TÜKETİCİ SİNİRBİLİMİ KAVRAMININ BİBLİYOMETRİK ANALİZ YÖNTEMİ İLE İNCELENMESİ

Abstract

Bu çalışmanın amacı; dünyada 2003-2023 yılları arasında, Web of Science (WoS) veri tabanında yer alan ve “consumer neuroscience” kavramını konu alan akademik çalışmaları bibliyometrik analiz yöntemi ile inceleyerek tüketici sinirbilimi konusunun tematik gelişimini bilimsel haritalama yöntemiyle ortaya çıkarmaktır. Ulaşılan makale verilerinin Vosviewer programı aracılığıyla bibliyometrik analizi gerçekleştirilmiştir. Tüketici sinirbilimi kavramı ile olası diğer kavramlar arasındaki ağ ilişkisi belirlenerek kümelendirme ve görselleştirme aracılığıyla hipotetik modelin alt yapısı oluşturulmuştur. Bu doğrultuda, tüketici sinirbilimi alanındaki araştırma eğilimlerinin belirlenmesi, ilgili yazındaki araştırmaların spesifik yönlerinin tanınması ve aynı zamanda alandaki boşlukları tespit ederek gelecekte yapılması planlanan çalışmalara katkı sağlaması hedeflenmiştir. Analiz sonucunda 32 alt unsura sahip 6 küme ve kelime bazlı ilişki ağları tespit edilmiştir. Bulunan kümeler sırasıyla; tüketici sinirbiliminin kapsamı, tüketici sinirbiliminin gelişim süreci, tüketici sinirbilimi araştırmalarında kullanılan teknikler, satın alma niyeti araştırmaları, makine öğrenimi, sanal gerçeklik olarak isimlendirilmiştir. Nöropazarlama, EEG, fMRI, tüketici davranışı, duygu, reklamcılık ve nöroekonomi kavramlarının ilişki ağında öne çıktığı tespit edilmiştir.

Keywords

• tüketici sinirbilimi
• nöropazarlama
• bibliyometrik analiz

Examining of the Consumer Neuroscience Concept with Bibliometric Analysis Method

Abstract

The aim of the study is to reveal the thematic development of the subject of consumer neuroscience with the scientific mapping method by examining the academic studies on the concept of “consumer neuroscience” in the Web of Science (WoS) database between 2003 and 2023 in the world, with the bibliometric analysis method. The article data obtained as a result of the research were discussed and bibliometric analysis was carried out with the Vosviewer program. During the analysis process, the network relationship between the concept of consumer neuroscience and other possible concepts was determined and the infrastructure of the hypothetical model was created through clustering and visualization. It is aimed to identify research trends in the field of consumer neuroscience, to recognize specific aspects of the research in the relevant literature, and to contribute to future studies by identifying gaps in the field. As a result of the analysis, 6 clusters and word-based relationship networks with 32 sub-elements were identified. The clusters found are respectively; The scope of consumer neuroscience is named as the development process of consumer neuroscience, techniques used in consumer neuroscience research, purchase intention research, machine learning, virtual reality. It has been determined that the concepts of neuromarketing, EEG, fMRI, consumer behavior, emotion, advertising and neuroeconomics are prominent topics in the relationship network.

Keywords

• consumer neuroscience
• neuromarketing
• bibliometrics analysis

References

1. Acedo, F. J., Barroso, C., Casanueva, C., Galán, J. L. (2006). Co‐authorship in management and organizational studies: An empirical and network analysis. Journal of management studies, 43(5), 957-983.
2. Agarwal, S. (2015). Introduction to neuromarketing and consumer neuroscience. Journal of Consumer Marketing, 32(4), 302-303.
3. Alsharıf, A. H., Md Salleh, N. Z., Baharun, R. (2020). Bibliometric analysis. Journal of Theoretical and Applied Information Technology, 98(15), 2948-2962.
4. Alvino, L., Constantinides, E., van der Lubbe, R. H. (2021). Consumer neuroscience: Attentional preferences for wine labeling reflected in the posterior contralateral negativity. Frontiers in Psychology, (12), 688713.
5. Alvino, L., Pavone, L., Abhishta, A., Robben, H. (2020). Picking your brains: Where and how neuroscience tools can enhance marketing research. Frontiers in Neuroscience, (14), 577666.
6. Ariely, D., Berns, G. (2010). Neuromarketing: The hope and hype of neuroimaging in business. Nature Reviews Neuroscience, (11), 284-292.
7. Babiloni, F. (2012). Consumer nueroscience: A new area of study for biomedical engineers. IEEE Pulse, 3(3), 21-23.
8. Balconi, M. & Sansone, M. (2021). Neuroscience and consumer behavior: Where to now?. Frontiers in Psychology, (12), 705850.

