Competition Law and Intelligent Value Ecosystems and Dominance

1. Introduction

An intelligent value ecosystem is a business environment in which multiple interconnected products, services, platforms, data resources, algorithms, devices, applications, suppliers and consumers interact to create and capture value. Unlike a conventional market, competition may occur not merely between individual products but between entire ecosystems.

Examples include:

• smartphone–operating-system–app-store ecosystems;
• search–advertising–browser–mapping ecosystems;
• e-commerce–payments–logistics–cloud ecosystems;
• connected-car–charging–software ecosystems;
• cloud–AI–data–application ecosystems;
• digital-payment–banking–merchant ecosystems.

The competition-law problem arises when an undertaking uses control over one part of an ecosystem to obtain or reinforce power in adjacent markets.

Modern competition authorities increasingly examine data, algorithms, interoperability, network effects, switching costs, self-preferencing, tying, exclusivity, access restrictions and ecosystem-wide leverage, rather than relying exclusively upon traditional market-share analysis. China's 2026 Internet Platform Anti-Monopoly Compliance Guidelines expressly recognise data, algorithms, technology, capital and platform rules as potential sources of competition concerns.

2. Meaning of an Intelligent Value Ecosystem

An intelligent value ecosystem can be represented as:

Data → Algorithm → Platform → Users → Complementors → Transactions → More Data → Improved Algorithm → Greater User Attraction

This creates a potentially self-reinforcing competitive structure.

For example:

Operating system → App store → Apps → Users → Payments → Advertising → Data → Developer dependence

The ecosystem becomes strategically important when the operator controls several interconnected layers.

Core characteristics

A. Multi-sidedness

The ecosystem usually connects different groups:

• consumers;
• suppliers;
• advertisers;
• developers;
• merchants;
• payment providers;
• logistics providers.

Competition on one side can therefore affect competition on another.

B. Network effects

The value of the platform may increase as more users, developers or merchants participate.

C. Data feedback loops

More users generate more data; more data may improve algorithms; improved algorithms attract additional users.

D. Switching costs

Users may accumulate:

• transaction histories;
• subscriptions;
• contacts;
• purchased applications;
• loyalty benefits;
• cloud data;
• device integrations.

This can make migration to competing ecosystems costly.

E. Ecosystem lock-in

An undertaking may make individual products interoperable within its own ecosystem while making interoperability with rivals more difficult.

F. Vertical and horizontal integration

The ecosystem operator can simultaneously act as:

• infrastructure provider;
• platform operator;
• marketplace;
• advertiser;
• seller;
• payment intermediary;
• data processor;
• competitor of businesses dependent upon the platform.

This creates a significant dual-role problem.

3. Dominance in Intelligent Ecosystems

Traditional dominance analysis normally asks whether an undertaking possesses substantial market power in a defined relevant market.

In intelligent ecosystems, however, regulators may additionally examine ecosystem power.

Important indicators include:

1. market share;
2. control over critical infrastructure;
3. number of users;
4. number of dependent businesses;
5. network effects;
6. switching costs;
7. access to data;
8. interoperability;
9. control of technical standards;
10. vertical integration;
11. ability to discriminate between ecosystem participants;
12. ability to favour one's own downstream services.

Germany's Section 19a GWB is particularly significant because it permits enhanced scrutiny of enterprises of paramount significance for competition across markets. The Bundeskartellamt has applied this framework to Alphabet/Google, Amazon, Apple, Meta and Microsoft.

4. Major Competition-Law Concerns

A. Self-Preferencing

An ecosystem operator may rank or display its own service more favourably than competing services.

Example:

Search platform → own comparison service → competing comparison services

The concern is not merely that the undertaking owns competing products, but that it controls the distribution mechanism through which competitors reach consumers.

The EU's Google Shopping litigation is an important example.

B. Tying and Bundling

An undertaking may condition access to a dominant ecosystem component upon acceptance of another product.

Examples:

• operating system + search;
• app store + payment system;
• cloud infrastructure + software;
• smart device + proprietary application;
• payment wallet + merchant service.

Bundling can be legitimate where it produces efficiencies. Competition concerns arise where the bundle materially restricts competing suppliers.

C. Interoperability Restrictions

An ecosystem can become difficult to challenge when competitors cannot adequately interoperate with:

• APIs;
• operating systems;
• payment systems;
• data formats;
• authentication systems;
• hardware interfaces;
• cloud infrastructure.

Interoperability therefore becomes a central competition issue.

D. Data Advantage

Data can function as an important competitive input.

An ecosystem operator may possess data relating to:

• consumers;
• transactions;
• searches;
• merchants;
• developers;
• advertising;
• product performance.

