Competition Law and Intelligent Value Ecosystems and Dominance

1. Introduction

An intelligent value ecosystem is a business ecosystem in which multiple products, services, platforms, data resources, algorithms, artificial intelligence systems, payment mechanisms, distribution channels, suppliers, developers and consumers are interconnected so that value is created across the ecosystem rather than through a single standalone product.

Examples include:

• e-commerce + payments + logistics + advertising;
• smartphones + operating systems + app stores + search + advertising;
• gaming + streaming + social networks + payment systems;
• food-delivery + restaurants + riders + advertising + consumer data;
• cloud computing + AI models + data + enterprise software;
• digital music + copyright + streaming platforms;
• mobility + mapping + payments + vehicle services.

Competition law becomes particularly important when an undertaking uses its position in one part of the ecosystem to extend or reinforce market power into adjacent markets.

China's platform-economy framework expressly recognises that platforms can use data, algorithms, technology, capital advantages and platform rules to strengthen market power. The 2026 SAMR Internet Platform Antitrust Compliance Guidelines similarly identify these resources as potential sources of competition risk.

2. Meaning of Intelligent Value Ecosystem Dominance

The concept can be understood through five interconnected elements:

A. Data

The ecosystem collects:

• consumer behaviour;
• purchasing history;
• search data;
• location information;
• transaction information;
• supplier performance;
• pricing information;
• engagement data.

Large-scale data accumulation can create advantages that competitors cannot easily reproduce.

B. Algorithms and AI

Algorithms can determine:

• rankings;
• recommendations;
• prices;
• advertising allocation;
• search visibility;
• access to customers;
• credit or risk assessments;
• delivery allocation.

The competition concern arises where algorithms are used not merely for efficiency but to exclude competitors or discriminate against business users.

C. Network effects

More users can attract more sellers, developers and service providers, which in turn attract more users.

This can produce:

more users → more data → better services → more users → greater ecosystem power.

D. Ecosystem integration

A dominant undertaking may connect:

operating system → app store → payment → advertising → cloud → AI → consumer data.

The integration may produce genuine efficiencies, but it may also make entry into one component dependent upon access to another.

E. Switching costs

Consumers and businesses may become dependent upon:

• accumulated data;
• digital identities;
• loyalty benefits;
• payment accounts;
• software compatibility;
• developer tools;
• customer reviews;
• advertising histories;
• ecosystem-specific hardware.

High switching costs can make an apparently contestable market substantially less competitive.

3. Relevant Competition-Law Issues

I. Market Definition

Traditional product-by-product market definition may be insufficient.

Authorities may examine:

1. the individual product market;
2. the platform market;
3. adjacent markets;
4. multi-sided markets;
5. ecosystem relationships;
6. data or technology inputs.

China's platform-economy guidance specifically recognises the special characteristics of platform markets when analysing competition.

4. Establishing Dominance

Dominance may be demonstrated through factors such as:

Market share

A high market share can be important, but it is not necessarily conclusive.

Network effects

The stronger the network effect, the greater the potential entry barrier.

Control over important inputs

Examples include:

• essential data;
• app-store access;
• payment infrastructure;
• intellectual property;
• cloud infrastructure;
• digital identity;
• advertising inventory.

Technological advantages

AI models, proprietary algorithms and technical standards may strengthen market power.

User dependence

Dependence of merchants, developers or consumers can be particularly important.

Financial and capital strength

Large ecosystems may finance expansion into adjacent markets and absorb losses during market entry.

5. Major Forms of Abuse

A. Self-preferencing

An ecosystem operator may give its own downstream service preferential:

• ranking;
• visibility;
• access;
• recommendation;
• pricing;
• advertising placement.

Example:

Platform → controls search → owns competing service → algorithm favours its own service.

This can disadvantage independent competitors.

B. Tying and Bundling

A dominant ecosystem may condition access to one service upon acceptance of another.

Examples:

• operating system + search;
• app store + payment system;
• cloud + software;
• hardware + proprietary services.

The legal question is whether the linkage is objectively justified or instead forecloses competing suppliers.

C. Exclusive Dealing

An ecosystem may require merchants, developers or suppliers to deal exclusively with it.

This was central to China's Alibaba and Meituan cases.

D. Refusal to Deal or Access

A dominant ecosystem may deny competitors:

• APIs;
• data;
• interoperability;
• app-store access;
• technical interfaces;
• essential infrastructure.

