Enterprise AI Analysis
Unpacking digital heritage experiences using PLS SEM and fsQCA through a perception-place behavior model
This research delves into how Digital Twin Technology (DTT) influences tourist behavior in cultural heritage. It unveils two key pathways: a cognitive route via perceived realism and cultural identity, and an emotional route through narrative immersion and place attachment. Cultural capital significantly modulates these paths. The study also identifies multiple sufficient configurations for behavioral intentions, moving beyond simple linear models to highlight the complex interplay of psychological factors and technology. This leads to a novel Perception-Place-Behavior (PPB) framework, suggesting adaptive presentation strategies in digital heritage.
Key Metrics & Immediate Impact
For enterprises leveraging Digital Twin Technology (DTT) in cultural heritage, this research provides actionable insights into optimizing user engagement and fostering sustainable behavioral intentions. By understanding the distinct cognitive and emotional pathways, businesses can tailor their DTT applications to maximize cultural appreciation and environmental respect.
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Increased Cultural Identity (CI)
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Enhanced Place Attachment (PA)
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Lift in Cultural Respect Intentions (CRI)
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Cognitive Pathway
Focuses on how perceived realism and cultural identity drive user engagement and behavioral intentions, particularly for cultural respect. High cultural capital can temper the direct realism-to-identity link by encouraging critical engagement.
Perception-Place-Behavior (PPB) Model Flow
Perceived Realism (PR)
→
Cultural Identity (CI)
→
Place Attachment (PA)
→
Behavioral Intentions (EBI/CRI)
The PPB model illustrates a layered process where technical perception influences identity, which then consolidates into emotional attachment, ultimately leading to behavioral intentions. This model integrates technology acceptance with cultural theory, offering a holistic view of user psychology in digital heritage contexts.
Cultural Capital's Dual Impact
-11.5%
Moderation Effect on PR → CI
Cultural capital negatively moderates the perceived realism to cultural identity path (β = -0.115, p = 0.032). This suggests that higher cultural capital can lead to critical distancing from hyper-realistic presentations, as knowledgeable users may prioritize evidential grounding over surface spectacle.
Emotional Pathway
Explores the role of narrative immersion and place attachment in fostering environmental behavior intentions. Cultural capital strengthens this path by enabling deeper narrative decoding and emotional resonance.
EBI vs. CRI: Driving Pathways
| Behavioral Intention | Dominant Pathway | Key Drivers | Implications for DTT Design |
|---|---|---|---|
| Environmental Behavior Intention (EBI) | Narrative-Attachment Route |
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| Cultural Respect Intention (CRI) | Realism-Identity Route |
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EBI is more closely tied to the narrative-attachment route, fostering environmental action through affective bonds, whereas CRI is linked to the realism-identity route, supporting normative respect via cognitive alignment. This differentiation guides targeted DTT design for specific behavioral outcomes.
Adaptive Presentation in Action: Yuanmingyuan Digital Restoration
The digital restoration project of the Yuanmingyuan (Old Summer Palace) exemplifies an adaptive presentation strategy. It not only helps visitors recognize its historical destruction but also fosters national cultural consciousness, thereby enhancing visitors' place attachment. This approach, by carefully balancing realism and narrative, demonstrates how DTT can strengthen cultural identity and emotional connection to heritage sites, moving beyond mere visual spectacle to deep cultural engagement. This project's success underscores the importance of a dual-mode system, catering to different cultural capital levels.
Methodological Approach
Highlights the dual-method strategy combining PLS-SEM for average effects and fsQCA for identifying diverse causal configurations, providing a nuanced understanding beyond linear relationships.
Perception-Place-Behavior (PPB) Model Flow
Perceived Realism (PR)
→
Cultural Identity (CI)
→
Place Attachment (PA)
→
Behavioral Intentions (EBI/CRI)
The PPB model illustrates a layered process where technical perception influences identity, which then consolidates into emotional attachment, ultimately leading to behavioral intentions. This model integrates technology acceptance with cultural theory, offering a holistic view of user psychology in digital heritage contexts.
Cultural Capital's Dual Impact
-11.5%
Moderation Effect on PR → CI
Cultural capital negatively moderates the perceived realism to cultural identity path (β = -0.115, p = 0.032). This suggests that higher cultural capital can lead to critical distancing from hyper-realistic presentations, as knowledgeable users may prioritize evidential grounding over surface spectacle.
Advanced ROI Calculator
Estimate the potential gains from implementing adaptive DTT strategies in your cultural heritage institution. Tailor your inputs to see how optimized realism and narrative can translate into measurable improvements in visitor engagement and sustainable behavior.
Estimated Annual Savings
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Annual Hours Reclaimed
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Your Implementation Roadmap
Our phased implementation approach ensures a seamless integration of adaptive DTT strategies, maximizing impact while minimizing disruption. Each phase is designed to build on the last, ensuring a robust and sustainable solution tailored to your institution's unique needs.
Phase 1: Assessment & Strategy
Comprehensive analysis of existing DTT infrastructure, content, and audience profiles. Development of a tailored adaptive presentation strategy, identifying key cognitive and emotional pathways to target.
Phase 2: Dual-Mode System Development
Design and development of 'expert mode' for high cultural capital users (rich historical context, source annotations) and 'story mode' for low cultural capital users (gamified interactions, simplified storylines).
Phase 3: Integration & Testing
Seamless integration of new DTT features into existing platforms. Rigorous A/B testing and user feedback loops to fine-tune realism, narrative, and cultural capital moderation effects for optimal engagement.
Phase 4: Continuous Optimization & Scaling
Ongoing monitoring of behavioral intentions (EBI, CRI) and iterative refinement based on performance data. Scaling adaptive strategies across additional heritage sites or content modules.
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