Digital Twins in Tourism: A Sociological Reframing of Smart, Sustainable Destinations in 2025
- OUS Academy in Switzerland
- Sep 3
- 10 min read
Author: Bilal Malik
Affiliation: Independent researcher
Abstract
Digital twin technology—the creation of a dynamic, data-rich virtual representation of a physical asset, process, or place—has accelerated rapidly across the tourism sector in 2025. This week’s professional discourse again highlights the move from small pilots to destination-wide platforms that simulate visitor flows, resource consumption, and environmental impacts in near real time. This paper offers an academic, yet simple, critical sociology perspective on this trend. It integrates conceptual and technical insights with social theory, including Bourdieu’s concept of capital, world-systems theory, and institutional isomorphism, to examine how digital twins may reshape governance, markets, and everyday experiences in tourism. The argument is threefold. First, digital twins have clear operational value for optimizing demand management, sustainability, accessibility, and risk preparedness. Second, their deployment is not purely technical: it redistributes power, reorders who gains symbolic and economic capital, and can reproduce global core–periphery inequalities if uncritical imitation prevails. Third, ethically grounded governance and inclusive capacity building can turn digital twins into a tool for shared prosperity and environmental stewardship rather than a new layer of digital dependency. The paper concludes with a practical implementation roadmap, measurable indicators, and research priorities for 2025–2030.
Keywords: digital twins; tourism; smart destinations; sustainability; data governance; Bourdieu; world-systems; institutional isomorphism; visitor management; responsible innovation
1. Introduction: Why Digital Twins, Why Now?
Tourism is under pressure to become more sustainable, equitable, and resilient. Visitor peaks strain infrastructure; climate hazards disrupt seasons; and local communities expect benefits rather than burdens. Digital twin technology has become a leading candidate to address these challenges. In tourism, a digital twin is a living model of a destination—streets, heritage sites, transport, accommodations, ecosystems—fed by streams of data (sensors, bookings, mobility traces, weather, prices) and analyzed by algorithms to support planning and real-time operations.
What is distinctive in 2025, and visible in sector discussions this week, is not the novelty of the idea but its spread: destinations are scaling from single-site models to integrated, region-wide systems. The focus is moving from visualization to decision support—shaping policies on carrying capacity, congestion pricing, energy optimization, and climate adaptation. At the same time, the social consequences are more apparent. Who controls the models? Whose data are represented? Who has the skills to interpret and govern them? These questions invite a sociological analysis that looks beyond efficiency to power, legitimacy, and justice.
2. Conceptual Grounding: What Is a Tourism Digital Twin?
A tourism digital twin is best understood as an ecosystem of representations:
Physical layer: attractions, transport networks, utilities, ecosystems, cultural heritage assets.
Data layer: real-time and historical data from IoT sensors, ticketing, accommodation occupancy, mobility, payments, environmental monitors, and qualitative community inputs.
Modeling layer: simulations (agent-based, system dynamics), predictive analytics (demand forecasting, anomaly detection), and prescriptive tools (optimization of routes, staffing, energy).
Interface layer: dashboards for managers; alerts for operations; APIs for businesses; accessible information tools for visitors and residents.
Governance layer: rules on privacy, sharing, accountability, cybersecurity, and community co-creation.
The power of a digital twin lies not simply in mirroring the world but in testing futures: “What if this festival grows by 20%?” “What if heatwaves increase by 2°C?” “What if we pedestrianize a district in summer?” By running scenarios, destinations can compare trade-offs, reducing guesswork in strategic decisions.
3. Theoretical Foundations
3.1 Bourdieu’s Forms of Capital
Bourdieu’s framework helps explain the uneven gains that digital twins may create:
Economic capital: Revenues from optimized flows, reduced energy costs, and smoother operations. Destinations with the resources to build twins capture early mover advantages.
Cultural capital: Know-how in data analytics, urban planning, and heritage conservation. Skilled teams convert streams of numbers into meaningful policy.
Social capital: Networks among tourism boards, local businesses, community groups, and technologists. Collaboration determines whether insights become action.
Symbolic capital: The prestige of being a “smart, sustainable” destination. Symbolic capital can attract investors and visitors, creating a virtuous circle—but it can also mask uneven local benefits.
A key risk is the conversion of symbolic capital into economic capital without parallel social benefits, where branding outpaces genuine improvements for residents.
