Digital Twin Cities And Simulation-Based Governance Control

1. Introduction

Digital Twin Cities are computational replicas of physical cities that combine geographic information, sensor networks, Internet-of-Things devices, transport data, utility information, building models, environmental data, and artificial intelligence to simulate how a city operates. Governments can use these systems to model traffic, housing, energy demand, pollution, emergency response, infrastructure investment, and land-use changes before implementing policies in the physical world.

Simulation-based governance control goes further. It occurs when governmental authorities rely on digital-twin simulations, predictive models, automated decision systems, or algorithmic scenarios to determine or substantially influence public decisions.

The central legal and competition-law concern is that a digital twin can become more than a planning tool. If one private platform controls the underlying data, modelling infrastructure, APIs, cloud computing, simulation software, or decision-making interface, it may acquire infrastructural and informational power over urban governance.

This creates issues involving:

• monopoly over urban data;
• control of essential digital infrastructure;
• exclusion of competing technology providers;
• algorithmic discrimination;
• transparency and explainability;
• administrative-law legality;
• privacy and surveillance;
• procurement dependence;
• interoperability and data portability;
• public-sector vendor lock-in;
• manipulation of simulations;
• and concentration of decision-making power.

2. Meaning of a Digital Twin City

A digital twin city is a continuously updated digital representation of a physical city.

It may integrate:

1. Geospatial information
   • maps;
   • cadastral information;
   • zoning;
   • building models.
2. Real-time sensor information
   • traffic sensors;
   • cameras;
   • environmental monitors;
   • smart meters;
   • public transport systems.
3. Infrastructure information
   • roads;
   • bridges;
   • water systems;
   • electricity grids;
   • telecommunications networks.
4. Population and mobility information
   • commuting patterns;
   • public transport use;
   • pedestrian flows;
   • vehicle movements.
5. Simulation models
   • traffic simulations;
   • flood modelling;
   • energy models;
   • emergency scenarios;
   • climate projections.
6. AI and predictive analytics

The digital twin therefore becomes an information infrastructure for governmental decision-making.

3. From Digital Twin to Governance Control

The important distinction is between:

Digital twin as analytical infrastructure

and

Digital twin as governance infrastructure.

A city may initially use a digital twin merely to test whether a proposed road will increase congestion.

But gradually, the system may begin determining:

• which roads should receive investment;
• where housing should be permitted;
• which neighbourhoods receive public services;
• where police resources should be deployed;
• which buildings require inspection;
• how electricity should be allocated;
• where congestion charges should apply;
• which infrastructure projects receive priority.

The simulation therefore becomes part of the decision-making chain.

4. Simulation-Based Governance Control

Simulation-based governance can operate through a five-stage process:

Stage 1 — Data collection

The system collects enormous quantities of urban information.

Stage 2 — Digital representation

The information is incorporated into the digital twin.

Stage 3 — Scenario generation

The system generates hypothetical scenarios.

For example:

"What happens if this highway lane is removed?"

Stage 4 — Policy optimisation

The system compares alternative scenarios and recommends the apparently optimal policy.

Stage 5 — Administrative implementation

Government authorities use the recommendation to make actual decisions.

The legal problem is that the apparently neutral simulation may embed assumptions concerning:

• economic value;
• acceptable risk;
• environmental priorities;
• mobility;
• public safety;
• housing;
• equality;
• and distribution of public resources.

Consequently, technical modelling can become a form of policy-making.

5. Competition-Law Dimension

Digital twins can generate substantial market power because they combine several network effects.

A. Data network effects

More data produces better simulations.

Better simulations attract more government users.

More users generate more data.

This produces a reinforcing cycle.

B. Switching costs

Once a city builds its infrastructure around one digital-twin provider, changing suppliers can become extremely expensive.

The city may have to migrate:

• datasets;
• APIs;
• models;
• digital building representations;
• sensor integrations;
• historical records;
• simulation parameters.

C. Interoperability barriers

A dominant provider may control technical standards or interfaces necessary for competitors to connect.

D. Economies of scale

Developing a sophisticated digital twin requires:

• cloud infrastructure;
• AI;
• geospatial databases;
• simulation expertise;
• cybersecurity;
• sensor integration.

