Neuromarketing y las preferencias del consumidor desde web of science: Análisis bibliométrico
Neuromarketing and consumer preferences from the web of science: a bibliometric analysisContenido principal del artículo
Neuromarketing has gained relevance as a tool for understanding consumer behavior and preferences. This article examines the scientific production related to neuromarketing and consumer preferences through a bibliometric analysis of 554 records retrieved from the Web of Science database. Using R-Studio and bibliometrix v.4.1.4, most cited papers, frequent keywords and scientific impact metrics were examined. In addition, co-citation networks and thematic groupings were explored. The results highlight factors such as absolute and relative impact of neuromarketing studies, evidencing a bibliometric approach that connects science, innovation and strategic management. Keywords evolve around terms such as “cognition”, ‘emotion’ and “decision making”, reflecting a growth in the interdisciplinarity of the field. Cocitation networks reveal crucial nodes and patterns, providing a comprehensive view of research trends and priorities in neuromarketing.
Neuromarketing has gained relevance as a tool for understanding consumer behavior and preferences. This article analyzes the scientific production on neuromarketing and consumer preferences through a bibliometric analysis based on 554 records retrieved from Web of Science. Using R-Studio and bibliometrix v.4.1.4, most cited papers, frequent keywords and scientific impact metrics were examined. In addition, co-citation networks and thematic groupings were explored. The results highlight factors such as absolute and relative impact of neuromarketing studies, evidencing a bibliometric approach that connects science, innovation and strategic management. Keywords evolve around terms such as “cognition”, “emotion” and “decision making”, reflecting a growth in the interdisciplinarity of the field. Cocitation networks reveal crucial nodes and patterns, providing a comprehensive view of research trends and priorities in neuromarketing.
Detalles del artículo

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
Cómo citar
Referencias
Araújo Ruiz, J. A., y Arencibia Jorge, R. (2002). Informetría, bibliometría y cienciometría: Aspectos teórico-prácticos. ACIMED, 10(4), 5-6. https://n9.cl/68paw
Alsharif, A. H., Salleh, N. Z. M., Baharun, R., Abuhassna, H., y Hasheme, A. R. (2022). A global research trends of neuromarketing: 2015-2020. Revista de Comunicacion, 81(1), 15-32. https://doi.org/10.26441/RC21.1-2022-A1
Barney, J. (1991). Special Theory Forum The Resource-Based Model of the Firm: Origins, Implications, and Prospects. Journal of Management, 17(1), 97-98. https://doi.org/10.1177/014920639101700107
Blázquez-Resino, J. J., y Bravo, M. Á. G. (2022). Application of neuromarketing tools for marketing research. VISUAL Review. International Visual Culture Review / Revista Internacional de Cultura, 9(Monographic). https://doi.org/10.37467/revvisual.v9.3581
Cenizo, C. (2022). Neuromarketing: Concepto, evolución histórica y retos. Icono14, 20(1), 11. https://n9.cl/aqblo
Cohen, W. M., y Levinthal, D. A. (1990). Absorptive Capacity: A New Perspective on Learning and Innovation. Administrative Science Quarterly, 35(1), 128-152. https://doi.org/10.2307/2393553
Cruz, C. M. L., De Medeiros, J. F., Hermes, L. C. R., Marcon, A., y Marcon, É. (2016). Neuromarketing and the advances in the consumer behaviour studies: A systematic review of the literature. International Journal of Business and Globalisation, 17(3), 330-351. https://doi.org/10.1504/IJBG.2016.078842
Duque-Hurtado, P., Samboni-Rodriguez, V., Castro-Garcia, M., Montoya-Restrepo, L. A., y Montoya-Restrepo, I. A. (2020). Neuromarketing: Its current status and research perspectives. Estudios Gerenciales, 36(157), 525-539. https://doi.org/10.18046/j.estger.2020.157.3890
Eck, N. van, y Waltman, L. (2009). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538. https://doi.org/10.1007/s11192-009-0146-3
Frommel, V. V. (2024). Determinants of Brand Trust: A Neuroanalytical Study in the B2B Sector Using the Example of Manufacturing Industry. Developments in Marketing Science: Proceedings of the Academy of Marketing Science, Part F2055, 18-31. https://doi.org/10.1007/978-3-031-49039-2_3
