Current Trends in the Application of EEG in Neuromarketing: A Bibliometric Analysis
DOI:
https://doi.org/10.47743/saeb-2022-0020Keywords:
bibliometric analysis, consumer behavior, EEG, neuromarketing, Scopus database.Abstract
Despite several neuroscience tools existing, electroencephalography (EEG) is the most used and favoured tool among researchers because of its relatively low cost and high temporal resolution. Our study aimed to identify the global academic research trends of the empirical EEG studies in neuromarketing. This paper adopted the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol to identify relevant articles. A bibliometric analysis software (VOSviewer) was used to evaluate thirty open-access articles found in the Scopus database between 2016 and 2020. We found that the USA is the most productive country with five research articles that used the EEG tool in marketing studies, followed by Australia, Italy, and Malaysia with three articles each. According to the most prolific journals in neuromarketing, it has been found that Frontiers in Neuroscience journal (CiteScore 5.4) is the most prolific journal with two articles and 25 total citations, followed by Scientific reports (CiteScore 7.1) with two articles and eighteen total citations, which lead us to infer that the publications’ number does not necessarily reflect the citations’ number. The study provides a profound and comprehensive overview of academic research that used EEG in marketing research.
References
Abbas, A. F., Jusoh, A., Mas'od, A., Ali, J., Alsharif, A., & Alharthi, R. (2021). A bibliometric analysis of publications on social media influencers using vosviewer. Journal of Theoretical and Applied Information Technology, 99, 5662-5676.
Abbas, A. F., Jusoh, A., Mas’od, A., Alsharif, A. H., & Ali, J. (2022). Bibliometrix analysis of information sharing in social media. 9(1), 2016556. http://dx.doi.org/10.1080/23311975.2021.2016556
Aditya, D., & Sarno, R. (2018). Neuromarketing: State of the arts. Advanced Science Letters, 24(12), 9307-9310. http://dx.doi.org/10.1166/asl.2018.12261
Alsharif, A. H., Salleh, N. Z. M., & Baharun, R. (2021a). Neuromarketing: Marketing research in the new millennium. Neuroscience Research Notes, 4(3), 27-35. http://dx.doi.org/10.31117/neuroscirn.v4i3.79
Alsharif, A. H., Salleh, N. Z. M., & Baharun, R. (2021b). Neuromarketing: The popularity of the brain-imaging and physiological tools. Neuroscience Research Notes, 3(5), 13-22. http://dx.doi.org/10.31117/neuroscirn.v3i5.80
Alsharif, A. H., Salleh, N. Z. M., Baharun, R., Alharthi, R. H. E., Mansor, A. A., Ali, J., & Abbas, A. F. (2021). Neuroimaging Techniques in Advertising Research: Main Applications, Development, and Brain Regions and Processes. Sustainability (Basel), 13(11), 6488. http://dx.doi.org/10.3390/su13116488
Badcock, N. A., Mousikou, P., Mahajan, Y., de Lissa, P., Thie, J., & McArthur, G. (2013). Validation of the Emotiv EPOC(®) EEG gaming system for measuring research quality auditory ERPs. PeerJ, 1, e38. http://dx.doi.org/10.7717/peerj.38
Baker, H. K., Pandey, N., Kumar, S., & Haldar, A. (2020). A bibliometric analysis of board diversity: Current status, development, and future research directions. Journal of Business Research, 108, 232-246. http://dx.doi.org/10.1016/j.jbusres.2019.11.025
Balconi, M., Sebastiani, R., & Angioletti, L. (2019). A neuroscientific approach to explore consumers’ intentions towards sustainability within the luxury fashion industry. Sustainability (Basel), 11(18), 5105. http://dx.doi.org/10.3390/su11185105
Bazzani, A., Ravaioli, S., Trieste, L., Faraguna, U., & Turchetti, G. (2020). Is EEG Suitable for Marketing Research? A Systematic Review. Frontiers in Neuroscience, 14, 594566. http://dx.doi.org/10.3389/fnins.2020.594566
Berger, H. (1969). On the electroencephalogram of man. Electroencephalography and Clinical Neurophysiology, 3, 28-37.