These costs can create significant barriers to entry.

E. Ecosystem foreclosure

A dominant platform may extend its power from:

cloud → data → simulation → analytics → public procurement → governance.

This can transform a digital-twin supplier into a quasi-infrastructural gatekeeper.

6. Digital Twin as an Essential Facility

A particularly important competition-law question is whether certain components of a digital twin constitute an essential facility.

Potentially indispensable resources could include:

• unique municipal datasets;
• real-time traffic data;
• citywide sensor infrastructure;
• digital cadastral information;
• interoperability interfaces;
• public infrastructure APIs;
• high-resolution urban models.

If competitors cannot realistically reproduce these resources, denial of access could exclude rival suppliers.

However, essential-facility doctrine generally requires more than mere usefulness. The resource must be sufficiently indispensable and the refusal sufficiently capable of eliminating effective competition.

7. Six Major Case Laws

1. Oscar Bronner GmbH & Co. KG v Mediaprint

The European Court of Justice developed a strict approach to refusal-to-deal claims involving potentially indispensable infrastructure.

The Court emphasised that access is not automatically required simply because another undertaking would benefit from it.

Relevance to digital twins

A dominant digital-twin operator could argue that its proprietary:

• simulation platform;
• cloud architecture;
• urban data;
• APIs;

is merely a commercial product.

A competitor seeking access would have to establish genuine indispensability.

Principle

Digital infrastructure does not automatically become an essential facility merely because competitors find access commercially advantageous.

2. IMS Health GmbH & Co. KG v NDC Health

The IMS Health litigation is particularly relevant to digital governance because it involved control over a highly structured information system.

The Court recognised circumstances in which refusal to license an indispensable information structure could amount to abusive conduct.

Relevance

A digital-twin provider might possess a unique:

city-data architecture + modelling structure + interoperability framework.

If competing providers cannot realistically operate without access to it, the case provides an important conceptual framework for analysing compulsory access.

Principle

Intellectual-property protection cannot necessarily be used as an absolute shield against competition-law intervention where exceptional conditions are satisfied.

3. Microsoft Corp. v Commission

The European Commission's Microsoft case concerned interoperability information and Microsoft's control over an important technological ecosystem.

The case demonstrated how control over interoperability can allow a dominant undertaking to extend market power into neighbouring markets.

Digital-twin relevance

Suppose a dominant digital-twin company controls:

• municipal APIs;
• simulation protocols;
• data formats;
• software interfaces.

It could potentially prevent competing traffic, energy, or environmental applications from integrating with the city platform.

Principle

Interoperability can become a competition parameter where control over interfaces allows a dominant firm to protect or extend market power.

4. Google Shopping

The Google Shopping litigation concerned the treatment of Google's own comparison-shopping service within its general search results.

The case illustrates how a platform can use control over an important gateway to favour its own downstream service.

Digital-twin relevance

A city digital-twin platform could operate simultaneously as:

1. infrastructure provider;
2. data intermediary;
3. analytics provider;
4. application marketplace;
5. governance recommendation platform.

If the operator systematically favours its own:

• transport optimisation service;
• energy-management system;
• urban-planning application;

over competing services, self-preferencing concerns may arise.

Principle

A dominant platform's control over an important gateway can create competition concerns when that control is used to advantage its own downstream activities.

5. Bronner / Magill / IMS Health Line of Cases and Intellectual-Property Access

The Magill litigation is also important because it established an exceptional framework for compulsory access to protected information.

The issue was whether refusal to supply information could, in exceptional circumstances, constitute abuse.

Digital-twin relevance

Consider a company holding a proprietary urban-data layer that is indispensable to competing city-management applications.

The legal question becomes:

Is the data merely valuable, or is it genuinely indispensable?

That distinction is critical.

Principle

Competition law may intervene in exceptional circumstances where control over information or intellectual property becomes a means of eliminating effective competition.

6. Slovak Telekom v European Commission

The Court of Justice examined exclusionary conduct involving telecommunications infrastructure and access conditions.

The case is particularly useful for understanding situations where a dominant infrastructure operator controls access to a downstream market.

