Global Supply Chain Digital Twins and Systemic Control Risks

Introduction

Supply-chain digital twins are digital representations of physical supply networks that continuously model, simulate, predict, and sometimes optimize the behaviour of factories, warehouses, ports, logistics networks, suppliers, inventories, transport routes, and customers. They combine data from IoT sensors, enterprise-resource-planning systems, cloud platforms, GPS, logistics platforms, artificial intelligence, and external market information.

From a competition-law perspective, the important issue is that a digital twin can evolve from a decision-support technology into an infrastructure layer controlling economically significant supply-chain decisions. If one platform becomes the common digital environment through which competitors forecast demand, allocate inventory, select suppliers, determine logistics routes, evaluate risks, or optimize prices, the platform operator may acquire substantial systemic control over market conditions.

The principal competition concerns include:

1. concentration of supply-chain data;
2. exclusionary control over interoperability;
3. algorithmic coordination between competitors;
4. discriminatory access to logistics or supplier information;
5. self-preferencing;
6. tying and leveraging across adjacent markets;
7. denial of access to essential digital infrastructure;
8. discriminatory algorithmic optimization;
9. acquisition of emerging digital-twin competitors; and
10. systemic dependency on a small number of cloud/data-platform providers.

1. Meaning and Structure of a Supply-Chain Digital Twin

A digital twin may reproduce several interconnected layers:

A. Physical layer

This includes:

• factories;
• warehouses;
• ports;
• trucks;
• ships;
• aircraft;
• distribution centres;
• energy infrastructure;
• inventories; and
• production equipment.

B. Data layer

The twin may continuously ingest:

• inventory levels;
• production capacity;
• delivery times;
• supplier performance;
• demand forecasts;
• transportation costs;
• customer orders;
• GPS information;
• machine performance;
• weather information; and
• commodity prices.

C. Algorithmic layer

AI models may then determine:

• which supplier should be used;
• how much should be produced;
• which warehouse should receive goods;
• which transportation route should be selected;
• when inventory should be replenished;
• how scarce capacity should be allocated; and
• how prices should respond to changing market conditions.

D. Governance layer

The most important competition-law question arises when the platform also determines who can access the data, algorithms, interfaces and decision-making infrastructure.

The digital twin therefore potentially becomes more than software. It can become a market-governance infrastructure.

2. Why Digital Twins Create Systemic Competition Risks

Traditional supply chains generally involve numerous independent decisions.

A digital twin can centralize those decisions.

For example:

Suppliers → Data Platform → Digital Twin → AI Optimization → Logistics Allocation → Buyers

If competing companies use the same digital twin, the platform can potentially observe a large proportion of the market simultaneously.

This creates a fundamental competition-law tension:

The same technology that increases efficiency can also increase the ability of market participants to coordinate or exclude rivals.

The issue becomes particularly serious when the platform possesses:

• unique real-time data;
• network effects;
• high switching costs;
• proprietary APIs;
• predictive models;
• control over interoperability;
• exclusive access to logistics data; or
• integration with physical infrastructure.

3. Market Definition

Several relevant markets may exist simultaneously.

A. Digital-twin software market

Competition may occur between:

• digital-twin providers;
• industrial software companies;
• cloud providers; and
• specialized supply-chain platforms.

B. Supply-chain data market

A separate market may arise around access to:

• real-time logistics information;
• inventory information;
• supplier-performance data;
• production information; and
• demand forecasts.

C. Cloud and compute infrastructure

Digital twins can depend heavily upon:

• cloud computing;
• GPU/AI infrastructure;
• data storage;
• networking;
• cybersecurity services.

D. Downstream physical markets

The digital twin may also affect:

• shipping;
• logistics;
• manufacturing;
• retail;
• energy;
• automotive supply chains;
• pharmaceuticals; and
• agricultural distribution.

Consequently, competition authorities may need to examine ecosystem power rather than only software-market shares.