Biercewicz, K., Borawski, M., & Duda, J. (2020). Method for Selecting an Engagement Index for a Specific Type of Game Using Cognitive Neuroscience. International Journal of Computer Games Technology, 2020, 1-19. http://dx.doi.org/10.1155/2020/2450651
Block, J. H., & Fisch, C. (2020). Eight tips and questions for your bibliographic study in business and management research. Management Review Quarterly, 70(3), 307-312. http://dx.doi.org/10.1007/s11301-020-00188-4
Bosshard, S. S., Bourke, J. D., Kunaharan, S., Koller, M., & Walla, P. (2016). Established liked versus disliked brands: Brain activity, implicit associations and explicit responses. Cogent Psychology, 3(1), 1-16. http://dx.doi.org/10.1080/23311908.2016.1176691
Burle, B., Spieser, L., Roger, C., Casini, L., Hasbroucq, T., & Vidal, F. (2015). Spatial and temporal resolutions of EEG: Is it really black and white? A scalp current density view. International Journal of Psychophysiology, 97(3), 210-220. http://dx.doi.org/10.1016/j.ijpsycho.2015.05.004
Cartocci, G., Caratù, M., Modica, E., Maglione, A. G., Rossi, D., Cherubino, P., & Babiloni, F. (2017). Electroencephalographic, heart rate, and galvanic skin response assessment for an advertising perception study: Application to antismoking public service announcements. Journal of Visualized Experiments, 3(126), 55872-55881. http://dx.doi.org/10.3791/55872
Cherubino, P., Martinez-Levy, A. C., Caratù, M., Cartocci, G., Di Flumeri, G., Modica, E., . . . Trettel, A. (2019). Consumer Behaviour through the Eyes of Neurophysiological Measures: State-of-the-Art and Future Trends. Computational Intelligence and Neuroscience, 2019, 1976847. http://dx.doi.org/10.1155/2019/1976847
Chew, L. H., Teo, J., & Mountstephens, J. (2016). Aesthetic preference recognition of 3D shapes using EEG. Cognitive Neurodynamics, 10(2), 165-173. http://dx.doi.org/10.1007/s11571-015-9363-z
Comerio, N., & Strozzi, F. (2019). Tourism and its economic impact: A literature review using bibliometric tools. Tourism Economics, 25(4), 109-131. http://dx.doi.org/10.1177/1354816618793762
Constantin, A., Popescu, N., Popescu, D., Tiganoaia, B., Negoita, O. D., & Niculescu, A. (2020). EEG object recognition: Studies for criminal investigation and neuro-applications in social care. International Journal of Advanced and Applied Sciences, 7(1), 79-86. http://dx.doi.org/10.21833/ijaas.2020.01.008
Di Flumeri, G., Herrero, M. T., Trettel, A., Cherubino, P., Maglione, A. G., Colosimo, A., & Babiloni, F. (2016). EEG frontal asymmetry related to pleasantness of olfactory stimuli in young subjects Selected Issues in Experimental Economics (pp. 373-381): Springer. http://dx.doi.org/10.1007/978-3-319-28419-4_23
Doborjeh, Z. G., Kasabov, N., Doborjeh, M. G., & Sumich, A. (2018). Modelling peri-perceptual brain processes in a deep learning spiking neural network architecture. Scientific Reports, 8(1), 1-13. http://dx.doi.org/10.1038/s41598-018-27169-8
Eijlers, E., Boksem, M. A. S., & Smidts, A. (2020). Measuring neural arousal for advertisements and its relationship with advertising success. Frontiers in Neuroscience, 14(4), 736-748. http://dx.doi.org/10.3389/fnins.2020.00736
