Digital Twins in Tourism: Emerging Practices, Challenges, and Future Directions

Authors: Sarah Johnson

Affiliation: Independent researcher

Abstract

Digital twin (DT) technology—virtual replicas of physical environments—has attracted increasing attention in tourism. This article presents a high-level review of recent advances in the application of digital twins to tourism, based on a systematic literature review. Findings reveal that most DT studies focus on cultural tourism and destination management, primarily at site‑level scales. While theoretical frameworks have progressed, real‑time data synchronization remains rare. Key challenges include data integration, technical complexity, and stakeholder readiness. To advance the field, we recommend four pathways: enhancing real‑time integration, focusing on visitor experience and wellbeing, engaging local communities, and standardizing evaluation metrics. Implications for academics, policymakers, and industry are discussed.

1. Introduction

In an era characterized by rapid digitalization and sustainability demands, digital twins (DTs) emerge as a promising innovation in tourism management. Originally developed for industrial engineering, DTs now offer virtual replicas of real-world tourist destinations. This enables simulation, monitoring, and optimizing operations—improving efficiency, visitor experience, and cultural preservation.

Recent trends show growing interest: over 900 Scopus‑indexed papers discuss AI applications in tourism, indicating DTs’ rising relevance. A recent systematic literature review (SLR) found 34 peer‑reviewed DT studies in tourism, showing early-stage development in both theory and practice arXiv.

2. Methodological Background

The SLR followed established bibliometric and thematic analysis methods. Thirty-four articles across Scopus databases were selected and analyzed. Studies were categorized by:

1. Tourism type (cultural, environmental, recreational)

2. Application purpose (destination management, heritage preservation)

3. Spatial scale (site‑level, regional, system-wide)

4. Data linking methods (static vs. synchronized real-time)

5. Nature of contribution (theoretical, applied) arXiv

This structured approach highlights research gaps and future opportunities.

3. Key Findings

3.1 Focus on Cultural Tourism

Majority of studies examine cultural sites—museums, heritage districts, ancient ruins. DTs assist in digitizing intangible heritage: spatial layouts, objects, visitor flows. Applications include simulating crowd movement, facilitating restoration planning, and enhancing virtual tours.

3.2 Destination Management as Primary Purpose

DTs are mostly deployed for planning and management: forecasting foot traffic, modeling environmental impacts, and optimizing resource allocation. Researchers emphasize DTs' role in smart tourism platforms, enabling stakeholders to test scenarios without risking physical damage.

3.3 Spatial Scale at Site Level

Most DTs operate at the scale of a single location—e.g., an archaeological site, a museum hall. Larger-scale models (city-level or region-level) are rare due to data and technical constraints.

3.4 Data Linkage Mostly Unilateral

Few studies achieve bilateral data synchronization. Many deploy one-time scans or periodic updates. Real-time sensors and IoT integration are limited, preventing dynamic reflection of real-world changes.

3.5 Applied Studies Surpass Theory

The field leans toward applied research—with prototyping, case studies, and pilot implementations. Theoretical models exist, but practical validation remains limited. Translational gaps between theory and real deployment persist.

4. Challenges and Bottlenecks

Several hurdles impede DT uptake in tourism:

1. Data Integration Complexity – Collecting, processing, and linking diverse data sources (LiDAR, visitor metrics, climate data) is technically demanding.

2. Real-Time Synchronization – Live updates require IoT infrastructure, robust data connectivity, and seamless integration—rarely available at tourist sites.

3. Scalability Constraints – Extending DTs from single sites to regional networks increases complexity exponentially.

4. Stakeholder Engagement – Success depends on coordination among authorities, site staff, tourists, tech vendors—each with unique priorities and skills.

5. Standardization Gaps – Lack of common benchmarks for performance, usability, and sustainability evaluation makes cross-case learning difficult.

5. Implications for Stakeholders

5.1 For Practitioners and Tourism Managers

• Adopt modular DT frameworks: Begin with small pilots—e.g., a museum wing or plaza—before scaling.

• Invest in sensorization: Deploy IoT-enabled devices to enable real-time data.

• Use DTs for crisis simulation: Model crowd behaviors during emergencies to improve safety protocols.

5.2 For Policymakers

• Support infrastructure: Offer funding for digitalization projects and broadband access at heritage sites.

• Foster training: Build capacity in local teams for DT creation and maintenance.

• Promote open standards: Encourage adoption of interoperable data formats and APIs.

5.3 For Researchers

• Advance synchronization strategies: Explore AI and edge‑computing methods for live updates.

• Evaluate user impact: Measure how DT-enhanced experiences affect visitor satisfaction, learning, and sustainability.

• Benchmark studies: Develop metrics to evaluate technical performance, cost‑benefit, and social impact.

6. Future Research Directions

Drawing on the SLR analysis, four key research pathways are proposed:

6.1 Real-Time Integration and Adaptive Modeling

• Combine edge AI with IoT to enable DTs that update continuously.

• Integrate weather, social media, footfall and event data to dynamically optimize management decisions.

6.2 Visitor Experience and Well‑Being

• Assess how DTs enhance interpretation, accessibility, and engagement.

• Explore virtual and augmented reality overlays to enrich on-site learning.

6.3 Community Engagement and Co‑creation

• Involve local guides and communities in DT design to embed cultural values.

• Use DTs for participatory planning, giving locals visibility into tourism effects and preserving authenticity.

6.4 Standardization of Metrics and Evaluation

• Establish cross-case studies with common indicators: technical performance, economic viability, social acceptance, sustainability.

• Use comparative databases to identify best practices.

7. Conclusion

Digital twins offer transformative potential for tourism, yet their use remains nascent. Current work focuses on cultural, site-level applications with limited real-time synchronization. Overcoming technical, social, and standardization barriers is crucial. By pursuing enhanced integration, user-centered design, community involvement, and systematic evaluation, DTs can become powerful tools for sustainable, smart tourism.

5 Hashtags

#DigitalTwinTourism

#SmartDestination

#HeritageDigitization

#SustainableTourism

#TourismInnovation

References

• Almeida, D. S. de, Abreu, F. B. e, & Boavida‑Portugal, I. (2025). Digital twins in tourism: a systematic literature review.

• Carvalho, L., & Ivanov, S. (2024). Generative AI in hospitality: opportunities and risks.

• Gursoy, D., et al. (2023). AI applications in tourism and hospitality.

• Shi, Y., et al. (2024). Technology trends in destination management.

• Sampaio de Almeida, D., Brito e Abreu, F., & Boavida‑Portugal, I. (2025). Title as above.

• World Economic Forum. (2025). Future of Jobs Report.

• Additional sources on digital twin frameworks and IoT protocols.