9. Barth, A., Marx, W., Bornmann, L., Mutz, R. (2014). On the origins and the historical roots of the Higgs boson research from a bibliometric perspective. The European Physical Journal Plus, (129), 1-13.
10. Bell, L., Vogt, J., Willemse, C., Routledge, T., Butler, L. T., Sakaki, M. (2018). Beyond self-report: A review of physiological and neuroscientific methods to investigate consumer behavior. Frontiers in Psychology, (9), 1655.
11. Berčík, J., Neomániová, K., Gálová, J., Mravcová, A. (2021). Consumer neuroscience as a tool to monitor the impact of aromas on consumer emotions when buying food. Applied Sciences, 11(15), 6692.
12. Berčík, J., Neomániová, K., Mravcová, A., Gálová, J. (2021). Review of the potential of consumer neuroscience for aroma marketing and ıts ımportance in various segments of services. Applied Sciences, 11(16), 7636.
13. Berčík, J., Neomániová, K., Mušinská, K., Pšurný, M. (2022). Use of consumer neuroscience in the choice of aromatisation as part of the shopping atmosphere and a way to increase sales volume. Applied Sciences, 12(14), 7069.
14. Bilgin, O. K. & Dağlı, Ö. (2022). Reklam çekicilikleri, marka hatırlanırlığı ve uyarılma ilişkisinin deri tepkisi ile incelenmesi. Akdeniz Üniversitesi İletişim Fakültesi Dergisi, (38), 178-193.
15. Boz, H. (2020). Nöropazarlama araçları finansal piyasalara nasıl adapte edilir: Nörofinans. Finans Ekonomi ve Sosyal Araştırmalar Dergisi, 5(3), 518-528.
16. Byrne, A., Bonfiglio, E., Rigby, C., Edelstyn, N. (2022). A systematic review of the prediction of consumer preference using EEG measures and machine-learning in neuromarketing research. Brain Informatics, 9(1), 1-23.
17. Camerer, C. F., Loewenstein, G., Prelec, D. (2004). Neuroeconomics: Why economics needs brains. Scand J Econ, 106(3), 555-579.
18. Cao, C. C. & Reimann, M. (2020). Data triangulation in consumer neuroscience: Integrating functional neuroimaging with meta-analyses, psychometrics, and behavioral data. Frontiers in Psychology, 5(11), 550204.
19. Cardoso, L., Chen, M. M., Araújo, A., de Almeida, G. G. F., Dias, F., Moutinho, L. (2022). Accessing neuromarketing scientific performance: Research gaps and emerging topics. Behavioral Sciences, 12(2), 55.
20. Cayolla, R. (2022). Communicating the value of fan identity in the sport industry: Commentary on consumer neuroscience possible research ideas. International Journal of Sport Communication, 1(aop), 1-5.
21. Cerf, M. (2017). Methods. M. Cerf, M. Garcia-Garcia (Ed.), Consumer Neuroscience içinde (80-120. ss.), MIT Press.
22. Cherubino, P., Martinez-Levy, A. C., Caratu, M., Cartocci, G., Di Flumeri, G., Modica, E., Rossi, D., Mancini, M., Trettel, A. (2019). Consumer behaviour through the eyes of neurophysiological measures: State-of-the-art and future trends. Computational Intelligence and Neuroscience, 2019, 1976847.
23. Clark, K. R., Leslie, K. R., Garcia-Garcia, M., Tullman, M. L. (2018). How advertisers can keep mobile users engaged and reduce video-ad blocking: Best practices for video-ad placement and delivery based on consumer neuroscience measures. Journal of Advertising Research, 58(3), 311-325.
24. Ćosić, D. (2016). Neuromarketing in market research. Interdisciplinary Description of Complex Systems: INDECS, 14(2), 139-147.
25. Çakır, M. P., Çakar, T., Girişken, Y., Yurdakul, D. (2018). An investigation of the neural correlates of purchase behavior through fNIRS. European Journal of Marketing, 52(1/2), 224-243.
26. Çınar Altıntaş, F., Altıntaş, M. H., Işın, F. B. (2022). Örgütsel yaratıcılık kavramının bibliyometrik analiz yöntemi ile incelenmesi. Journal of Academic Value Studies, 8(4), 348-361.
27. Daugherty, T., Hoffman, E., Kennedy, K. (2016). Research in reverse: Ad testing using an inductive consumer neuroscience approach. Journal of Business Research, 69(8), 3168-3176.
