Understanding the Loyalty Effects of AI-driven Personalisation: Consumer Engagement as a Mediator and Algorithmic Trust as a Boundary Condition

Mengfei Xiao, Weixiang Gan*, Qiuying Yue, Fariza Binti Hashim, Tara Ahmed Mohammed
Graduate School of Business, SEGi University, Petaling Jaya, Selangor 47810, Malaysia
*Corresponding email: gabriel1995@qq.com
https://doi.org/10.71052/srb2024/WISX5526

As digital platforms increasingly rely on AI-driven personalisation, growing evidence suggests that improvements in algorithmic efficiency do not automatically translate into stronger brand loyalty. Addressing this disconnect, this study examines how AI-driven personalisation influences brand loyalty in digital platform contexts, with particular attention to the mediating role of consumer engagement and the moderating role of algorithmic trust. Drawing on a relational value-creation perspective, a conceptual model is developed to explain how technological personalisation is transformed into relational outcomes under different trust conditions. Using a quantitative, cross-sectional design, data were collected from 398 digital platform users through a structured questionnaire based on established measurement scales. Partial least squares structural equation modelling (PLS-SEM) was employed to test the proposed model after confirming measurement reliability, validity, and the absence of serious common method bias. The results show that AI-driven personalisation has a significant positive effect on brand loyalty and strongly enhances consumer engagement, which in turn positively influences brand loyalty and partially mediates the personalization-loyalty relationship. Furthermore, algorithmic trust emerges as a critical boundary condition, significantly strengthening both the effect of AI-driven personalisation on consumer engagement and the effect of consumer engagement on brand loyalty. These findings suggest that personalisation generates relational value not merely through technical accuracy, but through its capacity to activate consumer engagement within a trusted algorithmic environment. By integrating consumer engagement and algorithmic trust into a unified framework, this study advances existing research on AI-enabled marketing and brand loyalty and provides practical insights for digital platforms seeking to align personalisation strategies with long-term relationship building.

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Xiao, M., Gan, W., Yue, Q., Hashim, F. B., Mohammed, T. A. (2025) Understanding the Loyalty Effects of AI-driven Personalisation: Consumer Engagement as a Mediator and Algorithmic Trust as a Boundary Condition. Scientific Research Bulletin, 2(3), 39-58. https://doi.org/10.71052/srb2024/WISX5526

Published

18/12/2025