4. Data Concentration and Competitive Advantage

The strongest digital-twin provider may accumulate information from numerous participants.

Suppose 50 manufacturers provide the same platform with:

• production forecasts;
• costs;
• capacity;
• inventory;
• supplier information; and
• anticipated demand.

The platform may obtain a much more comprehensive picture of the industry than any individual participant.

This creates a potential data feedback loop:

More participants → more data → better predictions → better optimization → greater attractiveness → more participants → still more data

Such feedback can create substantial barriers to entry.

The competition concern is not simply possession of data. It is the possibility that the provider can use aggregated data to reinforce market power or disadvantage competitors.

5. Algorithmic Coordination

One of the most important systemic risks concerns coordination.

If competing companies allow a common digital twin to optimize their decisions, the system could potentially produce parallel or coordinated outcomes without a conventional human agreement.

For example, a platform might optimize:

• freight capacity;
• inventory;
• delivery schedules;
• production;
• prices; or
• purchasing.

If competitors provide sensitive information to a common algorithm, the system may reduce strategic uncertainty between them.

Competition law therefore has to distinguish between:

legitimate independent optimization

and

technology-enabled coordination that replaces competitive decision-making.

6. Information Exchange

Digital twins create unprecedented possibilities for information exchange.

Sensitive information can include:

• future capacity;
• planned production;
• inventory;
• costs;
• transportation rates;
• expected demand;
• supplier negotiations; and
• strategic investment.

The danger increases when competitors receive sufficiently detailed or current information about one another.

The traditional competition-law concern over information exchange therefore acquires a technological dimension:

A digital twin may become an automated information-exchange mechanism between competitors.

The absence of a traditional meeting or telephone call does not necessarily eliminate competition concerns.

7. Exclusionary Access Restrictions

A dominant digital-twin provider may control access through:

• APIs;
• licensing terms;
• authentication systems;
• technical standards;
• data formats;
• certification requirements;
• interoperability restrictions; and
• switching costs.

It could potentially make it difficult for rival platforms to access the information required to compete.

For example, a dominant platform might permit its own logistics subsidiary to access real-time supply-chain information while delaying or limiting access for independent competitors.

This could constitute a form of digital foreclosure.

8. Self-Preferencing

A platform operating a digital twin could simultaneously provide infrastructure and compete downstream.

For example:

Digital-twin platform + logistics business

or

Digital-twin platform + warehousing business

The platform might theoretically optimize its system in a manner that favours its affiliated business.

Possible mechanisms include:

• preferential routing;
• earlier access to capacity;
• better demand forecasts;
• preferential supplier recommendations;
• superior API functionality; or
• preferential placement in optimization results.

This is particularly problematic where customers cannot easily switch platforms.

9. Tying and Bundling

A powerful digital-twin provider might require customers to purchase related services.

For example:

Access to the supply-chain digital twin is available only if the customer purchases the provider's cloud, logistics, cybersecurity or analytics services.

This may raise tying or bundling concerns when the provider possesses substantial market power.

The issue becomes stronger where the digital twin functions as an essential technological gateway.

10. Essential-Facility-Type Concerns

A digital twin could potentially become infrastructure that rivals cannot reasonably replicate.

Relevant factors include:

1. uniqueness of the data;
2. technical complexity;
3. replication costs;
4. network effects;
5. interoperability;
6. switching costs;
7. duration of access restrictions; and
8. competitive importance of the platform.

However, merely describing a platform as an "essential facility" does not automatically establish a legal obligation to provide access.

Competition authorities normally need to establish the applicable legal test for refusal of access.

11. Interoperability as a Competition Remedy

Where digital-twin dominance creates foreclosure risks, authorities may consider:

• API access;
• data portability;
• interoperability obligations;
• non-discriminatory access;
• standardized data formats;
• separation of infrastructure and downstream operations; and
• restrictions on data use.

