SCIENTOMETRIC ANALYSIS OF SCIENTIFIC LITERATURE ON NEUROMARKETING TOOLS IN ADVERTISING

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

Published: Dec 30, 2022

  Lina Pilelienė

  Ahmed H. Alsharif

  Ibrahim Bader Alharbi

Abstract

Neuromarketing (NM) is a relatively new area of marketing that involves innovative technological changes in the marketing research process and the tools and methods used. Considering the novelty of the domain, the subject of the study is chosen to be articles published in scientific literature describing neuromarketing tools used in advertising. This study examined articles in the field of advertising that used neuromarketing techniques to measure consumers' neural and physiological responses to advertising, which has not yet been covered in the literature. Methodology. To fill the gap in the literature, the authors, guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, selected relevant articles and conducted a bibliometric analysis to identify global trends and developments in the field of advertising and neuromarketing. From the Web of Science (WoS) database, 41 articles published between 2009 and 2020 were extracted and analyzed. Purpose of the study was to establish a background for advertising research based on the application of NM tools. The findings revealed that Spain was the most productive country with eleven papers published in a domain of advertising research, followed by Italy and the USA with eight and seven papers, respectively. Among academic institutions, Sapienza University Rome was recognized as the leading academic organization with three articles. As for the most productive journals, Frontiers in Psychology was the most cited journal with eight articles and 29 total citations (TC). As the highest productive author, Babiloni, F. with two papers and 68 TCs by 2020 was identified. Keyword analysis showed that "advertising" (27 occurrences and 127 total references) is the most frequently used keyword. The analysis of co-occurrence of keywords showed that NM focused on marketing research such as advertising (12 occurrences, 63 total link strength (TLS)), followed by brain processes such as attention, emotions and memory. The paper titled “Neuromarketing: The new science of consumer behavior” was the most-cited paper with 152 TCs. Conclusion of the study. This study presents a brief overview of the latest universal areas of neuromarketing and advertising research. The findings suggest that neuroscientific methods and techniques are extremely important for mapping consumers' neural and physiological responses to advertising.

How to Cite

Pilelienė, L., H. Alsharif, A., & Bader Alharbi, I. (2022). SCIENTOMETRIC ANALYSIS OF SCIENTIFIC LITERATURE ON NEUROMARKETING TOOLS IN ADVERTISING. Baltic Journal of Economic Studies, 8(5), 1-12. https://doi.org/10.30525/2256-0742/2022-8-5-1-12
Article views: 747 | PDF Downloads: 416

##plugins.themes.bootstrap3.article.details##

Keywords

advertising, bibliometric analysis, marketing, neuromarketing, WoS database

References

Abbas, A. F., Jusoh, A., od, A. M., Ali, J., Alsharif, A. H., & E, A. R. H. (2021). A bibliometric analysis of publications on social media influencers using vosviewer. Journal of Theoretical and Applied Information Technology, 99(23), 5662–5676.

Abbas, A. F., Jusoh, A., od, A. M., Alsharif, A. H., & Ali, J. (2022). Bibliometrix analysis of information sharing in social media. Cogent Business & Management, 9(1), 2016556. DOI: https://doi.org/10.1080/23311975.2021.2016556

Ahmed, H. A., Md Salleh, N., Baharun, R., & Mehdi, S. (2020). Neuromarketing approach: An overview and future research directions. Journal of Theoretical and Applied Information Technology, 98(7), 991–1001.

Ahmed, H. A., NorZafir, M. S., Linares, P., Alhamzah, F. A., & Javed, A. (2022a). Current Trends in the Application of EEG in Neuromarketing: A Bibliometric Analysis. Scientific Annals of Economics and Business, 69(3), 393–415. DOI: https://doi.org/10.47743/saeb-2022-0020

Ahmed, H. A., NorZafir, M. S., Rohaizat, B., Hassan, A., & Rami, H. E. A. (2022b). A global research trends of neuromarketing: 2015-2020. Revista de Comunicación, 21(1), 15–32. DOI: https://doi.org/10.26441/rc21.1-2022-a1

