A Comparative Analysis of Source Credibility Between Virtual and Human Influencers on the Purchase Intention of Generation Z

alya Al-Ariqa; Tomy Dwi  Cahyono

doi:10.47747/ijbme.v7i3.3565

Authors

alya Al-Ariqa Universitas Teknologi Sumbawa
Tomy Dwi Cahyono Universitas Teknologi Sumbawa

DOI:

https://doi.org/10.47747/ijbme.v7i3.3565

Keywords:

Human Influencer, Virtual Influencer, Source Credibility, Purchase Intention

Abstract

The rapid advancement of artificial intelligence in digital marketing has introduced a new paradigm through the emergence of virtual influencers (VI) as substitutes for human influencers (HI). The presence of this algorithm-driven artificial appeal raises strategic questions regarding its effectiveness in shaping customer purchasing decisions. The objective of this study is to analyze how Generation Z consumers' perceptions of source credibility differ between these two types of influencers and how this affects their purchase intentions. Data were collected from 116 students at the Faculty of Economics and Business, Universitas Teknologi Sumbawa (UTS), utilizing a quantitative method with a causal-associative approach and multiple assessments. Linear regression modeling and Paired Sample T-Tests were employed for data analysis. The comparative test findings verify that human influencers generate a higher purchase intention (M=16.65 vs. M=15.58) and are considered significantly more credible (M=4.184 vs. M=3.917). However, regression analysis reveals that because the virtual influencer model eliminates the possibility of human error, it provides slightly superior causality prediction power and accuracy (R²=94.0% vs. R²=91.8%). Partial testing of the human influencer group indicates that the primary factors driving increased purchase intention are emotional closeness (X2.4) and review honesty (X2.5). These results provide strategic guidance for marketers on how to maximize the collaboration between human and computational efforts.

Downloads

Download data is not yet available.

References

Arora, A., Bansal, S., Kandpal, C., Aswani, R., & Dwivedi, Y. (2019). Measuring social media influencer index- insights from facebook, Twitter and Instagram. Journal of Retailing and Consumer Services, 49, 86–101. https://doi.org/10.1016/j.jretconser.2019.03.012

Arsenyan, J., & Mirowska, A. (2021). Almost human? A comparative case study on the social media presence of virtual influencers. International Journal of Human-Computer Studies, 155, 102694. https://doi.org/10.1016/j.ijhcs.2021.102694

Backaler, J. (2018). Digital influence: Unleash the power of influencer marketing to accelerate your global business. Springer International Publishing. https://doi.org/10.1007/978-3-319-78396-3

Flavián, C., Ibáñez-Sánchez, S., & Orús, C. (2021). Impacts of technological embodiment through virtual reality on potential guests' emotions and engagement. Journal of Hospitality Marketing & Management, 30(3), 1–20. https://doi.org/10.1080/19368623.2020.1770146

Campbell, C., & Farrell, J. R. (2020). More than meets the eye: The functional components underlying influencer marketing. Business Horizons, 63(4), 469–479. https://doi.org/10.1016/j.bushor.2020.03.003

Manifest Media. (2025, May 8). 80% of Gen Z consumers trust influencers over celebrity endorsements report. https://www.manifest-media.in/marketing/080525/80-gen-z-consumers-trust-influeners-over-celebrity-endorsements-rep.html

Lou, C., & Yuan, S. (2019). Influencer marketing: How message value and credibility affect consumer trust of branded content on social media. Journal of Interactive Advertising, 19(1), 58–73. https://doi.org/10.1080/15252019.2018.1533501

Lou, C., Kiew, S. T. J., Chen, T., Lee, M. T. Y., Ong, C. J. E., & Phua, Z. (2023). Authentically fake? How consumers respond to the influence of virtual influencers. Journal of Advertising, 52(4), 540–557. https://doi.org/10.1080/00913367.2022.2149641

Mei, Y., Geng, L., Cao, X., & Xie, Y. (2025). Artificial intelligence in green marketing: A systematic literature review. Sustainability, 17(22), Article 10382. https://doi.org/10.3390/su172210382

Moustakas, E., Lamba, N., Mahmoud, D., & Ranganathan, C. (2020). Blurring lines between fiction and reality: Perspectives of experts on marketing effectiveness of virtual influencers. 2020 International Conference on Cyber Security and Protection of Digital Services (Cyber Security), 1–6. https://doi.org/10.1109/CyberSecurity49315.2020.9138861

Ohanian, R. (1990). Construction and validation of a scale to measure celebrity endorsers' perceived expertise, trustworthiness, and attractiveness. Journal of Advertising, 19(3), 39–52. https://doi.org/10.1080/00913367.1990.10673191

Sands, S., Ferraro, C., Demsar, V., & Chandler, G. (2022). False idols: Unpacking the opportunities and challenges of falsity in the context of virtual influencers. Business Horizons, 65(6), 777–788. https://doi.org/10.1016/j.bushor.2022.08.002

Sankaran, R. (2023). Measuring consumer perception of overall brand equity drivers for m-payments. International Journal of Bank Marketing, 41(1), 130–157. https://doi.org/10.1108/IJBM-03-2022-0113

Thomas, V. L., & Fowler, K. (2021). Close encounters of the AI kind: Use of AI influencers as brand endorsers. Journal of Advertising, 50(1), 11–25. https://doi.org/10.1080/00913367.2020.1810595

Vinoi, N., Shankar, A., Alzeiby, E. A., Gupta, P., & Agarwal, V. (2024). Unveiling customer intentions: Exploring factors driving engagement with hospitality virtual influencers. Journal of Hospitality Marketing & Management. Advance online publication. https://doi.org/10.1080/19368623.2024.2429505