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MEASURING CONSUMER BRAND PERCEPTIONS IN TERMS OF NEUROMARKETING BY USING THE EEG METHOD: AN EXPERIMENTAL STUDY ON THE AUTOMOTIVE INDUSTRY

Yıl 2019, Cilt: 6 Sayı: 1, 121 - 133, 30.01.2019

Öz

ABSTRACT

Objective: The aim of this research is to determine consumer's car brand perceptions by using Electroencephalography- EEG device according to the determined comfort, security, fuel saving, stylish design, quality service, prestige, performance, durability and quality variables.

Materials and Methods: The aim of this research is to determine consumer's car brand perceptions by using Electroencephalography- EEG device according to the determined comfort, security, fuel saving, stylish design, quality service, prestige, performance, durability and quality variables. A 10-channel EEG device was used in the study. The work we conducted to determine the automobile brand perceptions of consumers was applied to 30 participants from the students and academicians at Fırat University. Participants were determined on a voluntary basis and necessary information was provided to each participant before work. car brand will be used in research to determine the best-selling car brand in Turkey 6 passenger has been identified. In this study, it will be determined how consumers perceive car brands. Participants were presented with PowerPoint presentations along with 9 identified dimensions of 6 brands. Each experiment lasted a total of 180 seconds. The responses of the participants were determined with the EEG device and processed into the prepared form.

Results: According to the results of this research, it was seen that the participants matched the determined dimensions most with Volkswagen and Toyota brands.

Conclusion: By using neuromarketing methods, we found that consumers are moving away from rationality. Besides intangible and emotional concepts are becoming more prominent for thae consumers. Even though it does not give a general judgment or conclusion of the perception of car brands, the results of this research provide important clues within the framework of the sample of the researcher. As consumer behaviors and preferences arise due to many factors, it is likely that different results will emerge in a wider range of economic, social, psychologically and culturally through different places, times and countries. Depending on these, different levels of perception may arise.

