Perbandingan Efektivitas Traditional vs AI-Mediated Marketing Channels terhadap Consumer Trust di Pasar Berkembang
DOI:
https://doi.org/10.59971/jumawa.v3i3.454Keywords:
AI-mediated marketing, traditional marketing channels, consumer trust, perceived credibility, emerging marketsAbstract
The growing adoption of artificial intelligence (AI) has transformed marketing practices and reshaped how organizations build consumer trust. This study compares the effectiveness of traditional and AI-mediated marketing channels in influencing consumer trust in emerging markets. A Systematic Literature Review (SLR) was conducted using the PRISMA framework. Relevant studies published between 2020 and 2026 were retrieved from the Scopus and Web of Science databases and analyzed through thematic synthesis. The findings indicate that traditional marketing channels primarily foster affective trust through interpersonal interaction, emotional engagement, and relationship quality. In contrast, AI-mediated marketing channels enhance cognitive trust through personalization, responsiveness, efficiency, and technological reliability. The review further reveals that neither channel is universally superior; their effectiveness depends on contextual factors and consumer characteristics. Digital literacy, privacy concerns, perceived risk, technology readiness, and cultural context were identified as key moderating variables influencing trust formation in emerging markets. Based on the synthesis, this study proposes an integrated conceptual framework demonstrating that consumer trust emerges from the interaction between relational and technological dimensions. The study contributes to the literature by integrating trust and technology adoption perspectives and provides managerial insights for developing hybrid marketing strategies that combine human-centered communication with AI-driven capabilities.
Downloads
References
Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114, 106548. https://doi.org/10.1016/j.chb.2020.106548
Bach, R. L., Kern, A., Müller, S., & Schwemmer, C. (2023). Artificial intelligence and public trust: Understanding the determinants of AI acceptance. AI & Society, 38(4), 1567–1582. https://doi.org/10.1007/s00146-022-01486-1
Benk, S., Budak, T., & Yüzbaşı, B. (2023). Artificial intelligence adoption and trust formation in digital environments: A systematic review. Technological Forecasting and Social Change, 194, 122676. https://doi.org/10.1016/j.techfore.2023.122676
Bullock, J., Luccioni, A., Pham, K. H., Lam, C. S. N., & Luengo-Oroz, M. (2025). Mapping the landscape of generative AI and consumer perceptions. Business Horizons, 68(1), 13–29. https://doi.org/10.1016/j.bushor.2024.08.002
Cheng, X., Fu, S., Sun, J., Bilgihan, A., & Okumus, F. (2023). Consumer trust toward AI-enabled services: The roles of perceived usefulness and technology readiness. SAGE Open, 13(4), 1–15. https://doi.org/10.1177/21582440231222760
Davenport, T. H., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), 24–42. https://doi.org/10.1007/s11747-019-00696-0
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M., Al-Busaidi, K. A., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., ... Wright, R. (2023). So what if ChatGPT wrote it? Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
Gonçalves, J., Sousa, M. J., & Pereira, F. S. (2023). Artificial intelligence, privacy concerns and consumer trust: A systematic review. Journal of Business Research, 165, 114073. https://doi.org/10.1016/j.jbusres.2023.114073
Grewal, D., Guha, A., Satornino, C. B., & Schweiger, E. B. (2021). Artificial intelligence in marketing: Impacts, challenges, and future research agenda. Journal of Business Research, 125, 194–204. https://doi.org/10.1016/j.jbusres.2020.11.020
Hasan, M. R., & Mayr, S. (2025). Consumer trust and authenticity perceptions toward AI-generated marketing content. Journal of Interactive Marketing, 70, 101–118.
Hoyer, W. D., Kroschke, M., Schmitt, B., Kraume, K., & Shankar, V. (2020). Transforming the customer experience through new technologies. Journal of Interactive Marketing, 51, 57–71. https://doi.org/10.1016/j.intmar.2020.04.001
Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49(1), 30–50. https://doi.org/10.1007/s11747-020-00749-9
Khan, M. A., & Mishra, S. (2023). Artificial intelligence-enabled marketing and consumer trust: Evidence from emerging economies. Journal of Retailing and Consumer Services, 73, 103364. https://doi.org/10.1016/j.jretconser.2023.103364
Longoni, C., Bonezzi, A., & Morewedge, C. K. (2022). Resistance to medical artificial intelligence. Journal of Consumer Research, 48(4), 629–650. https://doi.org/10.1093/jcr/ucab042
Martin, K. D., & Murphy, P. E. (2017). The role of data privacy in marketing. Journal of the Academy of Marketing Science, 45(2), 135–155. https://doi.org/10.1007/s11747-016-0495-4
Puntoni, S., Reczek, R. W., Giesler, M., & Botti, S. (2021). Consumers and artificial intelligence: An experiential perspective. Journal of Marketing, 85(1), 131–151. https://doi.org/10.1177/0022242920953847
Shavitt, S., & Barnes, A. J. (2020). Culture and consumer behavior: The role of horizontal and vertical cultural factors. Current Opinion in Psychology, 32, 149–154. https://doi.org/10.1016/j.copsyc.2019.08.026
Sheth, J. N. (2020). Borderless media: Rethinking international marketing. Journal of International Marketing, 28(1), 3–12. https://doi.org/10.1177/1069031X19897044
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