Digital-twin relevance

A digital-twin platform could similarly control the infrastructure through which third-party applications access:

• sensor data;
• geospatial information;
• municipal APIs;
• mobility information;
• simulation outputs.

If access conditions are structured to disadvantage competing applications, competition authorities may examine the conduct as exclusionary.

Principle

Control over infrastructure can create downstream competitive leverage where access arrangements disadvantage rivals.

7. Bronner-Type Infrastructure Analysis in Digital Cities

The cases collectively demonstrate an important distinction.

Not every municipal dataset is an essential facility.

The relevant questions include:

Indispensability

Can competitors reasonably reproduce the resource?

Replicability

Can another firm construct an equivalent dataset?

Technical feasibility

Can alternative systems integrate with the infrastructure?

Economic feasibility

Would duplication be economically realistic?

Elimination of competition

Would denial of access substantially eliminate effective competition?

Objective justification

Does the dominant operator have legitimate reasons for restricting access?

8. Administrative-Law Problem

Competition law is only one dimension.

Digital-twin governance also raises fundamental administrative-law questions.

A governmental decision may be unlawful if an authority effectively delegates discretionary decision-making to a private algorithm without adequate legal authority.

For example:

A city authority adopts a housing policy solely because the digital twin predicts that a particular neighbourhood generates the highest economic return.

The question becomes:

Who actually made the decision—the public authority or the algorithmic system?

9. Delegation of Public Power

Government agencies ordinarily cannot escape statutory duties merely by outsourcing technical functions.

A digital-twin supplier may provide:

• technical calculations;
• predictive models;
• simulations.

But the ultimate governmental decision should remain attributable to the legally authorised public authority.

This creates a distinction between:

Technical delegation

"Calculate expected traffic."

and

Normative delegation

"Decide which neighbourhood should lose road capacity."

The second is considerably more constitutionally sensitive.

10. Algorithmic Opacity

Digital twins can become difficult to scrutinise because their outputs may depend upon thousands of variables.

A simulation might recommend:

"Option B is optimal."

But officials may not know:

• which assumptions generated the result;
• which datasets were weighted;
• which populations were affected;
• whether alternative scenarios were excluded;
• whether the model contains historical bias.

This creates a black-box governance problem.

11. Right to Reasons

Where a simulation materially influences an administrative decision, affected persons may argue that they require sufficient information to understand:

• the decisive factors;
• the assumptions;
• the evidence;
• the methodology;
• the uncertainty.

This is particularly important where decisions affect:

• property;
• mobility;
• planning permission;
• taxation;
• public benefits;
• policing;
• environmental regulation.

12. Privacy and Surveillance

A digital twin may combine:

• CCTV;
• GPS;
• mobile-device data;
• public transport information;
• smart-meter information;
• vehicle information;
• building occupancy data.

The combination creates risks that are greater than those associated with each dataset separately.

The digital twin therefore creates a potential urban surveillance architecture.

A key principle should be:

Data collected for city management should not automatically become unrestricted data for behavioural monitoring.

13. Data Concentration

Digital twins can produce a new type of market power:

"Urban informational dominance."

A firm may control:

data + infrastructure + models + cloud + analytics + interface.

This is more powerful than ordinary market share because competitors may depend upon the dominant system to understand the market itself.

The provider therefore potentially becomes both:

market participant and market-information gatekeeper.

14. Simulation Manipulation

Another major concern is model manipulation.

A dominant provider might configure assumptions in a manner that favours its own infrastructure.

For example:

• its transport technology receives favourable assumptions;
• competitors' infrastructure is modelled pessimistically;
• alternative suppliers are assigned higher implementation costs;
• environmental benefits are calculated differently across technologies.

This creates a subtle form of exclusion.

The conduct may not involve an explicit refusal to deal.

Instead:

the model itself becomes the mechanism of competitive discrimination.

15. Algorithmic Self-Preferencing

Imagine a company operates:

1. the city digital twin;
2. an electric-vehicle charging network;
3. a traffic-management system.

The digital twin recommends expansion of the company's own charging network.

The recommendation may appear objective.

However, competition authorities should investigate:

• training data;
• assumptions;
• weighting;
• optimisation functions;
• conflicts of interest;
• treatment of competing infrastructure.

