFC regions correlating with credit behaviors, including the dorsolateral prefrontal cortex (dlPFC) associated with strategic decision-making, the orbitofrontal cortex (OFC) linked to emotional valuations, and the ventromedial prefrontal cortex (vmPFC) reflecting brand integration and reward processing. Notably, the right dorsomedial prefrontal cortex (dmPFC) and the right vmPFC contribute to positive credit preferences. This interdisciplinary approach bridges neuroscience and finance, offering unprecedented insights into the neural mechanisms guiding financial choices. The study's predictive model holds promise for refining financial services and illuminating human financial behavior within the burgeoning field of neurofinance. The work exemplifies the potential of interdisciplinary research to enhance our understanding of human financial decision-making.