Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Citation - WoS: 1Citation - Scopus: 1Prediction of Preference and Effect of Music on Preference: A Preliminary Study on Electroencephalography from Young Women(Tubitak Scientific & Technological Research Council Turkey, 2019-03-01) Yilmaz, Bulent; Gazeloglu, Cengiz; Altindis, FatihNeuromarketing is the application of the neuroscientific approaches to analyze and understand economically relevant behavior. In this study, the effect of loud and rhythmic music in a sample neuromarketing setup is investigated. The second aim was to develop an approach in the prediction of preference using only brain signals. In this work, 19-channel EEG signals were recorded and two experimental paradigms were implemented: no music/silence and rhythmic, loud music using a headphone, while viewing women shoes. For each 10-sec epoch, normalized power spectral density (PSD) of EEG data for six frequency bands was estimated using the Burg method. The effect of music was investigated by comparing the mean differences between music and no music groups using independent two-sample t-test. In the preference prediction part sequential forward selection, k-nearest neighbors (k-NN) and the support vector machines (SVM), and 5-fold cross-validation approaches were used. It is found that music did not affect like decision in any of the power bands, on the contrary, music affected dislike decisions for all bands with no exceptions. Furthermore, the accuracies obtained in preference prediction study were between 77.5 and 82.5% for k-NN and SVM techniques. The results of the study showed the feasibility of using EEG signals in the investigation of the music effect on purchasing behavior and the prediction of preference of an individual.Conference Object Citation - WoS: 4Citation - Scopus: 3Green Supplier Selection by Using Fuzzy TOPSIS Method(World Scientific Publishing Co. Pte Ltd wspc@wspc.com.sg, 2016-08) Dogan, Ahmet; Söylemez, İsmet; Özcan, Uǧur; Stylemez, IsmetWith the increased environmental consciousness in customers, organizations took upon the task of redesigning their strategic goals in a more environment-sensitive way in order to fulfill their social obligations, to enable sustainability, to gain competitive advantage and to make the world more habitable. Because, the emerging conditions in the 21st century indicate that the traditional criteria -such as price, cost so on for supply chain management, supplier selection and performance measurement of suppliers are no more sufficient and there is the necessity of adding new criteria such as environmental matters. This paper deals with the problem of selecting green suppliers in an organization in Turkey that has operations in the field of accumulator. The aim is to select the greenest of 3 suppliers in Turkey, France and Bulgaria which supply the organization with the plastic material used in the production of accumulator. The problem is solved via fuzzy TOPSIS, which is a multi-criteria decision making method (MCDM), and the results are used to select the greenest supplier. © 2017 Elsevier B.V., All rights reserved.