3.2 World-Systems Theory
World-systems theory maps how global structures create core–semi-periphery–periphery relations. Digital twins can either narrow or widen these divides:
Core destinations already possess capital and expertise, potentially deepening their lead through advanced modeling and marketing.
Semi-peripheral and peripheral regions may face vendor lock-in, skill shortages, and data extraction—becoming data providers rather than decision makers.
Equity-focused design and fair partnerships are therefore not optional; they are necessary for avoiding a digital dependency cycle.
3.3 Institutional Isomorphism
DiMaggio and Powell identify coercive, normative, and mimetic forces that push institutions to become similar:
Coercive: Funding and regulations may require “smart” solutions to access grants.
Normative: Professional communities promote standards and best practices.
Mimetic: Destinations copy what appears successful elsewhere, especially under uncertainty.
Isomorphism can accelerate diffusion but risks copy-paste implementations that ignore local culture, informal economies, and ecological contexts. The challenge is contextual isomorphism—learning from others while adapting with community input.
4. Method and Scope
This paper is a theory-led, practice-informed essay. It synthesizes current sector discourse with established academic literature in tourism, urban informatics, sustainability, and sociology. The goal is to offer actionable conceptual clarity and a roadmap for stakeholders this year, with language accessible to managers and policymakers.
5. Why the Trend Is Accelerating in 2025
Climate and resilience pressures: Heatwaves, storms, and water stress make scenario planning urgent.
Maturity of data infrastructure: Cheaper sensors, 5G, edge computing, and interoperable data standards lower barriers to real-time modeling.
AI-augmented analytics: Forecasting, anomaly detection, and prescriptive recommendations are improving, making twins more useful day to day.
Visitor expectations: Travelers want smoother mobility, accurate crowd information, and authentic, low-impact experiences.
Policy momentum: Performance-based sustainability targets and carbon management encourage digital tools that quantify impact.
Operational return on investment: Even modest gains in energy efficiency, staffing, or crowd control can justify initial investments when scaled.
6. Use Cases with Social and Technical Depth
6.1 Visitor Flow and Carrying Capacity
Agent-based models simulate how different visitor segments move through space and time. Combined with simple nudging (timed ticketing, route suggestions), destinations flatten peaks, protecting heritage fabric and improving satisfaction. The sociological dimension: whose mobility is prioritized? A just twin includes residents’ rhythms and does not reduce neighborhoods to “throughput corridors.”
6.2 Heritage Conservation and Authenticity
Micro-sensors track vibration, humidity, and footfall loads to protect fragile sites. Digital twins test protective measures before physical changes occur. Cultural capital is preserved not only as artifacts but as living practices—festivals, crafts, and oral histories—represented alongside 3D models. Community curatorship prevents a purely aesthetic twin that ignores intangible heritage.
6.3 Climate Adaptation and Heat Management
Simulating shade, albedo, wind corridors, and cooling centers helps destinations design heat-smart streetscapes. Models can prioritize tree planting where queues form, align operating hours with safe temperatures, and adjust transport schedules. Here, institutional isomorphism is risky: designs copied from cooler climates may fail. Local calibration is essential.
6.4 Inclusive Mobility and Accessibility
Twins can map curb cuts, elevator reliability, slope gradients, resting spots, and quiet routes for neurodiverse travelers. This moves accessibility from compliance to design intelligence, converting social capital (knowledge of lived experience) into symbolic capital (reputation for inclusion) and, ultimately, economic capital (wider markets).
6.5 Small Business Resilience
APIs from the twin can share privacy-preserving forecasts for foot traffic, enabling micro-enterprises to plan staffing and inventory. This spreads benefits beyond large firms, turning data into distributed economic capital rather than a centralized asset.
6.6 Risk and Emergency Preparedness
Scenario playbooks for floods, fires, or transport failures can be rehearsed virtually. During events, common operating pictures align responders, operators, and community channels. The ethical question is not whether to act, but who decides when and how to restrict movement; transparent protocols and public oversight build legitimacy.
7. Architecture: From Data to Decisions
Sensing: Mobility counters, environmental monitors, energy meters, ticketing systems, qualitative inputs (community reporting, surveys).
Data governance: Minimization, anonymization, role-based access, audit trails, and community-approved data charters.
Modeling:
Descriptive (maps, dashboards)
Predictive (short-term demand, weather-impact forecasts)
Prescriptive (optimization: routing, staffing, pricing windows)
Decision loop: Alerts → human review → action → feedback to model.