García-Madariaga, J., Moya, I., Recuero, N., & Blasco, M. F. (2020). Revealing unconscious consumer reactions to advertisements that include visual metaphors: A neurophysiological experiment. Frontiers in Psychology, 11(3), 760-776. http://dx.doi.org/10.3389/fpsyg.2020.00760
Goto, N., Lim, X. L., Shee, D., Hatano, A., Khong, K. W., Buratto, L. G., . . . Schaefer, A. (2019). Can brain waves really tell if a product will be purchased? Inferring consumer preferences from single-item brain potentials. Frontiers in Integrative Neuroscience, 13, 19. http://dx.doi.org/10.3389/fnint.2019.00019
Goto, N., Mushtaq, F., Shee, D., Lim, X. L., Mortazavi, M., Watabe, M., & Schaefer, A. (2017). Neural signals of selective attention are modulated by subjective preferences and buying decisions in a virtual shopping task. Biological Psychology, 128, 11-20. http://dx.doi.org/10.1016/j.biopsycho.2017.06.004
Guixeres, J., Bigné, E., Ausín Azofra, J. M., Alcañiz Raya, M., Colomer Granero, A., Fuentes Hurtado, F., & Naranjo Ornedo, V. (2017). Consumer neuroscience-based metrics predict recall, liking and viewing rates in online advertising. Frontiers in Psychology, 8(3), 1808. http://dx.doi.org/10.3389/fpsyg.2017.01808
Harris, J. M., Ciorciari, J., & Gountas, J. (2019). Consumer neuroscience and digital/social media health/social cause advertisement effectiveness. Behavioral Sciences (Basel, Switzerland), 9(4), 25. http://dx.doi.org/10.3390/bs9040042
Jordao, I. L. D. S., Souza, M. T. D., Oliveira, J. H. C. D., & Giraldi, J. D. M. E. (2017). Neuromarketing applied to consumer behaviour: An integrative literature review between 2010 and 2015. International Journal of Business Forecasting and Marketing Intelligence, 3(3), 270-288. http://dx.doi.org/10.1504/IJBFMI.2017.085371
Kane, N., Acharya, J., Benickzy, S., Caboclo, L., Finnigan, S., Kaplan, P. W., . . . van Putten, M. J. A. M. (2017). A revised glossary of terms most commonly used by clinical electroencephalographers and updated proposal for the report format of the EEG findings. Revision 2017. Clinical Neurophysiology Practice, 2, 170-185. http://dx.doi.org/10.1016/j.cnp.2017.07.002
Kim, Y., Park, K., Kim, Y., Yang, W., Han, D., & Kim, W. S. (2020). The Impact of Visual Art and High Affective Arousal on Heuristic Decision-Making in Consumers. Frontiers in Psychology, 11, 565829. http://dx.doi.org/10.3389/fpsyg.2020.565829
Ma, Q., Abdeljelil, H. M., & Hu, L. (2019). The Influence of the consumer ethnocentrism and cultural familiarity on brand preference: Evidence of Event-Related Potential (ERP). Frontiers in Human Neuroscience, 13, 220. http://dx.doi.org/10.3389/fnhum.2019.00220
Ma, Q., Zhang, L., & Wang, M. (2018). “You Win, You Buy”-How Continuous Win Effect Influence Consumers’ Price Perception: An ERP Study. Frontiers in Neuroscience, 12, 691. http://dx.doi.org/10.3389/fnins.2018.00691
Mengual-Recuerda, A., Tur-Viñes, V., & Juárez-Varón, D. (2020). Neuromarketing in haute cuisine gastronomic experiences. Frontiers in Psychology, 11, 1772. http://dx.doi.org/10.3389/fpsyg.2020.01772
Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., . . . Group, P.-P. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic Reviews, 4(1), 1-9. http://dx.doi.org/10.1186/2046-4053-4-1
Morin, C. (2011). Neuromarketing: The new science of consumer behavior. Society, 48(2), 131-135. http://dx.doi.org/10.1007/s12115-010-9408-1