The competitive concern becomes particularly strong where the operator uses data obtained from dependent businesses to compete against those same businesses.

E. Exclusivity

An ecosystem operator may impose or encourage:

• exclusive distribution;
• exclusive payment arrangements;
• exclusive app placement;
• exclusive advertising arrangements;
• default-status agreements.

Such arrangements may strengthen entry barriers when the ecosystem already possesses substantial network effects.

F. Switching Costs and Lock-In

Competition can be weakened if customers face substantial costs when moving from one ecosystem to another.

For example:

Device → operating system → applications → data → subscriptions → payments

The more interconnected these components become, the greater the potential switching cost.

5. At Least Six Important Case Laws

1. Google LLC and Alphabet Inc. v European Commission — Google Android, Case T-604/18

Court: General Court of the European Union
Year: 2022

This is one of the most important cases concerning an integrated digital ecosystem.

The case concerned Google's Android operating system, Play Store, Google Search and Chrome, together with contractual arrangements involving device manufacturers and mobile network operators.

The General Court considered:

• multi-sided platforms;
• ecosystem relationships;
• tying;
• exclusivity payments;
• anti-fragmentation arrangements;
• exclusionary effects.

The Court's judgment specifically characterised the dispute in terms of the interaction between Android, Play Store, Search and Chrome and examined the conduct as part of an overall strategy.

Principle

Competition law may examine conduct across interconnected ecosystem components rather than treating every product completely independently.

Relevance

For intelligent value ecosystems, the case demonstrates how:

OS + App Store + Search + Browser + Device manufacturers

can constitute a competitive structure in which power in one layer affects competition in another.

2. Google Shopping — Commission Decision, Case AT.39740

Authority: European Commission
Year: 2017

The European Commission found that Google had abused its dominant position by giving more favourable positioning and display to its own comparison-shopping service in general search results.

The case is particularly important for self-preferencing.

The modern EU market-definition materials expressly identify Google Shopping as an example relevant to digital ecosystems.

Principle

A dominant platform controlling an important gateway can potentially distort competition by systematically favouring its own downstream service.

Ecosystem significance

The competitive mechanism can be expressed as:

Dominant search gateway → ranking algorithm → consumer attention → own downstream service

Thus, control over distribution can be as important as control over the underlying product.

3. Google and Alphabet — Google Shopping General Court litigation

The subsequent judicial proceedings are important because they demonstrate the need to distinguish between:

• ordinary product innovation;
• legitimate algorithmic design;
• and exclusionary use of a dominant gateway.

The case illustrates how competition law can investigate algorithmically mediated preferential treatment.

For intelligent ecosystems, this is significant because algorithms increasingly determine:

• ranking;
• recommendations;
• visibility;
• advertising;
• product discovery;
• consumer choice.

4. Bundeskartellamt — Alphabet/Google, Section 19a GWB

Authority: German Federal Cartel Office

The Bundeskartellamt determined that Alphabet/Google possesses paramount significance for competition across markets.

Its analysis takes account of Google's broad ecosystem involving:

• Search;
• Maps;
• YouTube;
• Chrome;
• Android;
• Play Store;
• advertising services.

The authority notes that Google's ecosystem gives it significant influence over companies' access to users and advertising customers.

Principle

Competition law may recognise that market power arises from the combined significance of interconnected services, rather than from one isolated product.

Importance

This is particularly relevant to intelligent ecosystems because power may accumulate across multiple complementary markets.

5. Bundeskartellamt — Amazon, Section 19a GWB

Authority: German Federal Cartel Office

Amazon is an important ecosystem example because it operates across:

• online marketplace;
• retail;
• advertising;
• cloud services;
• streaming and other services.

The Bundeskartellamt describes Amazon as having combined multiple services into a digital ecosystem and determined in 2022 that Amazon had paramount significance for competition across markets. Germany's Federal Court of Justice upheld that determination in 2024.

Earlier competition issue

The authority had also examined Amazon's price-parity arrangements on its marketplace.

Principle

A platform can simultaneously be:

infrastructure + marketplace + seller + advertising provider

and this creates special competition concerns because the platform operator may compete with businesses that depend upon its infrastructure.

6. Bundeskartellamt — Apple, Section 19a GWB

The Bundeskartellamt determined in 2023 that Apple possesses paramount significance for competition across markets. The Federal Court of Justice confirmed the legal assessment in 2025.

The Apple ecosystem involves:

• iPhone;
• iOS;
• App Store;
• applications;
• payment mechanisms;
• developer relationships;
• digital services.