Kessler, M. M. (1963). Bibliographic coupling between scientific papers. American Documentation, 14(1), 10-25. https://doi.org/10.1002/asi.5090140103
Kim, J. Y., y Kim, M. J. (2024). Identifying customer preferences through the eye-tracking in travel websites focusing on neuromarketing. Journal of Asian Architecture and Building Engineering, 23(2), 515-527. https://doi.org/10.1080/13467581.2023.2244566
Lyu, D., y Mañas-Viniegra, L. (2023). Tendencias emergentes en «neuromarketing»: Análisis Bibliométrico con CiteSpace (2017-2021). https://doi.org/10.33732/ixc/13/02Tenden
Nerur, S. P., Rasheed, A. A., y Natarajan, V. (2008). The intellectual structure of the strategic management field: An author co-citation analysis. Strategic Management Journal, 29(3), 319-336. https://doi.org/10.1002/smj.659
Núñez-Cansado, M., Carrascosa Méndez, G., y Juárez-Varón, D. (2024). Analysis of the residual effect using neuromarketing technology in audiovisual content entrepreneurship. Sustainable Technology and Entrepreneurship, 3(3). https://doi.org/10.1016/j.stae.2023.100069
Oberoi, S., Kansra, P., y Awasthi, V. (2024). A bibliometric analysis on research trends in neuromarketing: Current status and future directions. En Digital Influence on Consumer Habits: Marketing Challenges and Opportunities (79-92). https://doi.org/10.1108/978-1-80455-342-820241005
Ouzir, M., Chakir Lamrani, H., Bradley, R. L., y El Moudden, I. (2024). Neuromarketing and decision-making: Classification of consumer preferences based on changes analysis in the EEG signal of brain regions. Biomedical Signal Processing and Control, https://doi.org/10.1016/j.bspc.2023.105469
Panda, D., Chakladar, D. D., Rana, S., y Shamsudin, M. N. (2024). Spatial Attention-Enhanced EEG Analysis for Profiling Consumer Choices. IEEE Access, 12, 13477-13487. https://doi.org/10.1109/ACCESS.2024.3355977
Pritchard, R. D. (1969). Equity theory: A review and critique. Organizational Behavior and Human Performance, 4(2), 176-211. https://doi.org/10.1016/0030-5073(69)90005-1
Quiles, M., Martínez, E. T., López, S., Horna, E., Montesano, L., Fernández, L., y Huertas, A. (2024). Data fusion in neuromarketing: Multimodal analysis of biosignals, lifecycle stages, current advances, datasets, trends, and challenges. Information Fusion, https://doi.org/10.1016/j.inffus.2024.102231
Ramos-Rodríguez, A.-R., y Ruíz-Navarro, J. (2004). Changes in the intellectual structure of strategic management research: A bibliometric study of the Strategic Management Journal, 1980–2000. Strategic Management Journal, 25(10), 981-1004. https://doi.org/10.1002/smj.397
Rodríguez, V. J. C., Antonovica, A., Martín, D. L. S., y Sebastián, M. G. de B. (2022). El estudio del branding y el packaging desde el campo del neuromarketing: Una revisión bibliométrica. Revista de Estudios Empresariales. Segunda Época, 197-229. https://doi.org/10.17561/ree.n2.2022.6885
Shahzad, M. F., Yuan, J., Arif, F., y Waheed, A. (2024). Inside out. Social media videos and destination branding. Neuromarketing using EEG technique. Journal of Islamic Marketing, 15(3), 886-918. https://doi.org/10.1108/JIMA-08-2022-0236
Small, H. (1973). Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, 24(4), 265-269. https://doi.org/10.1002/asi.4630240406
Thomas, A. R. (2016). Introduction. En Ethics and Neuromarketing: Implications for Market Research and Business Practice (pp. 1-3). Scopus. https://doi.org/10.1007/978-3-319-45609-6_1
Tomás-Górriz, V., y Tomás-Casterá, V. (2018). La Bibliometría en la evaluación de la actividad científica. Hospital a Domicilio, 2(4), https://doi.org/10.22585/hospdomic.v2i4.51
Watanuki, S. (2024). Identifying distinctive brain regions related to consumer choice behaviors on branded foods using activation likelihood estimation and machine learning. Frontiers in Computational Neuroscience, https://doi.org/10.3389/fncom.2024.1310013
Zupic, I., y Čater, T. (2015). Bibliometric Methods in Management and Organization. Organizational Research Methods, 18(3), 429-472. https://doi.org/10.1177/1094428114562629