Interoperability can be particularly important because a digital twin may otherwise become a technological bottleneck.

12. Vertical Foreclosure

Digital twins connect multiple levels of a supply chain.

A single platform might connect:

raw materials → manufacturers → warehouses → transport → wholesalers → retailers

If the platform owner operates at multiple levels, it may have the ability and incentive to disadvantage independent businesses.

For example, the platform could provide its affiliated manufacturer with superior forecasts while rivals receive less accurate or delayed information.

This is a classic vertical-foreclosure problem translated into digital infrastructure.

13. Conglomerate Power

Digital twins can facilitate expansion into neighbouring markets.

A provider may begin with:

industrial simulation

and subsequently expand into:

• cloud computing;
• procurement;
• logistics;
• insurance;
• financing;
• cybersecurity;
• marketplace services; and
• autonomous supply-chain management.

The accumulated data can facilitate expansion across these markets.

Thus, the relevant question may be:

Is the company merely successful in digital-twin software, or is it becoming a vertically and horizontally integrated supply-chain gatekeeper?

14. Mergers and Acquisitions

Acquisitions can create substantial competition concerns.

A large logistics platform might acquire:

• a digital-twin developer;
• an industrial-IoT company;
• a predictive analytics provider;
• a supply-chain marketplace; or
• a specialized data company.

Even where the target has relatively low current revenue, its data and technology may have considerable future competitive significance.

Competition authorities may therefore examine:

• innovation competition;
• data accumulation;
• interoperability;
• nascent competition;
• vertical integration; and
• ecosystem foreclosure.

15. Six Important Case Laws

The following cases provide useful legal foundations for analysing digital-twin systemic-control problems, even though most predate modern supply-chain digital-twin technology.

1. United States v. Terminal Railroad Association, 224 U.S. 383 (1912)

The U.S. Supreme Court considered control over an important transportation gateway.

The terminal facilities were controlled by an association that could affect competitors' access to essential transportation infrastructure.

Relevance to digital twins

The case provides an early illustration of how control over infrastructure can produce competitive power.

A modern digital twin controlling access to critical logistics information or infrastructure could raise analogous questions where the platform becomes an unavoidable gateway for competitors.

Principle

Control over strategically indispensable infrastructure can create competition concerns when access is used to exclude competitors.

16. 2. United States v. AT&T, 524 F. Supp. 1336 (D.D.C. 1981)

The AT&T litigation involved telecommunications infrastructure and vertical integration.

The concern was that control over essential telecommunications facilities could be leveraged to disadvantage competing providers.

Relevance

Digital supply chains similarly involve multiple layers:

data infrastructure → platform → downstream services

A dominant digital-twin provider controlling infrastructure and competing downstream may create incentives for discriminatory treatment.

Principle

Vertical integration involving an important infrastructure layer can raise serious foreclosure concerns when infrastructure control affects downstream competition.

17. 3. Bronner v. Mediaprint, C-7/97

The Court of Justice of the European Union examined refusal of access to a newspaper distribution system.

The Court established a demanding framework for imposing compulsory access under the essential-facilities doctrine.

Relevance to digital twins

A digital twin may become difficult for competitors to reproduce because of:

• accumulated data;
• network effects;
• complex integrations;
• proprietary infrastructure; and
• historical information.

Bronner demonstrates that importance alone is insufficient.

A competition authority must carefully establish the legal conditions for compulsory access.

Principle

Dominance does not automatically create a general duty to share infrastructure or assets with competitors.

18. 4. IMS Health GmbH & Co. OHG v NDC Health GmbH, C-418/01

IMS Health concerned access to a data structure used in the pharmaceutical sector.

The case is particularly relevant because the disputed infrastructure was fundamentally information-based.

The CJEU identified stringent conditions for compelling access to intellectual-property-related infrastructure.

Relevance to digital twins

Supply-chain digital twins may depend upon proprietary:

• data structures;
• interoperability formats;
• software architectures;
• databases; and
• interfaces.

