Physical Humanlikeness as A Moderator of The Relationship Between AI Influencer Marketing and Purchase Intention
DOI:
https://doi.org/10.35870/ijmsit.v6i1.7072Keywords:
Physical Humanlikeness, AI Influencer Marketing, Purchase IntentionAbstract
The purpose of this study is to examine the role of AI influencers in enhancing social media user experience, strengthened by physical human likeness as a moderating variable to reinforce the purchasing experience. This study employs a quantitative method with a sample of 250 respondents who have experience in purchasing through artificial intelligence. The data analysis technique used is SEM-PLS, conducted using SmartPLS 4.0. Artificial intelligence improves customer interaction and engagement, which in turn increases purchase intention. Additionally, Companies should integrate human-like elements into AI services, such as more empathetic communication styles, personalized responses, and the ability to capture customers’ emotional context. This approach enhances customer engagement and experience, ultimately increasing purchase intention. This study extends the literature in AI marketing by demonstrating that the success of AI is not solely dependent on technological advancement, but also on its ability to create interaction experiences that resemble human interactions.
Downloads
References
Audrezet, A., & Koles, B. (2023). Virtual influencers: A study of consumer perceptions and engagement. Journal of Marketing Management, 39(5–6), 567–589.
Baron-Cohen, S. (1995). Mindblindness: An essay on autism and theory of mind. MIT Press.
Block, E., & Lovegrove, R. (2021). Discordant storytelling, audience engagement, and the emergence of virtual influencers. Journal of Marketing Management, 37(1–2), 79–109. https://doi.org/10.1080/0267257X.2020.1803486
Campbell, C., Sands, S., Ferraro, C., Tsao, H. Y. J., & Mavrommatis, A. (2020). From data to action: How marketers can leverage AI. Business Horizons, 63(2), 227–243. https://doi.org/10.1016/j.bushor.2019.12.002
Chetioui, Y., Benlafqih, H., & Lebdaoui, H. (2020). How fashion influencers contribute to consumers’ purchase intention. Journal of Fashion Marketing and Management, 24(3), 361–380. https://doi.org/10.1108/JFMM-08-2019-0157
Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). SAGE Publications.
Deng, X., & Jiang, P. (2023). Exploring the impact of virtual influencers on consumer behavior. Journal of Interactive Advertising, 23(2), 145–160.
Geyser, W. (2024). Influencer marketing benchmark report 2024. Influencer Marketing Hub. https://influencermarketinghub.com
Ghozali, I. (2018). Aplikasi analisis multivariate dengan program IBM SPSS 25. Badan Penerbit Universitas Diponegoro.
Gray, H. M., Gray, K., & Wegner, D. M. (2007). Dimensions of mind perception. Science, 315(5812), 619. https://doi.org/10.1126/science.1134475
Gray, K., & Wegner, D. M. (2012). Feeling robots and human zombies: Mind perception and the uncanny valley. Cognition, 125(1), 125–130. https://doi.org/10.1016/j.cognition.2012.06.007
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2019). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). SAGE Publications.
Jiang, L., Qin, Y., et al. (2024). Human-like AI influencers and consumer engagement. Journal of Interactive Marketing.
Ju, Y., et al. (2024). Emotional expression and authenticity in virtual influencers. Computers in Human Behavior, 145, 107789.
Kim, T., & Duhachek, A. (2020). Artificial intelligence and consumer responses. Journal of Consumer Research, 47(4), 563–582.
Kim, T., et al. (2022). Humanizing AI: The role of mind perception. Journal of Marketing Research, 59(3), 456–473.
Kumar, V., Dixit, A., Javalgi, R. R. G., & Dass, M. (2019). Research framework for the role of artificial intelligence in marketing. Journal of Business Research, 98, 135–145. https://doi.org/10.1016/j.jbusres.2019.01.016
Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 140, 1–55.
Mariani, M., et al. (2022). Virtual influencers in marketing: A systematic review. Psychology & Marketing, 39(10), 1925–1945.
Moustakas, E., et al. (2020). The rise of virtual influencers. Journal of Marketing Management, 36(11–12), 1050–1070.
Shen, B. (2021). Social media influencers and fashion marketing. Fashion and Textiles, 8(1), 1–15.
Shen, Z. (2021), “A persuasive eWOM model for increasing consumer engagement on social media: evidence from Irish fashion micro-influencers”, Journal of Research in Interactive Marketing, Vol. 15 No. 2, pp. 181-199, doi: 10.1108/jrim-10-2019-0161.
Stein, J. P., et al. (2022). Perceived humanness and AI acceptance. Computers in Human Behavior, 128, 107106.
Thomas, V. L., & Fowler, K. (2021). Close encounters of the AI kind: Understanding consumer responses to AI influencers. Business Horizons, 64(3), 369–378. https://doi.org/10.1016/j.bushor.2021.01.003
Wan, Y., & Jiang, P. (2023). Virtual influencers and purchase intention: Evidence from social media. Electronic Commerce Research, 23(4), 2101–2120.
Wang, C.L. (2024), “Editorial– what is an interactive marketing perspective and what are emerging research areas?”, Journal of Research in Interactive Marketing, Vol. 18 No. 2, pp. 161-165, doi: 10.1108/jrim-03-2024-371
Wang, X. (2024). Aesthetic appeal and influencer marketing effectiveness. Journal of Retailing and Consumer Services, 75, 103456.
Wiedmann, K. P., & von Mettenheim, W. (2021). Attractiveness, trustworthiness, and expertise in influencer marketing. Journal of Business Research, 134, 576–585.
Wiedmann, K.-P. and von Mettenheim, W. (2021), “Attractiveness, trustworthiness and expertise social influencers’ winning formula?”, The Journal of Product and Brand Management, Vol. 30 No. 5, pp. 707-725, doi: 10.1108/jpbm-06-2019-2442.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Rahyono, Ayu Nursari, Lestari Wuryanti, Reza Hardian Pratama
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
1. Copyright Retention and Open Access License
Authors retain copyright of their work and grant the journal non-exclusive right of first publication under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
This license allows unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
2. Rights Granted Under CC BY 4.0
Under this license, readers are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, including commercial use
- No additional restrictions — the licensor cannot revoke these freedoms as long as license terms are followed
3. Attribution Requirements
All uses must include:
- Proper citation of the original work
- Link to the Creative Commons license
- Indication if changes were made to the original work
- No suggestion that the licensor endorses the user or their use
4. Additional Distribution Rights
Authors may:
- Deposit the published version in institutional repositories
- Share through academic social networks
- Include in books, monographs, or other publications
- Post on personal or institutional websites
Requirement: All additional distributions must maintain the CC BY 4.0 license and proper attribution.
5. Self-Archiving and Pre-Print Sharing
Authors are encouraged to:
- Share pre-prints and post-prints online
- Deposit in subject-specific repositories (e.g., arXiv, bioRxiv)
- Engage in scholarly communication throughout the publication process
6. Open Access Commitment
This journal provides immediate open access to all content, supporting the global exchange of knowledge without financial, legal, or technical barriers.