Kaynakça

  • Adhami, M. (2013). Using neuromarketing to discover how we really feel about apps. International Journal of Mobile Marketing, 8(1), 95-103.
  • Ariely, D.,& Berns,G.(2010). Neuromarketing: The Hope And Hype Of Neuroimaging İn Business, Nature Reviews Neuroscience, Vol.11, (284-292).
  • Aytekin, P. & Kahraman, A. (2014). Pazarlamada Yeni Bir Araştırma Yaklaşımı: Nöropazarlama, Journal Of Management Marketing And Logistics (JMML), Volume: 1 Issue:1 s.48-62. 48-62.
  • Balconi, M., Stumpo, B., & Leanza, F. (2014). Advertising, brand and neuromarketing or how consumer brain works. Neuropsychological Trends, 16 (November), 15-21.
  • Bastiaansen, M., & Straatman, S., & Driessen, E., & Mitas, O., & Stekelenburg, J., & Wang, L. (2016). My destination in your brain: A novel neuromarketing approach for evaluating the effectiveness of destination marketing. Journal of Destination Marketing & Management.
  • Brown, C., & Randolph, A. B., & Burkhalter, J. N. (2012). The story of taste: Using EEGs and self-reports to understand consumer choice. The Kennesaw Journal of Undergraduate Research, 2(1), 5.
  • Da Rocha, A. F. & Rocha, F. T. & Armuda, L. H. (2013). A Neuromarketing Study of Consumer Satisfaction.
  • Dimpfel, W. (2015). Neuromarketing: Neurocode-Tracking in Combination with Eye-Tracking for Quantitative Objective Assessment of TV Commercials. Journal of Behavioral and Brain Science, 5(04), 137.
  • Doborjeh, Z. G., & Doborjeh, M. G., & Kasabov, N. (2017). Attentional bias pattern recognition in spiking neural networks from spatio-temporal EEG data. Cognitive Computation, 1-14.
  • Estrada, E., & Nazeran, H., & Nava, P., & Behbehani, K., & Burk, J., & Lucas, E. (2004, September). EEG feature extraction for classification of sleep stages. In Engineering in Medicine and Biology Society, 2004. IEMBS'04. 26th Annual International Conference of the IEEE (Vol. 1, pp. 196-199). IEEE.
  • Hammou, K., Galib, & M., Melloul, J. (2013), The Contributions of Neuromarketing in Marketing, Journal of Management Research, Volume:5, Issue:4, 20-33.
  • Horská, E., & Berčík, J. (2014). The influence of light on consumer behavior at the food market. Journal of Food Products Marketing, 20(4), 429-440.
  • Khushaba, R. & N., Wise, & C., Kodagoda, & S., Louviere, J., & Kahn, B. E., & Townsend, C. (2013). Consumer neuroscience: Assessing the brain response to marketing stimuli using electroencephalogram (EEG) and eye tracking. Expert Systems with Applications, 40(9), 3803-3812.
  • Lee, E. J., & Kwon, G., & Shin, H. J., & Yang, S., & Lee, S., & Suh, M. (2014). The spell of green: Can frontal EEG activations identify green consumers?. Journal of Business Ethics, 122(3), 511-521.
  • Lewis, D. & Bridger, D., (2005). Market Researchers Make İncreasing Use Of Brain İmaging, Advances in Clinical Neuroscience & Rehabilitation, 5 (3) (2005 July/August)
  • Morin C. (2011), Neuromarketing: The New Science of Consumer Behaviour, Volume 48, Issue 2, pp 131-135
  • Murugappan, M., & Murugappan, S., & Gerard, C. (2014, March). Wireless EEG signals based neuromarketing system using Fast Fourier Transform (FFT). In Signal Processing & its Applications (CSPA), 2014 IEEE 10th International Colloquium on (pp. 25-30). IEEE.
  • Nomura, T., & Mitsukura, Y. (2015). EEG-based detection of TV commercials effects. Procedia Computer Science, 60, 131-140.
  • Ohme, R., & Reykowska, D., & Wiener, D., & Choromanska, A. (2009). Analysis of neurophysiological reactions to advertising stimuli by means of EEG and galvanic skin response measures. Journal of Neuroscience, Psychology, and Economics, 2(1), 21.
  • Sands, F.Stephen, (2009), Sample Size Analysis for Brain Collection (EEG) Methodologies,WhitePaper,October2009. (http://www.sandsresearch.com/assets/white-paper.pdf)
  • Sharma, Naman & Koc, Macit & Kishor, Jugal, Neuromarketing - A Step Ahead of Traditional Marketing Tools (February 10, 2014). Proceedings of 3rd International Conference on Management Innovations (ICMI-2014). Available at SSRN: https://ssrn.com/abstract=2406314 or http://dx.doi.org/10.2139/ssrn.2406314
  • Şimşek , A. İhsan. (2016). Tüketicilerin Otomobil Markalari Üzerindeki Algılarının Nöropazarlama Açisindan Ölçülmesi: Elaziğ Ilinde Yapilan Deneysel Bir Çalişma, Fırat Ünivesitesi, SBE Yayınlanmamış Yüksek Lisans Tezi, Elazığ.
  • Taşkın, Ç., Koç, E., & Boz, H. (2017). Perceptual Image of Conflict-Ridden Destinations: An EEG and Eye Tracker Analysis. Business & Economics Research Journal, 8(3).
  • Yadava, M., Kumar, P., Saini, R., Roy, P. P., & Dogra, D. P. (2017). Analysis of EEG signals and its application to neuromarketing. Multimedia Tools and Applications, 76(18), 19087-19111.
  • Yılmaz, B., & Korkmaz, S., & Arslan, D. B., & Güngör, E., & Asyalı, M. H. (2014). Like/dislike analysis using EEG: determination of most discriminative channels and frequencies. Computer methods and programs in biomedicine, 113(2), 705-713.

MEASURING CONSUMER BRAND PERCEPTIONS IN TERMS OF NEUROMARKETING BY USING THE EEG METHOD: AN EXPERIMENTAL STUDY ON THE AUTOMOTIVE INDUSTRY