28. De-Frutos-Arranz, S. & López, M. F. B. (2022). The state of the art of emotional advertising in tourism: A neuromarketing perspective. Tourism Review International, 26(2), 139-162.
29. Deppe, M., Schwindt, W., Kugel, H., Plassmann, H., Kenning, P. (2005). Nonlinear responses within the medial prefrontal cortex reveal when specific implicit information influences economic decision making. Journal of neuroimaging, 15(2), 171-182.
30. Dini, H., Simonetti, A., Bigne, E., Bruni, L. E. (2022). EEG theta and N400 responses to congruent versus incongruent brand logos. Scientific Reports, 12(1), 4490.
31. Ellegaard, O. & Wallin, J.A. (2015). The bibliometric analysis of scholarly production: How great is the impact?. Scientometrics, 105(3), 1809-1831.
32. Erk, S., Spitzer, M., Wunderlich, A. P., Galley, L., Walter, H. (2002). Cultural objects modulate reward circuitry. NeuroReport, 13(18), 2499-2503.
33. Fisher, C. E., Chin, L., Klitzman, R. (2010). Defining neuromarketing: Practices and professional challenges. Harvard Review of Psychiatry, 18(4), 230-237.
34. Girişken, Y. & Çakar, T. (2016). Detecting the effect of voice-over in tv ads via optic brain imaging (fnirs) and in-depth interview methods. İstanbul Üniversitesi Siyasal Bilgiler Fakültesi Dergisi, (55), 43-53.
35. Goodman, A. M., Wang, Y., Kwon, W. S., Byun, S. E., Katz, J. S., Deshpande, G. (2017). Neural correlates of consumer buying motivations: A 7T functional magnetic resonance imaging (fMRI) study. Frontiers in Neuroscience, (11), 512.
36. Harris, J. M., Ciorciari, J., Gountas, J. (2018). Consumer neuroscience for marketing researchers. Journal of Consumer Behaviour, 17(3), 239-252.
37. Harris, J. M., Ciorciari, J., Gountas, J. (2019). Consumer neuroscience and digital/social media health/social cause advertisement effectiveness. Behavioral Sciences, 9(4), 42.
38. Herrando, C., Jimenez-Martinez, J., Martín-De Hoyos, M. J., Asakawa, K., Yana, K. (2023). Emotional responses in online social interactions: The mediating role of flow. Asia Pacific Journal of Marketing and Logistics, 35(7), 1599-1617.
39. Hsu, M. & Yoon, C. (2015). The neuroscience of consumer choice. Current Opinion in Behavioral Sciences, (5), 116-121.
40. Janssen, M. & Hamm, U. (2014). Governmental and private certification labels for organic food: Consumer attitudes and preferences in Germany. Food Policy, (49), 437-448.
41. Javor, A., Kindermann, H., Koschutnig, K., Ischebeck, A. (2018). The neural correlates of trustworthiness evaluations of faces and brands: Implications for behavioral and consumer neuroscience. European Journal of Neuroscience, 48(6), 2322-2332.
42. Javor, A., Koller, M., Lee, N., Chamberlain, L., Ransmayr, G. (2013) Neuromarketing and consumer neuroscience: Contributions to neurology. BMC Neurology (13), 13.
43. Karmarkar, U. R. & Plassmann, H., (2019). Consumer neuroscience: Past, present, and future. Organizational Research Methods, 22(1), 174-195.
44. Karmarkar, U. R. & Yoon, C. (2016). Consumer neuroscience: Advances in understanding consumer psychology. Current Opinion in Psychology, (10), 160-165.
45. Kenning, P., Linzmajer, M. (2011). Consumer neuroscience: An overview of an emerging discipline with implications for consumer policy. Journal für Verbraucherschutz und Lebensmittelsicherheit, (6), 111-125.
46. Khusbaba, R.N., Kodagoda, S., Wise, C. 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.
47. Kim, D. J., Ferrin, D. L., Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544-564.
48. Knutson, B., Rick, S., Wimmer, G. E., Prelec, D., Loewenstein, G. (2007). Neural predictors of purchases. Neuron, 53(1), 147-156.
49. Krampe, C., Strelow, E., Haas, A., Kenning, P. (2018). The application of mobile fNIRS to “shopper neuroscience” - first insights from a merchandising communication study. European Journal of Marketing, 52(1/2), 244-259.
50. Labban, A., Ma, Y., Dube, L. (2021). A neurobehavioral account of differential consumer responses to price and in-store display between un/healthy food. European Journal of Marketing, 55(11), 2988-3009.