Ahmed, H. A., NorZafir, M. S., Rohaizat, B., Rami, H. E. A., Aida, A. M., Javed, A., & Alhamzah, F. A. (2021). Neuroimaging Techniques in Advertising Research: Main Applications, Development, and Brain Regions and Processes. Sustainability, 13(11), 6488. DOI: https://doi.org/10.3390/su13116488

Ali, J., Jusoh, A., Idris, N., Abbas, A. F., & Alsharif, A. H. (2021a). Everything is Going Electronic, so do Services and Service Quality: Bibliometric Analysis of E-Services and E-Service Quality. International Journal of Interactive Mobile Technologies, 15(18), 148–166. DOI: https://doi.org/10.3991/ijim.v15i18.24519

Ali, J., Jusoh, A., Idris, N., Abbas, A. F., & Alsharif, A. H. (2021b). Nine Years of Mobile Healthcare Research: A Bibliometric Analysis. International Journal of Online & Biomedical Engineering, 17(10). DOI: https://doi.org/10.3991/ijoe.v17i10.25243

Alsharif, A. H., Salleh, N. Z. M., Ahmad, W. A. b. W., & Khraiwish, A. (2022). Biomedical Technology in Studying Consumers’ Subconscious Behavior. International Journal of Online and Biomedical Engineering, 18(8), 98–114. DOI: https://doi.org/10.3991/ijoe.v18i08.31959

Alsharif, A. H., Salleh, N. Z. M., & Baharun, R. (2020). Research trends of neuromarketing: A bibliometric analysis. Journal of Theoretical and Applied Information Technology, 98(15), 2948–2962.

Alsharif, A. H., Salleh, N. Z. M., & Baharun, R. (2021a). Neuromarketing: Marketing research in the new millennium. Neuroscience Research Notes, 4(3), 27–35. DOI: https://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. DOI: https://doi.org/10.31117/neuroscirn.v3i5.80

Alsharif, A. H., Salleh, N. Z. M., Baharun, R., & Alharthi, R. H. E. (2021c). Neuromarketing research in the last five years: a bibliometric analysis. Cogent Business & Management, 8(1), 1978620. DOI: https://doi.org/10.1080/23311975.2021.1978620

Ananos, E. (2015). Eye tracker technology in elderly people: How integrated television content is paid attention to and processed. Comunicar, 23(45), 75–83. DOI: https://doi.org/10.3916/c45-2015-08

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. DOI: https://doi.org/10.1007/s11301-020-00188-4

Bočková, K., Škrabánková, J., & Hanák, M. (2021). Theory and practice of neuromarketing: Analyzing human behavior in relation to markets. Emerging Science Journal, 5(1), 44–56. DOI: https://doi.org/10.28991/esj-2021-01256

Carrington, M. J., Neville, B. A., & Whitwell, G. J. (2014). Lost in translation: Exploring the ethical consumer intention–behavior gap. Journal of Business Research, 67(1), 2759–2767. DOI: https://doi.org/10.1016/j.jbusres.2012.09.022

Comerio, N., & Strozzi, F. (2019). Tourism and its economic impact: A literature review using bibliometric tools. Tourism economics, 25(4), 109–131. DOI: https://doi.org/10.1177/1354816618793762

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(4), 137. DOI: https://doi.org/10.4236/jbbs.2015.54014

Fortunato, V. C. R., Giraldi, J. D. M. E., & Oliveira, J. H. C. D. (2014). A review of studies on neuromarketing: Practical results, techniques, contributions and limitations. Journal of Management Research, 6(2), 201–221. DOI: https://doi.org/10.5296/jmr.v6i2.5446

Gingras, Y. (2016). Bibliometrics and research evaluation: Uses and abuses. MIT Press.

Grigaliunaite, V., & Pileliene, L. (2016). Emotional or rational? The determination of the influence of advertising appeal on advertising effectiveness. Scientific Annals of Economics Business, 63(3), 391–414.

