# Spiritual Trust in AI Systems: Investigating the Role of Ta‘abbud in Personalized E-Commerce for Generation Z
> Syahraeni

URL kanonis: https://discover.unhas.ac.id/publications/pub_scopus_105033370019
Jurnal / Konferensi: Al Muamalat
Tahun terbit: 2025
DOI: https://doi.org/10.15575/am.v12i2.46646
ISSN: 20863225
Citations: 2

## Authors
- Syahraeni

## Abstract
The rapid growth of AI-based e-commerce has yet to integrate spiritual values such as ta‘abbud, essential for Muslim consumers in fostering trust and holistic well-being. This study aims to explore the role of ta‘abbud in AI recommendation systems, enhancing consumer well-being materially and spiritually through increased consumer trust. The research is grounded in four theoretical frameworks: the Technology Acceptance Model (TAM), Consumer Well-Being, Consumer Behavior, and AI Personalization. The study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess relationships between variables. Data were collected via a stratified sampling questionnaire involving 240 Generation Z respondents. The findings reveal that information accessibility significantly influences the shopping experience (R² = 0.743), whereas recommendation quality moderately affects consumer trust (R² = 0.724). Furthermore, AI-based recommendation personalization enhances consumer well-being (R² = 0.635) by improving trust and recommendation relevance (R² = 0.586). Although the effect of ta‘abbud is relatively small, it plays a meaningful role in shaping trust in AI systems, particularly for halal product purchases. This study offers practical implications for Sharia-compliant e-commerce in building consumer loyalty through value-based strategies.

## Keywords
- Structural equation modeling
- Personalization
- Relevance (law)
- Product (mathematics)
- Psychology
- Quality (philosophy)
- Loyalty
- Consumer behaviour
- Knowledge management
- Marketing
- Partial least squares regression
- Data collection
- Confirmatory factor analysis
- Preference
- Social psychology
- Sampling (signal processing)
- Recommender system
- Business
- Applied psychology
- Advertising
- Diversity (politics)
- Computer-assisted web interviewing
- Experience sampling method

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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