51. Lajante, M., Droulers, O., Dondaine, T., Amarantini, D. (2012). Opening the “black box” of electrodermal activity in consumer neuroscience research. Journal of Neuroscience, Psychology, and Economics, 5(4), 238-249.
52. Leanza, F. (2017). Consumer neuroscience: The traditional and VR TV commercial. Neuropsychological trends, 21(1), 81-90.
53. Lee, N., Brandes, L., Chamberlain, L., Senior, C. (2017). This is your brain on neuromarketing: Reflections on a decade of research. Journal of Marketing Management, 33(11-12), 878-892.
54. Levy, B., Medina, A. M., Manove, E., Weiss, R. D. (2011). The characteristics of a discrete mood episode, neuro-cognitive impairment and re-hospitalization in bipolar disorder. Journal of Psychiatric Research, 45(8), 1048-1054.
55. Li, S., Walters, G., Packer, J., Scott, N. (2018). Using skin conductance and facial electromyography to measure emotional responses to tourism advertising. Curr. Issues Tourism, (21), 1761-1783.
56. Lim, W. M. (2018). What will business-to-business marketers learn from neuro-marketing? Insights for business marketing practice. Journal of Business-to-Business Marketing, 25(3), 251-259.
57. Lindstrom, M. (2009). Buy.ology. Optimist Yayıncılık.
58. Linzmajer, M., Hubert, M., Hubert, M. (2021). It’s about the process, not the result: An fMRI approach to explore the encoding of explicit and implicit price information. Journal of Economic Psychology, (86), 102403.
59. Liu, Y., Zhao, R., Xiong, X., Ren, X. (2023). A bibliometric analysis of consumer neuroscience towards sustainable consumption. Behavioral Sciences, 13(4), 298.
60. Lobb, A. E., Mazzocchi, M., Traill, W. B. (2007). Modelling risk perception and trust in food safety information within the theory of planned behaviour. Food Quality and Preference, 18(2), 384-395.
61. Luhmann, N. (2000). Familiarity, confidence, trust: Problems and alternatives. Trust: Making and Breaking Cooperative Relations, 6(1), 94-107.
62. Mansor, A. A., Isa, S. M., Noor, S. S. M. (2021). P300 and decision-making in neuromarketing. Neuroscience Research Notes, 4(3), 21-26.
63. Martínez-López, F. J., Merigó, J. M., Valenzuela-Fernández, L., Nicolás, C. (2018). Fifty years of the European Journal of Marketing: A bibliometric analysis. European Journal of Marketing, 52(1/2), 439-468.
64. McClure, S. M., Li, J., Tomlin, D., Cypert, K. S., Montague, L. M., Montague, P. R. (2004). Neural correlates of behavioral preference for culturally familiar drinks. Neuron, 44(2), 379-387.
65. Morin, C. & Renvoise, P. (2019). Beyindeki ikna kodu. Maltepe Üniversitesi Kitapları.
66. Morin, C. (2011). Neuromarketing: The new science of consumer behavior. Proceedings of the Symposıum: Consumer Culture in Global Perspective içinde (131-135. ss.), Springer Science+Business Media.
67. Niedziela, M. M. & Ambroze, K. (2021). The future of consumer neuroscience in food research. Food Quality and Preference, (92), 104124.
68. Ohme, R., Reykowska, D., Wiener, D., Choromanska, A. (2010). Application of frontal EEG asymmetry to advertising research. Journal of Economic Psychology, 31(5), 785-793.
69. Oliveira, P. M., Guerreiro, J., Rita, P. (2022). Neuroscience research in consumer behavior: A review and future research agenda. International Journal of Consumer Studies, 46(5), 2041-2067.
70. Ortigueira-Sánchez, L. C. & Risco-Martínez, S. L. (2021). A bibliometric analysis on the state of the art of neuromarketing research in Web of Science. Gecontec: Revista Internacional De Gestión Del Conocimiento Y La Tecnología, 9(2), 1-21.
71. Paulus, M. P. & Frank, L. R. (2003). Ventromedial prefrontal cortex activation is critical for preference judgments. Neuroreport, 14(10), 1311-1315.
72. Plassmann, H., Ambler, T., Braeutigam, S., Kenning, P. (2007). What can advertisers learn from neuroscience?. International Journal of Advertising, 26(2), 151-175.