Interfaces: Manager dashboards (policy levers, KPIs), business portals (forecasts), citizen apps (rights-respecting), and open data sandboxes for research.
Cybersecurity: Network segmentation, encryption, red-team testing, and resilience drills.
A crucial design principle is human-in-the-loop oversight where the system recommends but humans decide, especially for value-laden choices.
8. Value and Impact Through a Capital Lens
8.1 Economic Capital
Reduced energy and logistics costs through optimized schedules.
Revenue stabilization by spreading demand across time and space.
New products (timed experiences, dynamic routes).
Workforce planning that reduces overtime and burnout.
Risk: If vendors capture disproportionate value via proprietary lock-ins, destinations may pay ongoing rents that outstrip benefits. Contracting should include data portability and exit options.
8.2 Social Capital
Trust grows when communities see their concerns reflected in models and outcomes.
Collaborative data commons (with privacy guards) allow universities, startups, and NGOs to co-create tools.
Participatory scenario workshops cultivate shared problem ownership.
Risk: If the twin becomes a black box, community trust falls. Explanations and co-design are non-negotiable.
8.3 Cultural Capital
Skilled teams who interpret models and mediate trade-offs are a strategic asset.
Heritage interpretation improves when curators, guides, and residents co-author the virtual layer.
Risk: Over-reliance on external consultants can drain local capabilities. Apprenticeships and scholarships build lasting cultural capital.
8.4 Symbolic Capital
Recognition as a smart, responsible destination attracts investors and visitors.
Communication must avoid techno-fetishism; symbolic capital should match real outcomes, verified by public metrics.
9. Ethics, Justice, and Governance
Privacy and dignity: Use aggregation, differential privacy, and clear retention limits. Avoid hyper-granular tracking that chills public life.
Bias and representativeness: Complement sensor data with community knowledge to include informal economies and marginalized groups.
Algorithmic accountability: Publish model assumptions, uncertainty ranges, and error rates. Enable independent audits.
Power asymmetries: Guard against core–periphery extraction by requiring local data stewardship, shared IP options, and joint decision councils.
Environmental duty: Treat the twin as a tool for carbon reduction, with explicit emissions budgets guiding operations.
10. Implementation Roadmap (12–36 Months)
Phase 1: Co-design and Governance (Months 1–6)
Map stakeholders; create a data charter with community consent practices.
Define high-value pilot corridors (old town, waterfront, festival zone).
Inventory existing data sources and gaps; plan privacy-by-design.
Phase 2: Minimum Viable Twin (Months 6–12)
Integrate a small set of sensors and operational feeds.
Deliver two or three clear wins (e.g., queue reduction at a landmark; heat-aware routing).
Begin capacity building: analyst training, data literacy sessions for managers and SMEs.
Phase 3: Scale and Integrate (Months 12–24)
Extend to transport, utilities, and environmental monitoring.
Introduce predictive models for demand and energy.
Establish business APIs with privacy limits to democratize benefits.
Phase 4: Institutionalization (Months 24–36)
Embed the twin in annual budgeting and policy cycles.
Formalize auditing, cyber drills, and independent oversight.
Publish outcome dashboards co-owned with the community.
11. Measurement: From Outputs to Outcomes
Operational KPIs
Average queue times, on-time performance of shuttles, energy per visitor, water usage per day, emergency response times.
Sustainability KPIs
Carbon intensity per visitor-day, percentage of visits shifted to off-peak windows, microclimate cooling effects, heritage risk scores.
Equity KPIs
Accessibility coverage, share of SME API users, resident satisfaction, distribution of benefits across neighborhoods.
Governance KPIs
Data access requests met, audit completion rates, number of public co-design sessions, model transparency score.
12. Discussion: Power, Inequality, and the Risk of Copy-Paste
Digital twins do not float above society; they reconfigure it. World-systems theory reminds us that technology can consolidate core power. A destination with strong economic and cultural capital can compound advantages by learning faster and signaling modernity. Peripheral regions risk becoming data raw-material exporters, with value captured elsewhere. Institutional isomorphism adds that under uncertainty, organizations copy what looks legitimate. The result may be a homogenized smartness that ignores local craft, street vendors, informal festivals, and family economies that animate tourism.