Moya, I., García-Madariaga, J., & Blasco, M. F. (2020). What Can Neuromarketing Tell Us about Food Packaging? Foods, 9(12), 1856. http://dx.doi.org/10.3390/foods9121856
Muñoz, Y., López-Gallego, F., Arias-Salazar, A., & Serna-Rodríguez, M. (2019). Selling of products: The use of single-electrode wireless EEG in consumer behavior. International Journal of Psychological Research, 12(1), 57-65. http://dx.doi.org/10.21500/20112084.4089
Nittono, H., & Watari, K. (2017). Effects of food sampling on brain potential responses to food branding. Psychologia, 60(1), 3-15. http://dx.doi.org/10.2117/psysoc.2017.3
Ohme, R., & Matukin, M. (2012). A small frog that makes a big difference: Brain wave testing of TV advertisements. IEEE Pulse, 3(3), 28-33. http://dx.doi.org/10.1109/mpul.2012.2189169
Plassmann, H., Ambler, T., Braeutigam, S., & Kenning, P. (2007). What can advertisers learn from neuroscience? International Journal of Advertising, 26(2), 151-175. http://dx.doi.org/10.1080/10803548.2007.11073005
Qiu, J. M., Casey, M. A., & Diamond, S. G. (2019). Assessing feedback response with a wearable electroencephalography system. Frontiers in Human Neuroscience, 13, 258. http://dx.doi.org/10.3389/fnhum.2019.00258
Ramsoy, T. Z., Michael, N., & Michael, I. (2019). A consumer neuroscience study of conscious and subconscious destination preference. Scientific Reports, 9(1), 1-8. http://dx.doi.org/10.1038/s41598-019-51567-1
Ramsoy, T. Z., Skov, M., Christensen, M. K., & Stahlhut, C. (2018). Frontal Brain Asymmetry and Willingness to Pay. Frontiers in Neuroscience, 12(3), 138-150. http://dx.doi.org/10.3389/fnins.2018.00138
Ravikumar, S., Agrahari, A., & Singh, S. N. (2015). Mapping the intellectual structure of scientometrics: A co-word analysis of the journal Scientometrics (2005–2010). Scientometrics, 102(1), 929-955. http://dx.doi.org/10.1007/s11192-014-1402-8
Rawnaque, F. S., Rahman, K. M., Anwar, S. F., Vaidyanathan, R., Chau, T., Sarker, F., & Mamun, K. A. A. (2020). Technological advancements and opportunities in Neuromarketing: A systematic review. Brain Informatics, 7(1), 10. http://dx.doi.org/10.1186/s40708-020-00109-x
Sánchez-Fernández, J., Casado-Aranda, L. A., & Bastidas-Manzano, A. B. (2021). Consumer Neuroscience Techniques in Advertising Research: A Bibliometric Citation Analysis. Sustainability (Basel), 13(3), 1589. http://dx.doi.org/10.3390/su13031589
Sargent, A., Watson, J., Ye, H., Suri, R., & Ayaz, H. (2020). Neuroergonomic Assessment of Hot Beverage Preparation and Consumption: An EEG and EDA Study. Frontiers in Human Neuroscience, 14, 175. http://dx.doi.org/10.3389/fnhum.2020.00175
Silverman, D. (1965). The anterior temporal electrode and the ten-twenty system. The American Journal of EEG Technology, 5(1), 11-14. http://dx.doi.org/10.1080/00029238.1965.11080641
Słupińska, K., Duda, J., & Biercewicz, K. (2021). Planning an experiment in a virtual environment reality as a place of research on human behaviour using methods of neuroscience measurement–bibliometric analysis and methodological approach. Procedia Computer Science, 192, 3123-3133. http://dx.doi.org/10.1016/j.procs.2021.09.085