73. Plassmann, H., O’Doherty, J., Shiv, B., Rangel, A. (2008). Marketing actions can modulate neural representations of experienced pleasantness. Proceedings of the National Academy of Sciences, (105), 1050-1054.
74. Plassmann, H., Ramsøy, T. Z., Milosavljevic, M. (2012). Branding the brain: A critical review and outlook. Journal of Consumer Psychology, 22(1), 18-36.
75. Plassmann, H., Venkatraman, V., Huettel, S., Yoon, C. (2015). Consumer neuroscience: Applications, challenges, and possible solutions. Journal of Marketing Research, 52(4), 427-435.
76. Pozharliev, R., Rossi, D., De Angelis, M. (2022). A picture says more than a thousand words: Using consumer neuroscience to study instagram users’ responses to influencer advertising. Psychology & Marketing, 39(7), 1336-1349.
77. Pritchard, A. 1969. Statistical bibliography or bibliometrics. Journal of Documentation, 25(4), 344-349.
78. Quaresima, V. & Ferrari, M. (2019). Functional near-infrared spectroscopy (fNIRS) for assessing cerebral cortex function during human behavior in natural/social situations: A concise review. Organizational Research Methods, 22(1), 46-68.
79. Ramsøy, T. Z. (2019). Building a foundation for neuromarketing and consumer neuroscience research: How researchers can apply academic rigor to the neuroscientific study of advertising effects. Journal of Advertising Research, 59(3), 281-294.
80. Ramsøy, T. Z., Skov, M., Christensen, M. K., Stahlhut, C. (2018). Frontal brain asymmetry and willingness to pay. Frontiers in Neuroscience, (12), 138.
81. Reimann, M., Castaño, R., Zaichkowsky, J., Bechara, A. (2012). How we relate to brands: Psychological and neurophysiological insights into consumer-brand relationships. Journal of Consumer Psychology, 22(1), 128-142.
82. Rodríguez, V. J. C., Antonovica, A., Martín, D. L. S. (2023). Consumer neuroscience on branding and packaging: A review and future research agenda. International Journal of Consumer Studies, 1-26.
83. Rúa-Hidalgo, I., Galmes-Cerezo, M., Cristofol-Rodríguez, C., Aliagas, I. (2021). Understanding the emotional impact of gifs on instagram through consumer neuroscience. Behavioral Sciences, 11(8), 108.
84. Saffari, F., Kakaria, S., Bigné, E., Bruni, L. E., Zarei, S., Ramsøy, T. Z. (2023). Motivation in the metaverse: A dual-process approach to consumer choices in a virtual reality supermarket. Frontiers in Neuroscience, (17), 1062980.
85. Sánchez-Fernández, J., Casado-Aranda, L. A., Bastidas-Manzano, A. B. (2021). Consumer neuroscience techniques in advertising research: A bibliometric citation analysis. Sustainability, 13(3), 1589.
86. Sánchez-Núñez, P., Cobo, M. J., Vaccaro, G., Peláez, J. I., Herrera-Viedma, E. (2021). Citation classics in consumer neuroscience, neuromarketing and neuroaesthetics: Identification and conceptual analysis. Brain Sciences, 11(5), 548.
87. Sanfey, A. G., Loewenstein G, McClure, S.M., Cohen, J.D. (2006). Neuroeconomics: Crosscurrents in research on decision-making. Trends in Cognitive Sciences, (10), 108-116.
88. Sargent, A., Watson, J., Topoglu, Y., Ye, H., Zhong, W., Ayaz, H., Suri, R. (2020). Reliability of consumer choices for conflicting price promotions. H. Ayaz (Ed.), Advances in Neuroergonomics and Cognitive Engineering: Proceedings of the AHFE 2019 International Conference on Neuroergonomics and Cognitive Engineering, and the AHFE International Conference on Industrial Cognitive Ergonomics and Engineering Psychology içinde (103-109. ss.), Springer International Publishing.
89. Schaefer, A., Buratto, L. G., Goto, N., Brotherhood, E. V. (2016). The feedback-related negativity and the P300 brain potential are sensitive to price expectation violations in a virtual shopping task. Plos One, 11(9), e0163150.
90. Schaefer, M. & Rotte, M. (2007). Favorite brands as cultural objects modulate reward circuit. Neuroreport, (18), 141-145.