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. DOI: https://doi.org/10.3389/fpsyg.2017.01808

Harris, J., Ciorciari, J., & Gountas, J. (2018). Consumer neuroscience for marketing researchers. Journal of Consumer Behaviour, 17(3), 239–252. DOI: https://doi.org/10.1002/cb.1710

Harris, J., Ciorciari, J., & Gountas, J. (2019). Consumer neuroscience and digital/social media health/social cause advertisement effectiveness. Behavioral Sciences, 9(4), 25. DOI: https://doi.org/10.3390/bs9040042

Isabella, G., Mazzon, J. A., & Dimoka, A. (2015). Culture differences, difficulties, and challenges of the neurophysiological methods in marketing research. Journal of International Consumer Marketing, 27(5), 346–363. DOI: https://doi.org/10.1080/08961530.2015.1038761

Izhikevich, E. M. (2003). Simple model of spiking neurons. IEEE Transactions on neural networks, 14(6), 1569–1572.

Javor, A., Koller, M., Lee, N., Chamberlain, L., & Ransmayr, G. (2013). Neuromarketing and consumer neuroscience: Contributions to neurology. BMC neurology, 13(1), 13. DOI: https://doi.org/10.1186/1471-2377-13-13

Jimenez-Marin, G., Bellido-Pérez, E., & López-Cortés, Á. (2019). Sensory Marketing The Concept, Its Techniques And Its Application At The Point Of Sale. Revista de Comunicación'Vivat Academia', 2(148), 121–147. DOI: http://doi.org/10.15178/va.2019.148.121-147

Kumar, S., Sureka, R., & Colombage, S. (2019). Capital structure of SMEs: A systematic literature review and bibliometric analysis. Management Review Quarterly, 4(2), 1–31. DOI: https://doi.org/10.1007/s11301-019-00175-4

Leanza, F. (2017). Consumer neuroscience: The traditional and VR TV commercial. Neuropsychological Trends, 21(1), 81–90. DOI: http://dx.doi.org/10.7358/neur-2017-021-lean

Levallois, C., Clithero, J. A., Wouters, P., Smidts, A., & Huettel, S. A. (2012). Translating upwards: linking the neural and social sciences via neuroeconomics. Nature Reviews Neuroscience, 13(11), 789–797. DOI: https://doi.org/10.1038/nrn3354

Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., . . . Stewart, L. A. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic reviews, 4(1), 1–9. DOI: https://doi.org/10.1186/2046-4053-4-1

Morin, C. (2011). Neuromarketing: The new science of consumer behavior. Society, 48(2), 131–135. DOI: https://doi.org/10.1007/s12115-010-9408-1

Nacpil, E. J. C., Wang, Z., Zheng, R. C., Kaizuka, T., & Nakano, K. (2019). Design and Evaluation of a Surface Electromyography-Controlled Steering Assistance Interface. Sensors, 19(6), 20. DOI: https://doi.org/10.3390/s19061308

Plassmann, H., Ramsoy, T. Z., & Milosavljevic, M. (2012). Branding the brain: A critical review and outlook. Journal of Consumer Psychology, 22(1), 18–36. DOI: https://doi.org/10.1016/j.jcps.2011.11.010

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.

Smidts, A. (2002). Kijken in het brein: Over de mogelijkheden van neuromarketing. Netherland. Erasmus Research Institute of Management.

Stallen, M., Smidts, A., Rijpkema, M., Smit, G., Klucharev, V., & Fernandez, G. (2010). Celebrities and shoes on the female brain: The neural correlates of product evaluation in the context of fame. Journal of Economic Psychology, 31(5), 802–811. DOI: https://doi.org/10.1016/j.joep.2010.03.006

Vecchiato, G., Astolfi, L., Fallani, F. D., Toppi, J., Aloise, F., Bez, F., . . . Babiloni, F. (2011). On the use of EEG or MEG brain imaging tools in neuromarketing research. Computational Intelligence and Neuroscience, 2011(3), 1–12. DOI: https://doi.org/10.1155/2011/643489

Wang, M., & Chai, L. (2018). Three new bibliometric indicators/approaches derived from keyword analysis. Scientometrics, 116(3), 721–750. DOI: https://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. DOI: https://doi.org/10.3389/fnins.2018.00076

Wei, Z., Wu, C., Wang, X. Y., Supratak, A., Wang, P., & Guo, Y. K. (2018). Using Support Vector Machine on EEG for Advertisement Impact Assessment. Frontiers in Neuroscience, 12, 12. DOI: https://doi.org/10.3389/fnins.2018.00076