Soria Morillo, L. M., Alvarez-Garcia, J. A., Gonzalez-Abril, L., & Ortega Ramírez, J. A. (2016). Discrete classification technique applied to TV advertisements liking recognition system based on low-cost EEG headsets. Biomedical Engineering Online, 15(1), 75. http://dx.doi.org/10.1186/s12938-016-0181-2
Stanton, S., Armstrong, W., & Huettel, S. (2017). Neuromarketing: Ethical implications of its use and potential misuse. Journal of Business Ethics, 144(4), 799-811. http://dx.doi.org/10.1007/s10551-016-3059-0
Stone, J. D., Rentz, L. E., Forsey, J., Ramadan, J., Markwald, R. R., Finomore, V. S., . . . Hagen, J. A. (2020). Evaluations of commercial sleep technologies for objective monitoring during routine sleeping conditions. Nature and Science of Sleep, 12, 821-842. http://dx.doi.org/10.2147/nss.s270705
Teo, J., Chew, L. H., Chia, J. T., & Mountstephens, J. (2018). Classification of affective states via EEG and deep learning. International Journal of Advanced Computer Science and Applications, 9(5), 132-142. http://dx.doi.org/10.14569/ijacsa.2018.090517
Van Eck, N., & Waltman, L. (2013). Manual for VOSviewer version 1.5. 4. Universiteit Leiden and Erasmus Universiteit Rotterdam, 1(1), 1-53.
Vecchiato, G., & Babiloni, F. (2011, 2011//). Neurophysiological Measurements of Memorization and Pleasantness in Neuromarketing Experiments. Paper presented at the Analysis of Verbal and Nonverbal Communication and Enactment. The Processing Issues, Berlin, Heidelberg.
Venkatraman, V., Dimoka, A., Pavlou, P. A., Vo, K., Hampton, W., Bollinger, B., . . . Winer, R. S. (2015). Predicting advertising success beyond traditional measures: New insights from neurophysiological methods and market response modeling. JMR, Journal of Marketing Research, 52(4), 436-452. http://dx.doi.org/10.1509/jmr.13.0593
Vlăsceanu, S. (2014). New Directions in Understanding the Decision-making Process: Neuroeconomics and Neuromarketing. Procedia - Social and Behavioral Sciences, 127, 758-762. http://dx.doi.org/10.1016/j.sbspro.2014.03.350
Wang, M., & Chai, L. (2018). Three new bibliometric indicators/approaches derived from keyword analysis. Scientometrics, 116(3), 721-750. http://dx.doi.org/10.1007/s11192-018-2768-9
Wei, Z., Wu, C., Wang, X., Supratak, A., Wang, P., & Guo, Y. (2018). Using support vector machine on EEG for advertisement impact assessment. Frontiers in Neuroscience, 12(3), 76-88. http://dx.doi.org/10.3389/fnins.2018.00076
Williams, N. S., McArthur, G. M., de Wit, B., Ibrahim, G., & Badcock, N. A. (2020). A validation of Emotiv EPOC Flex saline for EEG and ERP research. PeerJ, 8, e9713. http://dx.doi.org/10.7717/peerj.9713
Yang, T., & Kim, S. P. (2019). Group-level neural responses to service-to-service brand extension. Frontiers in Neuroscience, 13, 676. http://dx.doi.org/10.3389/fnins.2019.00676
Yang, T., Lee, S., Seomoon, E., & Kim, S. P. (2018). Characteristics of human brain activity during the evaluation of service-to-service brand extension. Frontiers in Human Neuroscience, 12, 44. http://dx.doi.org/10.3389/fnhum.2018.00044
Zamani, J., & Naieni, A. B. (2020). Best Feature Extraction and Classification Algorithms for EEG Signals in Neuromarketing. Frontiers in Biomedical Technologies, 7(3), 186-191. http://dx.doi.org/10.18502/fbt.v7i3.4621
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