91. Schmitt, B. (2012). The consumer psychology of brands. Journal of consumer Psychology, 22(1), 7-17.
92. Sedighi, M. (2016). Application of word co-occurrence analysis method in mapping of the scientific fields (case study: the field of Informetrics). Library Review, 65(1/2), 52-64.
93. Smidts, A., Hsu, M., Sanfey, A.G., Boksem, M. A., Ebstein, R. B., Huettel, S. A., Kable, J. W., Karmarkar, U. R., Kitayama, S., Knutson, B., Liberzon, I., Lohrenz, T., Stallen, M., Yoon, C. (2014). Advancing consumer neuroscience. Marketing Letters, (25), 257-267.
94. Smith, D. V. & Huettel, S. A. (2010). Decision neuroscience: Neuroeconomics. Wiley Interdisciplinary Reviews: Cognitive Science, 1(6), 854-871.
95. Stanton, S. J., Sinnott-Armstrong, W., Huettel, S. A. (2017). Neuromarketing: Ethical implications of its use and potential misuse. J Bus Ethics, (144), 799-811.
96. Stillman, P., Lee, H., Deng, X., Unnava, H. R., Fujita, K. (2020). Examining consumers’ sensory experiences with color: A consumer neuroscience approach. Psychology & Marketing, 37(7), 995-1007.
97. Ungureanu, F., Lupu, R. G., Cadar, A., Prodan, A. (2017, Ekim). Neuromarketing and visual attention study using eye tracking techniques. 2017 21st International Conference on System Theory, Control and Computing (ICSTCC) içinde (553-557. ss.), IEEE.
98. Van Eck, N. J. & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538.
99. Vecchiato, G., Astolfi, L., De Vico Fallani, F., Toppi, J., Aloise, F., Bez, F., Wei, D., Kong, W., Dai, J., Cincotti, F., Mattia, D., Babiloni, F. (2011). On the use of EEG or MEG brain imaging tools in neuromarketing research. Computational intelligence and neuroscience, (2011), 643489.
100. Vujičić, M., Grbac, B., Mozetič, V. (2021). Contributions of functional magnetic resonance imaging in market research: Obstacles and perspectives. Market-Tržište, 33(2), 185-203.
101. Wang, J. T. Y. (2011). Pupil dilation and eye tracking. M. Schulte-Mecklenbeck, A. Kuehberger, J. G. Johnson (Ed.), A Handbook of Process Tracing Methods for Decision Research: A Critical Review and User’s Guide içinde (185-204. ss.), Psychology Press.
102. Wannyn, W. (2017). Le marketing du neuromarketing: Enjeux académiques d’un domaine de recherche controversé. Social Science Information, 56(4), 619-639.
103. Xie, Z., Yu, Y., Zhang, J., Chen, M. (2022). The searching artificial intelligence: Consumers show less aversion to algorithm‐recommended search product. Psychology & Marketing, 39(10), 1902-1919.
104. Yağcı, M. I., Kuhzady, S., Balık, Z. S., Öztürk, L. (2018). In search of consumer’s black box: A bibliometric analysis of neuromarketing research. Tüketici ve Tüketim Araştırmaları Dergisi: Journal of Consumer and Consumption Research, 10(1), 101-134.
105. Ye, G., Hudders, L., De Jans, S., De Veirman, M. (2021). The value of influencer marketing for business: A bibliometric analysis and managerial implications. Journal of Advertising, 50(2), 160-178.
106. Yoon, C., Gutchess, A. H., Feinberg, F., Polk, T. A. (2006). A functional magnetic resonance imaging study of neural dissociations between brand and person judgments. Journal of Consumer Research, 33(1), 31-40.
107. Zhang, G., Li, M., Li, J., Tan, M., Li, H., Zhong, Y. (2022). Green product types modulate green consumption in the gain and loss framings: An event-related potential study. International Journal of Environmental Research and Public Health, 19(17), 10746.
108. Zhu, Z., Jin, Y., Su, Y., Jia, K., Lin, C. L., Liu, X. (2022). Bibliometric-based evaluation of the neuromarketing research trend: 2010-2021. Frontiers in Psychology, (13), 872468.
109. Zupic, I. & Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429-472.
110. Żurawicki, L. (2010). Neuromarketing: Exploring the brain of the consumer. Springer.
111. Zuschke, N. (2020). The impact of task complexity and task motivation on in-store marketing effectiveness: An eye tracking analysis. Journal of Business Research, (116), 337-350.