Yıl 2019, Cilt: 6 Sayı: 1, 121 - 133, 30.01.2019

Öz

Amaç: Bu araştırmanın amacı, belirlediğimiz konfor, güvenlik, yakıt tasarrufu, şık tasarım, kaliteli
hizmet, prestij, performans, dayanıklılık ve kalite değişkenlerine göre Electroencephalography- EEG cihazı
kullanılarak tüketicilerin otomobil marka algılarının tespit edilmesidir.
Gereç ve Yöntem: Araştırmada 10 kanallı EEG cihazı kullanılmıştır. Tüketicilerin otomobil marka
algılarını belirlemek amacıyla yaptığımız çalışmamız Fırat Üniversitesi’ndeki öğrenci ve akademisyenlerden
oluşan 30 katılımcıya uygulanmıştır. Katılımcılar gönüllülük esasına göre belirlenmiş ve çalışmadan önce
katılımcıların her birine çalışma ile ilgili gerekli bilgilendirmeler yapılmıştır. Araştırmada kullanılacak otomobil
markalarının belirlenmesi amacıyla Türkiye’de en çok satılan 6 binek otomobil markası belirlenmiştir. Bu
çalışmada tüketicilerin otomobil marka algıları incelenerek tüketicilerin otomobil markalarını nasıl algıladıkları
tespit edilecektir. Katılımcılara 6 marka tespit edilen 9 boyut ile birlikte powerpoint sunusu şeklinde
gösterilmiştir. Her bir deney toplam 180 saniye sürmüştür. Katılımcıların verdikleri tepkiler EEG cihazı
vasıtasıyla tespit edilerek hangi marka ve boyuta hangi düzeyde tepki verdikleri hazırlanan forma işlenmiştir.
Bulgular: Bu araştırmanın sonuçlarına göre katılımcıların belirlenen boyutları en çok Volkswagen ve
Toyota markaları ile eşleştirdiği görülmüştür.
Sonuç: Tüketicilerin rasyonellikten uzaklaştığı ve şık tasarım, kaliteli hizmet, prestij gibi daha
duygusal ve soyut kavramların ön plana çıktığı tespit edilmiştir. Bu araştırmanın sonuçları, otomobil
markalarının algılanması ile ilgili olarak genel bir yargı ya da hüküm doğurmasa da araştırmanın örneklemi
çerçevesinde elde edilen sonuçların analiz ve yorumlanmasına dayandığından en azından bu konuda önemli
ipuçları sunmaktadır. Tüketici davranış ve tercihleri birçok faktöre bağlı olarak ortaya çıktığından daha geniş
örneklemlerde yada ekonomik, sosyal, psikolojik ve kültürel olarak farklı yer, zaman ve ülkeler boyutunda
farklı sonuçların ortaya çıkması muhtemeldir. Bunlara bağlı olarak farklı algı düzeyleri ortaya çıkabilir.