IMS Health therefore illustrates the tension between property rights and competition-law access obligations.

Principle

Competition law can, in exceptional circumstances, require access to protected infrastructure, but the conditions are stringent.

19. 5. Microsoft Corp. v Commission, T-201/04

The European Commission's Microsoft case concerned interoperability information and Microsoft's position in software markets.

The General Court upheld significant aspects of the Commission's intervention.

Relevance

Interoperability is central to digital twins.

A dominant digital-twin platform might attempt to prevent rival systems from interacting effectively with:

• industrial equipment;
• supplier databases;
• logistics systems;
• ERP platforms; or
• competing AI tools.

The Microsoft litigation demonstrates that interoperability restrictions can have competition significance when controlled by a dominant undertaking.

Principle

Technical interoperability can become a competition-law issue where control over interoperability reinforces dominance and restricts effective competition.

20. 6. Google Shopping, Case T-612/17

The European Union litigation concerning Google's comparison-shopping service addressed the use of dominance in one digital market to favour the undertaking's own downstream service.

The case is highly relevant to digital ecosystems.

Relevance to digital twins

Imagine a company operating:

Supply-chain digital twin + logistics marketplace

If its algorithm systematically gives preferential treatment to its own logistics operation, the conduct could resemble self-preferencing concerns.

Possible mechanisms include:

• ranking manipulation;
• preferential optimization;
• privileged data;
• superior API access; and
• discriminatory visibility.

Principle

A dominant digital platform can face competition-law scrutiny where its conduct advantages its own downstream service and disadvantages competing services.

21. 7. Slovak Telekom v Commission, Joined Cases C-152/19 P and C-165/19 P

The CJEU considered exclusionary conduct involving access to telecommunications infrastructure.

The case provides important guidance on the relationship between dominance, access obligations and foreclosure.

Relevance

Digital-twin platforms may similarly occupy an upstream infrastructure position while competing downstream.

For example:

Digital-twin infrastructure → logistics marketplace → logistics services

The provider's control over the first layer may allow it to influence competition in the second and third layers.

Principle

Access-related conduct by dominant vertically integrated firms can be assessed through the effects it produces on downstream competition.

22. 8. United Brands v Commission, 27/76

United Brands is a foundational EU abuse-of-dominance case.

The CJEU addressed market power, dependence and exclusionary conduct in a vertically structured commercial environment.

Relevance

Digital twins can create new forms of commercial dependence.

A manufacturer may become dependent upon a particular platform because:

• all its suppliers are connected to it;
• its historical data is stored there;
• customers require compatibility with it;
• switching is expensive; and
• its AI models are integrated into operations.

United Brands therefore helps illustrate the broader concept of economic dependence arising from market power.

23. Synthesis of the Case Law

24. Systemic Control Through a Digital-Twin Ecosystem

The greatest risk occurs when several forms of control combine.

For example:

Data ownership
↓
Predictive superiority
↓
Network effects
↓
Interoperability control
↓
Supplier dependency
↓
Logistics optimization
↓
Downstream market power

At this point the platform may no longer merely participate in the market.

It may effectively shape the market in which its customers and competitors operate.

25. Algorithmic Discrimination

A digital twin can theoretically assign different optimization outcomes to different users.

For example:

• preferred customers receive earlier delivery slots;
• affiliated companies receive scarce capacity;
• rivals receive less favourable routes;
• independent suppliers receive inferior forecasts;
• certain competitors receive delayed information.

Because the decisions may be generated by machine-learning models, discrimination can be difficult to detect.

Competition authorities may therefore need access to:

• model documentation;
• training-data governance;
• audit logs;
• API records;
• optimization parameters;
• historical outputs; and
• version histories.

26. Cybersecurity and Systemic Competition Risk

A concentrated digital-twin infrastructure creates another problem: single-point dependency.