The authority has also examined Apple's App Tracking Transparency framework, including whether Apple's rules could favour its own offerings or impede competitors.

Principle

Competition authorities may scrutinise ecosystem rules where the ecosystem operator controls access to users while simultaneously offering competing services.

7. Bundeskartellamt — Facebook/Meta Data Combination Case

The German Facebook proceeding concerned the combination of user data obtained from different sources.

The case is significant because data aggregation can reinforce ecosystem power.

The competition concern can be represented as:

Multiple services → data combination → larger information advantage → improved targeting/product development → stronger ecosystem position

The Bundeskartellamt describes its Facebook proceeding as a landmark digital-sector abuse proceeding involving the combination of user data from different sources without voluntary consent.

Principle

Data advantages can become relevant to competition analysis where control over data contributes to market power or exclusionary effects.

8. Google — Data Processing / Cross-Service Data Case

The Bundeskartellamt's Google proceedings also examined the competitive implications of combining data across Google's services.

The authority stated that market power of large digital companies can be connected to the collection, processing and combination of data, and imposed user-choice measures in the Google data-processing proceeding.

Principle

Data aggregation across an ecosystem can create competitive advantages that are difficult for rivals to reproduce.

9. China: Alibaba — Platform Economy Antitrust

China provides particularly important material for intelligent value ecosystems.

The Alibaba enforcement action concerned the use of platform power and exclusive dealing/“choose one from two” arrangements.

The case demonstrates the application of China's Anti-Monopoly Law to platform ecosystems where merchants depend heavily upon access to a major platform.

Principle

A platform with substantial market power cannot necessarily use its ecosystem position to prevent merchants from dealing with competing platforms.

Ecosystem relevance

The conduct illustrates:

Platform users + merchants + data + traffic + exclusivity → ecosystem reinforcement

China's regulatory framework has subsequently developed considerably. The 2026 Internet Platform Anti-Monopoly Compliance Guidelines specifically identify data, algorithms, technology, capital and platform rules as possible sources of monopolistic conduct.

10. China: Meituan — Platform Economy and Exclusive Dealing

The Meituan enforcement action is another important Chinese platform-economy example.

It illustrates how a platform's control over:

• merchants;
• consumers;
• traffic;
• ordering infrastructure;
• data;
• platform rules

can create competitive concerns when merchants are pressured into exclusive arrangements.

The broader Chinese regulatory approach now expressly addresses platform practices such as refusal to deal, restrictions, tying and differential treatment.

6. Theoretical Model of Ecosystem Dominance

A useful analytical model is:

Stage 1 — Initial platform advantage

Large user base

↓

Stage 2 — Data accumulation

More users → more data

↓

Stage 3 — Algorithmic improvement

More data → better prediction/recommendation

↓

Stage 4 — Complementary services

More services → greater ecosystem value

↓

Stage 5 — Switching costs

More integration → greater user dependency

↓

Stage 6 — Competitor exclusion

Rivals find it harder to enter

↓

Stage 7 — Ecosystem dominance

Dominant position becomes self-reinforcing

Competition law becomes concerned particularly when the undertaking uses this position to exclude competitors rather than merely competing through superior products.

7. Intelligent Ecosystem and Relevant-Market Definition

Market definition becomes complicated because an ecosystem can contain multiple interconnected markets.

A regulator may separately examine:

The existence of an ecosystem does not automatically mean that all these markets constitute one relevant market.

Instead, authorities may analyse:

1. individual relevant markets;
2. relationships between markets;
3. ecosystem effects;
4. leveraging from one market into another.

8. Network Effects and Barriers to Entry

Intelligent ecosystems may produce unusually strong barriers to entry.

Direct network effect

More users → greater value for users.

Indirect network effect

More consumers → more sellers → more consumers.

Data network effect

More users → more data → better algorithm → more users.

Ecosystem network effect

More services → greater ecosystem value → stronger user retention → more complementary suppliers.

The last two are particularly significant for AI-driven ecosystems.

9. Self-Preferencing in Intelligent Ecosystems

A particularly important risk is:

Platform operator controls the rules while simultaneously competing under those rules.

For example:

Marketplace controls search ranking

↓

Marketplace also sells its own products

↓

Marketplace's algorithm ranks products

↓

Own products receive preferential treatment

This creates a potential conflict between the platform's role as a neutral intermediary and its role as a competitor.

The EU's current digital-market framework explicitly addresses self-preferencing. In July 2026, the European Commission announced DMA findings against Google concerning preferential treatment of Google's own services in Search.

