Assessing Consumer Perception in Muslim-made Cosmetics: A Relationship Quality Perspective

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Kurnia Budhy Scorita, Agung Wahyu Handaru, Setyo Ferry Wibowo

2025 Journal of Applied Data Sciences Vol. 7 Issue 1 Article Cited by 0 SDG 12SDG 8SDG 16 Quartile

Abstract

This study investigates the drivers of repurchase intention in the Muslim-made cosmetics market by examining the mediating roles of trust and satisfaction within a relationship quality framework. Grounded in Relationship Quality Theory and the Stereotype Content Model, the research integrates perceived product quality, brand image, and perceived AI warmth as key antecedents influencing consumer loyalty. A comparative analysis of two structural models (Model 1 and Model 2) is conducted to explore the directionality of the mutually reinforcing relationship between trust and satisfaction. Data were collected via structured online surveys from 439 Muslim consumers in Jakarta, Indonesia, and analyzed using PLS-SEM. Findings reveal that perceived AI warmth is the strongest predictor of both trust (t=7.587, p<0.001) and satisfaction (t=8.874, p<0.001). In Model 1, trust significantly precedes satisfaction (t=4.869, p<0.001); conversely, in Model 2, satisfaction reciprocally enhances trust (t=5.280, p<0.001), supporting a dynamic, co-evolutionary process. Perceived product quality significantly impacts trust (t=3.780, p<0.001) but only affects satisfaction when satisfaction is modeled as an antecedent to trust (Model 2: t=1.984, p=0.048). Brand image exerts a strong effect on satisfaction (Model 1: t=4.235, p<0.001; Model 2: t=4.855, p<0.001) but loses its direct path to trust in Model 2. Both trust and satisfaction have significant direct effects on repurchase intention (Model 1, Trust t=4.577, p<0.001, Satisfaction t=8.538, p<0.001; Model 2, Trust: t=4.630, p<0.001; Satisfaction t=8.130, p<0.001). The study validates the dual mediating roles of trust and satisfaction in translating perceptions of product quality, brand symbolism, and AI-induced warmth into behavioral loyalty. Theoretically, it advances a reciprocal, experience-driven model of relationship quality, extending prior discussions of reciprocity beyond traditional unidirectional frameworks. Practically, it offers actionable insights for marketers seeking to leverage AI personalization and identity-based branding to cultivate long-term loyalty in culturally sensitive, value-driven markets. © 2025, Bright Publisher. All rights reserved.

Affiliations

Department of Management, School of Postgraduate, Universitas Negeri Jakarta, Jakarta, 13220, Indonesia; Department of Management, Faculty of Economics and Business, Universitas Negeri Jakarta, Jakarta, 13220, Indonesia

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