Ir al menú de navegación principal Ir al contenido principal Ir al pie de página del sitio

Innovación tecnológica e IA

Vol. 19 (2025): La IA y el futuro digital construyendo el camino hacia un mundo sostenible y competitivo 978-84-10470-93-4

Estudio bibliométrico sobre la intersección entre marketing e inteligencia artificial

Enviado
octubre 29, 2025
Publicado
2025-11-06

Resumen

Este artículo presenta un estudio bibliométrico sobre el marketing en el contexto de la inteligencia artificial (IA). Utilizando herramientas analíticas, se examina la evolución de la investigación en este campo, identificando las tendencias emergentes y los principales temas de interés. El análisis se basa en una extensa revisión de publicaciones académicas, incluidos artículos, conferencias y libros, para mapear la producción científica y evaluar el impacto de las investigaciones en el área. De acuerdo con una base de datos de Scopus del 2013 al 2023 con palabras claves seleccionadas como inteligencia artificial y marketing. Los resultados revelan un crecimiento significativo en el número de publicaciones relacionadas con el marketing y la IA en los últimos años. Se destacan las áreas de aplicación más prominentes, como aprendizaje automático, big data, comercio y marketing digital. Los autores discuten sobre las principales implicaciones teóricas de la investigación.

Citas

  1. Abrardi, L., Cambini, C., & Rondi, L. (2022). Artificial intelligence, firms and consumer behavior: A survey. Journal of Economic Surveys, 36(4), 969-991. https://doi.org/10.1111/joes.12455
  2. Abrokwah-Larbi, K., & Awuku-Larbi, Y. (2024). The impact of artificial intelligence in marketing on the performance of business organizations: Evidence from SMEs in an emerging economy. Journal of Entrepreneurship in Emerging Economies, 16(4), 1090-1117. https://doi.org/10.1108/JEEE-07-2022-0207
  3. Ambika, A., Shin, H., & Jain, V. (2023). Immersive technologies and consumer behavior: A systematic review of two decades of research. Australian Journal of Management, 03128962231181429. https://doi.org/10.1177/03128962231181429
  4. Di Vaio, A., Hassan, R., & Alavoine, C. (2022). Data intelligence and analytics: A bibliometric analysis of human–Artificial intelligence in public sector decision-making effectiveness. Technological Forecasting and Social Change, 174, 121201. https://doi.org/10.1016/j.techfore.2021.121201
  5. Jain, V., Wadhwani, K., & Eastman, J. K. (2024). Artificial intelligence consumer behavior: A hybrid review and research agenda. Journal of Consumer Behaviour, 23(2), 676-697. https://doi.org/10.1002/cb.2233
  6. Katsikeas, C., Leonidou, L., & Zeriti, A. (2019). Revisiting international marketing strategy in a digital era: Opportunities, challenges, and research directions. International Marketing Review, 37(3), 405-424. https://doi.org/10.1108/IMR-02-2019-0080
  7. Kibria, M. G., Nguyen, K., Villardi, G. P., Zhao, O., Ishizu, K., & Kojima, F. (2018). Big Data Analytics, Machine Learning, and Artificial Intelligence in Next-Generation Wireless Networks. IEEE Access, 6, 32328-32338. https://doi.org/10.1109/ACCESS.2018.2837692
  8. Kotler, P. (2011). Marketing: Versión para Latinoamérica. Pearson Educación de México, SA de CV. https://public.ebookcentral.proquest.com/choice/publicfullrecord.aspx?p=5134088
  9. Kronemann, B., Kizgin, H., Rana, N., & K. Dwivedi, Y. (2023). How AI encourages consu
  10. mers to share their secrets? The role of anthropomorphism, personalisation, and privacy concerns and avenues for future research. Spanish Journal of Marketing - ESIC, 27(1), 3-19. https://doi.org/10.1108/SJME-10-2022-0213
  11. Kshetri, N., Dwivedi, Y. K., Davenport, T. H., & Panteli, N. (2024). Generative artificial intelligence in marketing: Applications, opportunities, challenges, and research agenda. International Journal of Information Management, 75, 102716. https://doi.org/10.1016/j.ijinfomgt.2023.102716
  12. Nazir, S., Khadim, S., Ali Asadullah, M., & Syed, N. (2023). Exploring the influence of artificial intelligence technology on consumer repurchase intention: The mediation and moderation approach. Technology in Society, 72, 102190. https://doi.org/10.1016/j.techsoc.2022.102190
  13. Pantano, E., & Scarpi, D. (2022). I, Robot, You, Consumer: Measuring Artificial Intelligence Types and their Effect on Consumers Emotions in Service. Journal of Service Research, 25(4), 583-600. https://doi.org/10.1177/10946705221103538
  14. Pelet, J.-E., Lecat, B., Khan, J., Rundle-Thiele, S., Lee, L. W., Ellis, D., Wolf, M. M., Kavoura, A., Katsoni, V., & Wegmann, A. L. (2018). Winery website loyalty: The role of sales promotion and service attributes. International Journal of Wine Business Research, 30(2), 138-152. https://doi.org/10.1108/IJWBR-01-2017-0003
  15. Rai, A., Constantinides, P., & Sarker, S. (2019). Next generation digital platforms: Toward human-AI hybrids. 2019, 43(1), iii-ix.
  16. Rosenbloom, B. (2007). Multi-channel strategy in business-to-business markets: Prospects and problems. Industrial Marketing Management, 36(1), 4-9. https://doi.org/10.1016/j.indmarman.2006.06.010
  17. Seyyedamiri, N., & Tajrobehkar, L. (2019). Social content marketing, social media and product development process effectiveness in high-tech companies. International Journal of Emerging Markets, 16(1), 75-91. https://doi.org/10.1108/IJOEM-06-2018-0323
  18. Shah, N., Engineer, S., Bhagat, N., Chauhan, H., & Shah, M. (2020). Research Trends on the Usage of Machine Learning and Artificial Intelligence in Advertising. Augmented Human Research, 5(1), 19. https://doi.org/10.1007/s41133-020-00038-8
  19. Shi, F., Wang, J., Shi, J., Wu, Z., Wang, Q., Tang, Z., He, K., Shi, Y., & Shen, D. (2021). Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation, and Diagnosis for COVID-19. IEEE Reviews in Biomedical Engineering, 14, 4-15. https://doi.org/10.1109/RBME.2020.2987975
  20. Sung, E. (Christine), Bae, S., Han, D.-I. D., & Kwon, O. (2021). Consumer engagement via interactive artificial intelligence and mixed reality. International Journal of Information Management, 60, 102382. https://doi.org/10.1016/j.ijinfomgt.2021.102382
  21. Teepapal, T. (2025). AI-driven personalization: Unraveling consumer perceptions in social media engagement. Computers in Human Behavior, 165, 108549. https://doi.org/10.1016/j.chb.2024.108549
  22. Thakur, J., & Kushwaha, B. P. (2024). Artificial intelligence in marketing research and future research directions: Science mapping and research clustering using bibliometric analysis. Global Business and Organizational Excellence, 43(3), 139-155. https://doi.org/10.1002/joe.22233
  23. Zhao, Y., Xu, X., & Wang, M. (2019). Predicting overall customer satisfaction: Big data evidence from hotel online textual reviews. International Journal of Hospitality Management, 76, 111-121. https://doi.org/10.1016/j.ijhm.2018.03.017