Kaynakça

  • Adhami, M. (2013). Using neuromarketing to discover how we really feel about apps. International Journal of Mobile Marketing, 8(1), 95-103.
  • Ariely, D.,& Berns,G.(2010). Neuromarketing: The Hope And Hype Of Neuroimaging İn Business, Nature Reviews Neuroscience, Vol.11, (284-292).
  • Aytekin, P. & Kahraman, A. (2014). Pazarlamada Yeni Bir Araştırma Yaklaşımı: Nöropazarlama, Journal Of Management Marketing And Logistics (JMML), Volume: 1 Issue:1 s.48-62. 48-62.
  • Balconi, M., Stumpo, B., & Leanza, F. (2014). Advertising, brand and neuromarketing or how consumer brain works. Neuropsychological Trends, 16 (November), 15-21.
  • Bastiaansen, M., & Straatman, S., & Driessen, E., & Mitas, O., & Stekelenburg, J., & Wang, L. (2016). My destination in your brain: A novel neuromarketing approach for evaluating the effectiveness of destination marketing. Journal of Destination Marketing & Management.
  • Brown, C., & Randolph, A. B., & Burkhalter, J. N. (2012). The story of taste: Using EEGs and self-reports to understand consumer choice. The Kennesaw Journal of Undergraduate Research, 2(1), 5.
  • Da Rocha, A. F. & Rocha, F. T. & Armuda, L. H. (2013). A Neuromarketing Study of Consumer Satisfaction.
  • Dimpfel, W. (2015). Neuromarketing: Neurocode-Tracking in Combination with Eye-Tracking for Quantitative Objective Assessment of TV Commercials. Journal of Behavioral and Brain Science, 5(04), 137.
  • Doborjeh, Z. G., & Doborjeh, M. G., & Kasabov, N. (2017). Attentional bias pattern recognition in spiking neural networks from spatio-temporal EEG data. Cognitive Computation, 1-14.
  • Estrada, E., & Nazeran, H., & Nava, P., & Behbehani, K., & Burk, J., & Lucas, E. (2004, September). EEG feature extraction for classification of sleep stages. In Engineering in Medicine and Biology Society, 2004. IEMBS'04. 26th Annual International Conference of the IEEE (Vol. 1, pp. 196-199). IEEE.
  • Hammou, K., Galib, & M., Melloul, J. (2013), The Contributions of Neuromarketing in Marketing, Journal of Management Research, Volume:5, Issue:4, 20-33.
  • Horská, E., & Berčík, J. (2014). The influence of light on consumer behavior at the food market. Journal of Food Products Marketing, 20(4), 429-440.
  • Khushaba, R. & N., Wise, & C., Kodagoda, & S., Louviere, J., & Kahn, B. E., & Townsend, C. (2013). Consumer neuroscience: Assessing the brain response to marketing stimuli using electroencephalogram (EEG) and eye tracking. Expert Systems with Applications, 40(9), 3803-3812.
  • Lee, E. J., & Kwon, G., & Shin, H. J., & Yang, S., & Lee, S., & Suh, M. (2014). The spell of green: Can frontal EEG activations identify green consumers?. Journal of Business Ethics, 122(3), 511-521.
  • Lewis, D. & Bridger, D., (2005). Market Researchers Make İncreasing Use Of Brain İmaging, Advances in Clinical Neuroscience & Rehabilitation, 5 (3) (2005 July/August)
  • Morin C. (2011), Neuromarketing: The New Science of Consumer Behaviour, Volume 48, Issue 2, pp 131-135
  • Murugappan, M., & Murugappan, S., & Gerard, C. (2014, March). Wireless EEG signals based neuromarketing system using Fast Fourier Transform (FFT). In Signal Processing & its Applications (CSPA), 2014 IEEE 10th International Colloquium on (pp. 25-30). IEEE.
  • Nomura, T., & Mitsukura, Y. (2015). EEG-based detection of TV commercials effects. Procedia Computer Science, 60, 131-140.
  • Ohme, R., & Reykowska, D., & Wiener, D., & Choromanska, A. (2009). Analysis of neurophysiological reactions to advertising stimuli by means of EEG and galvanic skin response measures. Journal of Neuroscience, Psychology, and Economics, 2(1), 21.
  • Sands, F.Stephen, (2009), Sample Size Analysis for Brain Collection (EEG) Methodologies,WhitePaper,October2009. (http://www.sandsresearch.com/assets/white-paper.pdf)
  • Sharma, Naman & Koc, Macit & Kishor, Jugal, Neuromarketing - A Step Ahead of Traditional Marketing Tools (February 10, 2014). Proceedings of 3rd International Conference on Management Innovations (ICMI-2014). Available at SSRN: https://ssrn.com/abstract=2406314 or http://dx.doi.org/10.2139/ssrn.2406314
  • Şimşek , A. İhsan. (2016). Tüketicilerin Otomobil Markalari Üzerindeki Algılarının Nöropazarlama Açisindan Ölçülmesi: Elaziğ Ilinde Yapilan Deneysel Bir Çalişma, Fırat Ünivesitesi, SBE Yayınlanmamış Yüksek Lisans Tezi, Elazığ.
  • Taşkın, Ç., Koç, E., & Boz, H. (2017). Perceptual Image of Conflict-Ridden Destinations: An EEG and Eye Tracker Analysis. Business & Economics Research Journal, 8(3).
  • Yadava, M., Kumar, P., Saini, R., Roy, P. P., & Dogra, D. P. (2017). Analysis of EEG signals and its application to neuromarketing. Multimedia Tools and Applications, 76(18), 19087-19111.
  • Yılmaz, B., & Korkmaz, S., & Arslan, D. B., & Güngör, E., & Asyalı, M. H. (2014). Like/dislike analysis using EEG: determination of most discriminative channels and frequencies. Computer methods and programs in biomedicine, 113(2), 705-713.
Toplam 25 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Makaleler
Yazarlar

Atilla Yücel 0000-0002-8052-3236

Ahmed İhsan Şimşek

Yayımlanma Tarihi 30 Ocak 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 6 Sayı: 1

Kaynak Göster

APA Yücel, A., & Şimşek, A. İ. (2019). MEASURING CONSUMER BRAND PERCEPTIONS IN TERMS OF NEUROMARKETING BY USING THE EEG METHOD: AN EXPERIMENTAL STUDY ON THE AUTOMOTIVE INDUSTRY. Avrasya Sosyal Ve Ekonomi Araştırmaları Dergisi, 6(1), 121-133.