Thus, algorithmic neutrality cannot simply be presumed.

16. Public Procurement Concerns

Digital-twin projects frequently involve long-term procurement.

A city may become dependent upon one vendor.

The contract may then contain:

• proprietary formats;
• restricted APIs;
• expensive data extraction;
• high switching fees;
• exclusive maintenance arrangements.

This can create procurement-induced market foreclosure.

Competition policy should therefore consider the entire lifecycle of procurement rather than only the initial tender.

17. Data Portability and Interoperability

A competition-friendly digital twin should ideally support:

• open APIs;
• standardised data formats;
• export rights;
• interoperability;
• modular architecture;
• supplier switching;
• third-party applications.

Otherwise, a city may experience:

digital lock-in → reduced competition → higher prices → reduced innovation.

18. Systemic Risk

Digital-twin monopolisation can create systemic risk.

If one company controls digital twins for multiple cities, an outage could simultaneously affect:

• traffic management;
• emergency planning;
• utilities;
• public transport;
• environmental monitoring.

Cyberattacks could have cascading consequences.

The issue therefore moves beyond conventional competition law into critical infrastructure regulation.

19. The "Governance Stack" Problem

Digital cities can be understood as a stack:

Physical infrastructure

↓

Sensors

↓

Data layer

↓

Cloud infrastructure

↓

Digital twin

↓

Simulation engine

↓

AI optimisation

↓

Government decision

↓

Physical intervention

Control at an upper layer can influence every layer below it.

This creates a potentially powerful form of vertical technological control over government infrastructure.

20. Competition Risks by Layer

21. Remedies

Competition authorities and governments could consider several remedies.

Structural remedies

In extreme cases:

• separation of data and commercial services;
• separation of infrastructure and downstream applications.

Behavioural remedies

Require:

• non-discriminatory access;
• transparent APIs;
• interoperability;
• data portability;
• non-self-preferencing;
• auditability.

Governance remedies

Require:

• human oversight;
• explanation of material decisions;
• independent model audits;
• impact assessments;
• record keeping.

Procurement remedies

Contracts should include:

• exit clauses;
• data-export obligations;
• interoperability requirements;
• portability;
• technical documentation;
• transition assistance.

22. Regulatory Principle

The central regulatory principle should be:

A digital twin may assist government decision-making, but it should not become an unaccountable substitute for government decision-making.

Similarly:

Control over the digital infrastructure of a city should not automatically confer control over the competitive markets operating through that infrastructure.

23. Overall Legal Test

A comprehensive legal analysis can therefore ask:

1. Market definition

What is the relevant market?

2. Dominance

Does the digital-twin operator possess substantial market power?

3. Infrastructure dependence

Do competitors depend upon the platform?

4. Data indispensability

Is the underlying data realistically replicable?

5. Interoperability

Can rival systems connect?

6. Exclusion

Does the operator disadvantage competing providers?

7. Self-preferencing

Does it favour its own applications?

8. Algorithmic neutrality

Are simulation assumptions neutral?

9. Administrative legality

Does the government retain genuine decision-making authority?

10. Fundamental rights

Are privacy, equality, property and due-process interests protected?

11. Systemic risk

Would failure of the platform disrupt essential urban services?

12. Remedies

Can competition and technological neutrality be restored without destroying legitimate efficiencies?

24. Conclusion

Digital Twin Cities and Simulation-Based Governance Control represent a new intersection of competition law, administrative law, data governance, public procurement and critical-infrastructure regulation.

The principal danger is not simply that a company may become a monopoly supplier of software. The more significant danger is that the company may control the informational and computational infrastructure through which government understands and manages the city.

The cases concerning Bronner, Magill, IMS Health, Microsoft, Google Shopping and Slovak Telekom provide useful legal foundations for analysing indispensability, interoperability, information access, infrastructure control and exclusionary conduct.

The emerging legal question can therefore be expressed as:

When a private digital platform becomes indispensable to a government's ability to model, predict and manage urban reality, should that platform continue to be treated merely as an ordinary commercial supplier, or should it be regulated as a form of critical governance infrastructure?