Enterprise AI Analysis
The Impact of Integrated AI and AR in E-Commerce: The Roles of Personalization, Immersion, and Trust in Influencing Continued Use
This study explores how the integration of Artificial Intelligence (AI) and Augmented Reality (AR) in e-commerce impacts user behavior, specifically continued usage intention. Using the S-O-R framework and trust transfer theory, the research investigates the roles of personalized recommendation (AI-driven stimulus), immersion (AR-driven experiential path), perceived usefulness (cognitive path), and platform trust (moderator). Key findings include that personalized recommendation positively influences both immersion and perceived usefulness, and platform trust significantly strengthens these effects. Both immersion and perceived usefulness stimulate positive emotions, which in in turn drive continued usage intention, with perceived usefulness having a stronger effect. A novel finding is the significant positive correlation between perceived usefulness and immersion, indicating a coupling of psychological paths. However, immersion does not moderate the effect of personalized recommendation on emotional responses, suggesting a structural rather than real-time interactive integration. The study extends S-O-R theory by conceptualizing a dual cognitive-experiential path, enriches trust transfer theory by identifying trust as a moderator, and provides nuanced understanding of AI-AR integration as primarily structural.
Executive Impact
Quantified Insights for Your Enterprise
The findings underscore the importance of a holistic AI-AR integration strategy in e-commerce, moving beyond isolated functional enhancements. Enterprises should focus on building user trust as a foundational element, as it significantly amplifies the impact of personalized recommendations on both user engagement (immersion) and utility perception. The asymmetry in emotional drivers (cognitive usefulness being stronger than immersion) suggests that while immersive experiences are valuable, their primary role might be in long-term brand building and fostering a stable psychological connection rather than immediate emotional boosts from recommendations. This implies a need for a 'structural integration' approach where AI and AR synergistically create a coherent user experience, rather than expecting real-time interactive moderation between them. Practical implications include developing seamless data-experience loops, transparent algorithm logic, and designing AR for utilitarian products with a focus on efficacy, while for hedonic products, emphasizing rich immersive narratives for sustained loyalty.
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PR -> Immersion (H1a)
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PR -> Perceived Usefulness (H1b)
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Immersion -> Emotional Response (H3)
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Perceived Usefulness -> Emotional Response (H4)
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Emotional Response -> Continued Usage (H5)
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Trust moderates PR -> Immersion (H2a)
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Trust moderates PR -> Perceived Usefulness (H2b)
Deep Analysis & Enterprise Applications
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Comparison
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💡Cognition over Immersion
Perceived Usefulness (β=0.273) has a stronger impact on Emotional Response than Immersion (β=0.131), highlighting the utilitarian nature of e-commerce.
Integrated AI-AR Psychological Mechanism
Personalized Recommendation
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Perceived Usefulness & Immersion (Coupled)
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Positive Emotional Response
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Continued Usage Intention
| Aspect | Structural Coupling | Processual Coupling |
|---|---|---|
| Definition | Multiple technologies jointly construct a stable, unified psychological foundation. | One technology dynamically moderates or modifies the real-time effect of another. |
| Mechanism | AI dynamically configures AR content; AR generates contextual data for AI. | Immersion directly moderates the real-time emotional impact of recommendations (not supported in this study). |
| User Impact | Enhances overall experiential value through combined cognitive evaluations and experiential perceptions. | Aims for immediate, dynamic adjustments to emotional responses based on real-time interaction. |
| Finding in this study | Supported (PU & IM are coupled; TR moderates PR to PU/IM). | Not supported (IM does not moderate PR to ER). |
AI-AR in E-commerce: Lacoste & TopShop
Lacoste's virtual shoe try-on and TopShop's virtual dressing room applications exemplify how AI enhances user experiences by leveraging individual profiles, historical preferences, and browsing histories to provide personalized AR content. This transition from static AR experiences to intelligent, contextually adaptive ones significantly increases depth, personal relevance, and decision-making value. This aligns with the study's finding that AI-driven personalization (PR) positively impacts immersion (IM) and perceived usefulness (PU), driving richer user engagement.
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Your Enterprise AI Implementation Roadmap
Our phased approach ensures a seamless integration of AI and AR, maximizing impact with minimal disruption.
Phase 1: Foundational Trust & Data Integration
Establish robust data infrastructure and privacy protocols to build foundational platform trust. Implement transparent AI recommendation logic and secure data handling for AR interactions to enhance user confidence.
Phase 2: Dual-Path Optimization (Cognitive & Experiential)
Develop AI recommendation systems for heightened personalization and AR experiences for deeper immersion. Focus on the coupling effect, ensuring AR content is dynamically configured by AI to align with user preferences, thereby enhancing both perceived usefulness and immersive quality.
Phase 3: Emotion-Driven Engagement & Continuous Use
Design interaction points to elicit positive emotional responses by showcasing the utility and delight of integrated AI-AR. Implement continuous feedback loops to refine recommendations and AR experiences, driving sustained user engagement and loyalty.
Phase 4: Structural Integration Refinement
Analyze long-term user behavior to understand how the stable psychological structure (cognitive evaluation + experiential perception) influences overall value. Prioritize iterative improvements that reinforce the coherent, integrated experience over immediate, dynamic moderation between AI/AR functions.
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