If many competitors depend upon one platform, disruption of that platform could affect an entire industry.

A cyberattack or technical failure could simultaneously affect:

• production;
• inventory;
• shipping;
• warehousing;
• procurement; and
• distribution.

This makes digital-twin governance partly a competition-law and systemic-resilience issue.

27. Data Portability

Data portability can reduce switching costs.

A customer leaving a dominant digital twin may otherwise lose:

• historical production data;
• machine-learning models;
• supplier histories;
• workflow configurations;
• optimization records; and
• interoperability mappings.

Effective portability can therefore facilitate contestability.

But portability must be designed carefully because it may involve:

• confidential information;
• personal data;
• trade secrets;
• cybersecurity concerns; and
• third-party data.

28. Competition Risks from Common Digital Twins

A particularly sensitive scenario occurs when competing firms use the same digital twin.

The platform could potentially become a neutral technological intermediary—or, if poorly governed, a mechanism for coordinated behaviour.

Competition authorities should examine:

1. what data each participant provides;
2. what data each participant receives;
3. whether competitor-specific information is visible;
4. whether algorithms use competitors' confidential information;
5. whether recommendations are individualized;
6. whether pricing decisions are affected;
7. whether the platform controls strategic variables; and
8. whether customers can opt out.

29. Remedies

Potential remedies include:

Structural remedies

• separation of infrastructure and downstream businesses;
• divestiture;
• restrictions on acquisitions.

Behavioural remedies

• non-discrimination;
• transparent access criteria;
• interoperability;
• API access;
• data portability;
• restrictions on data combination;
• independent auditing.

Algorithmic remedies

• algorithmic auditing;
• logging requirements;
• model governance;
• explainability;
• monitoring for discriminatory outputs;
• restrictions on competitor-sensitive inputs.

Governance remedies

• independent compliance committees;
• data-access firewalls;
• confidentiality protocols;
• independent trustees;
• periodic competition audits.

30. Key Legal Questions for Competition Authorities

When investigating a supply-chain digital twin, authorities should ask:

Market power

• Does the platform have substantial market share?
• Are network effects significant?
• Are switching costs high?

Data

• Is the data unique?
• Can rivals reproduce it?
• Does the provider combine data from competing businesses?

Access

• Can competitors access the platform?
• Are APIs available?
• Are interoperability conditions discriminatory?

Algorithms

• Does the system facilitate coordination?
• Does it use competitor-sensitive information?
• Does it favour affiliated businesses?

Vertical integration

• Does the platform compete downstream?
• Does it operate logistics, warehousing or procurement services?

Mergers

• Could an acquisition eliminate an emerging competitor?
• Would the transaction combine complementary datasets?

Conclusion

Global supply-chain digital twins represent a major technological transformation because they can integrate physical infrastructure, data, algorithms and commercial decision-making into a single computational environment.

Their competition-law significance lies not merely in software market share. The central issue is the possibility of systemic control.

The most important risks are:

• concentration of strategic supply-chain data;
• algorithmic coordination;
• exclusion through interoperability restrictions;
• discriminatory access;
• self-preferencing;
• vertical foreclosure;
• tying and bundling;
• excessive switching costs;
• data-driven entry barriers; and
• acquisition of nascent digital-twin competitors.

The cases of Terminal Railroad, AT&T, Bronner, IMS Health, Microsoft, Google Shopping, Slovak Telekom and United Brands demonstrate that competition law already possesses doctrines capable of addressing many of these problems. What changes with digital twins is the scale, speed and automation with which market power can be exercised.

Ultimately, competition authorities should treat powerful digital twins not merely as software products but, where the facts justify it, as potential digital infrastructure governing access to economically critical supply chains. The central regulatory objective should be to preserve efficiency and innovation while preventing a single platform from becoming an indispensable technological gatekeeper capable of controlling competitors' data, access, routing, capacity and commercial decisions.

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