10. Interoperability as a Competition Remedy

Where ecosystem power is based upon technical incompatibility, remedies may include:

• API access;
• data portability;
• interoperability;
• non-discriminatory access;
• technical standards;
• switching mechanisms;
• separation of certain functions;
• restrictions on self-preferencing.

The EU's Digital Markets Act, for example, includes obligations concerning interoperability, data portability, access to information and restrictions on self-preferencing for designated gatekeepers.

11. Chinese Competition-Law Position

For China, the principal framework is the Anti-Monopoly Law, supplemented by rules and guidance concerning the platform economy.

The 2026 SAMR Internet Platform Anti-Monopoly Compliance Guidelines are especially relevant to intelligent ecosystems.

They identify risks involving:

• algorithmic coordination;
• dynamic pricing;
• traffic allocation;
• product ranking;
• data sharing;
• refusal to deal;
• tying;
• differential treatment;
• platform rules;
• control over essential data, models and applications.

The Guidelines specifically recognise that a dominant platform may create refusal-to-deal problems through account blocking, traffic restrictions, interface closure, interruption of data sharing or control over essential data, models or application platforms.

This is highly relevant to intelligent value ecosystems because AI models, APIs and data infrastructures can themselves become strategically important ecosystem inputs.

12. Competition Concerns Across the Ecosystem

13. Intelligent Ecosystem Acquisitions

Competition law must also examine acquisitions within ecosystems.

A dominant ecosystem may acquire:

• emerging competitors;
• complementary applications;
• data-rich startups;
• AI companies;
• developers;
• infrastructure providers.

The concern is sometimes not the immediate market share of the target but its future competitive significance.

Thus, merger review may consider:

Does the acquisition remove an independent source of innovation that could have challenged the ecosystem?

This is particularly relevant to AI, cloud computing, digital payments and platform markets.

14. Efficiency Defences

Not every ecosystem integration is anticompetitive.

Integration can create legitimate benefits such as:

• improved cybersecurity;
• lower transaction costs;
• better interoperability;
• reduced fraud;
• faster services;
• improved product quality;
• enhanced privacy;
• innovation;
• lower consumer prices.

Therefore, the relevant legal question is not:

“Is the ecosystem large?”

but rather:

Does the undertaking's conduct exploit or reinforce market power in a manner that produces exclusionary or exploitative effects without sufficient legitimate justification?

15. Remedies

Competition authorities may use several remedies.

Structural remedies

• divestiture;
• separation of businesses;
• prohibition of certain acquisitions.

Behavioural remedies

• non-discrimination;
• interoperability;
• access obligations;
• data portability;
• restrictions on tying;
• restrictions on self-preferencing.

Technical remedies

• API access;
• interoperability protocols;
• ranking transparency;
• data-access mechanisms.

Governance remedies

• independent compliance monitoring;
• algorithmic auditing;
• internal competition compliance;
• reporting obligations.

16. Six-Core-Case Summary

17. Emerging Issues: AI-Based Intelligent Ecosystems

The next generation of ecosystem competition is likely to involve:

AI model ecosystems

Foundation model → API → applications → users → data → model improvement

Cloud-AI ecosystems

Cloud infrastructure → compute → AI model → enterprise applications

Autonomous mobility ecosystems

Vehicle → operating system → sensors → mapping → charging → insurance → data

Smart-home ecosystems

Device → operating system → voice assistant → marketplace → cloud → data

Financial ecosystems

Wallet → payment network → credit → merchant platform → advertising → financial data

In each situation, the competition question is whether control of one layer permits the undertaking to foreclose competitors at another layer.

18. Conclusion

Competition law concerning intelligent value ecosystems is moving beyond the traditional question of whether one company dominates one narrowly defined market.

The central issue is increasingly the architecture of market power:

Data + algorithms + users + infrastructure + interoperability + network effects + complementary services + switching costs = ecosystem power.

The principal competition risks are self-preferencing, tying, exclusive dealing, refusal of access, discriminatory algorithms, data advantages, interoperability restrictions, ecosystem acquisitions and leveraging of dominance.

The Google Android, Google Shopping, Google/Alphabet, Amazon, Apple and Facebook/Meta proceedings demonstrate how modern competition authorities examine interconnected digital services. China's Alibaba and Meituan enforcement experience, together with the 2026 SAMR Internet Platform Anti-Monopoly Compliance Guidelines, demonstrates a similar movement toward analysing data, algorithms, technology and platform rules as components of competitive power.

Accordingly, the key legal principle for intelligent value ecosystems is:

Dominance is not necessarily created by one product alone; it may be reinforced by control over the interconnected architecture through which consumers, data, complementors and rival businesses reach one another.