A more hopeful path is reflexive isomorphism: adopt standards for safety, privacy, and interoperability, yet hybridize models with local cultural knowledge. Bourdieu’s symbolic capital must be earned through measurable improvements for residents and ecosystems, not just glossy dashboards.
13. Practical Safeguards for Fair and Context-Aware Twins
Local capability first: Budget at least 20–30% for training and apprenticeships so skills remain in the destination.
Open interfaces, portable data: Prevent lock-in; require documented schemas and export paths.
Community seats at the table: Establish a permanent advisory council of residents, SMEs, youth, and accessibility advocates.
Proportional data use: Collect only what is necessary; favor aggregated indicators over individual traces.
Ethical impact assessment: Before each major feature, evaluate privacy risk, distributional impact, and environmental footprint.
Transparent narratives: Publish model purposes, assumptions, and evaluation results in clear language.
14. Business Model Options and Shared Value
Public core, private innovation: Keep governance and common data models public while inviting private services on top under fair rules.
Outcome-based contracting: Tie vendor compensation partly to verified improvements (e.g., energy reduction targets), not only software delivery.
SME enablement: Provide free or low-cost forecast feeds for small operators, creating inclusive growth.
This approach aligns economic capital with social and symbolic capital, reducing tensions among stakeholders.
15. From Pilots to Policy: Embedding the Twin
A twin becomes meaningful when policy learns from it. Examples include:
Adaptive permits: Stall numbers or event sizes adjust with heat or congestion forecasts.
Time-of-day tariffs: Discounted entries for off-peak visits; dynamic parking or shuttle pricing aligned with emissions budgets.
Design codes: Shading, materials, and pedestrianization mandated where simulations show strong benefits.
Education pipelines: Partnerships that turn high-school and vocational projects into data literacy and sensor maintenance skills.
Such policies convert model insights into lasting institutional change—the hallmark of maturity.
16. Future Research Directions (2025–2030)
Mixed-methods evaluation: Combine sensor metrics with ethnography to capture lived experience and avoid “dashboard bias.”
Climate-twin integration: Deeper coupling with hydrology, heat, and biodiversity models to guide nature-based solutions.
Fair data markets: Mechanisms for communities and SMEs to co-benefit from data value without surveillance.
Crisis commons: Shared simulation libraries for small destinations that cannot afford bespoke builds.
Cultural analytics: Tools that model not only flows but meanings—rituals, narratives, and place attachment—so authenticity is designed in, not out.
17. Conclusion
Digital twins are becoming a mainstream governance technology in tourism in 2025. Properly designed, they lower environmental impact, improve visitor experiences, strengthen small businesses, and build resilience. But their real promise lies in how they restructure relationships: between data and decision, expert and resident, core and periphery. Using Bourdieu’s capital lens clarifies how benefits can be monopolized or shared; world-systems theory warns against reproducing dependency; institutional isomorphism cautions against uncritical imitation. The way forward is pragmatic and principled: local capability, ethical governance, transparent modeling, and inclusive participation. In that frame, digital twins become not just a technology, but a civic instrument—a way to align prosperity with stewardship, and to translate the best of tourism’s ideals into everyday practice.
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References / Sources
Batty, M. (2018). Inventing Future Cities.
Bohannon, J. & Gretzel, U. (eds.) (2021). Smart Tourism: Foundations and Developments.
Bourdieu, P. (1986). “The Forms of Capital.” In Handbook of Theory and Research for the Sociology of Education.
DiMaggio, P. & Powell, W. (1983). “The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality.” American Sociological Review.
Floridi, L. (2013). The Ethics of Information.
Goffman, E. (1974). Frame Analysis.
Grieves, M. (2019). Virtually Perfect: Driving Innovative and Lean Products through Product Lifecycle Management and Digital Twins.
Gretzel, U., Sigala, M., Xiang, Z., & Koo, C. (2015). “Smart Tourism: Foundations and Developments.” Electronic Markets.
Kitchin, R. (2014). The Data Revolution.
McPhee, W. & Ziman, J. (2020). Data-Driven City Management.
Ostrom, E. (1990). Governing the Commons.
Porter, M. (1998). Clusters and the New Economics of Competition.
Sheller, M. & Urry, J. (2006). “The New Mobilities Paradigm.” Environment and Planning A.
Urry, J. (2007). Mobilities.
Wallerstein, I. (1974). The Modern World-System.
Zuboff, S. (2019). The Age of Surveillance Capitalism.
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