China's platform guidelines specifically identify refusal to transact and restrictions involving platform rules, algorithms, technology and data as potential forms of abuse.

E. Discriminatory Treatment

Algorithms can impose different:

• prices;
• commissions;
• rankings;
• access conditions;
• payment conditions.

China's platform guidance expressly identifies algorithmic differentiation based upon payment ability, consumption preferences and usage behaviour as a possible discriminatory practice.

F. Predatory or Strategic Pricing

An ecosystem may subsidise one side of a market while recovering losses from another side.

Competition analysis must therefore consider the whole ecosystem, rather than examining one transaction in isolation.

6. Important Case Laws

1. Alibaba Group – “Choose One from Two” Case, China, 2021

This is one of the most important Chinese platform-dominance cases.

SAMR found that Alibaba held a dominant position in China's online retail-platform service market. Since 2015, it required merchants to choose between Alibaba and competing platforms and used platform rules, data, algorithms and incentives/penalties to enforce the arrangement.

SAMR concluded that the conduct constituted abuse through restricting counterparties to transact exclusively with it.

Alibaba was fined RMB 18.228 billion, equivalent to 4% of its 2019 domestic sales, and ordered to stop the unlawful conduct and undertake compliance reforms.

Principle

The case demonstrates that:

ecosystem power + platform rules + data/algorithmic enforcement + exclusivity can constitute abusive dominance.

7. Meituan – Food-Delivery “Choose One” Case, China, 2021

SAMR investigated Meituan's conduct in the online food-delivery platform market.

According to SAMR, Meituan used:

• differentiated fee rates;
• delayed merchant onboarding;
• exclusive cooperation arrangements;
• exclusive-dealing deposits;
• data;
• algorithms;
• punitive measures.

The authority concluded that the conduct restricted merchants from dealing with competing platforms and constituted abuse of dominant position.

Meituan was fined RMB 3.442 billion, required to return RMB 1.289 billion in exclusive-cooperation deposits and ordered to undertake compliance measures.

Principle

The case shows that an intelligent ecosystem can exercise market power through algorithmic and contractual control over ecosystem participants, rather than simply through price increases.

8. Tencent Music / China Music Group Case, China, 2021

SAMR investigated Tencent's acquisition of China Music Group.

The relevant market was China's online music platform market. SAMR noted that music copyright constituted a key resource and that, following the transaction, the combined entity would control more than 80% of exclusive music-library resources.

The authority concluded that the concentration could strengthen Tencent's ability to obtain exclusive copyright arrangements and raise barriers to entry.

SAMR ordered Tencent to:

• terminate exclusive copyright arrangements;
• restore competitive conditions;
• take specified corrective measures.

Principle

This illustrates input foreclosure within an intelligent ecosystem:

control of a critical upstream resource → control of downstream platforms → stronger ecosystem dominance.

9. Tencent / Huya–DouYu Merger Case, China, 2021

SAMR prohibited the proposed combination of Huya and DouYu.

The relevant markets included:

• online game operation services; and
• game live-streaming services.

SAMR found that Tencent already possessed significant control in the upstream online-game market, while Huya and DouYu were major competitors in game livestreaming. Their combination would have further strengthened Tencent's position and could have enabled vertical foreclosure and closed-loop control across the upstream and downstream markets.

Principle

This case is particularly important for ecosystem analysis because competition effects were not confined to the immediate merger market.

The authority considered:

upstream market power + downstream platform control + vertical integration = potential ecosystem foreclosure.

10. Google Android Case – European Union, 2018

The European Commission fined Google €4.34 billion concerning practices involving Android mobile devices.

The Commission concluded that Google had imposed restrictions involving Android manufacturers and mobile-network operators in a manner that strengthened Google's position in general search.

The case is significant because Android formed part of a broader ecosystem involving:

• operating systems;
• mobile devices;
• search;
• applications;
• app distribution;
• advertising.

Principle

The case demonstrates the competition-law relevance of leveraging dominance from one technological layer into another.

The ecosystem question is therefore:

Can control over an operating system be used to reinforce power in search or other adjacent markets?

11. Google Shopping Case – European Union, 2017

The European Commission found that Google had abused its dominant position as a general search engine by giving preferential treatment to its own comparison-shopping service.

The conduct concerned the relationship between:

• general search;
• search ranking;
• comparison shopping;
• advertising;
• consumer traffic.

The case therefore illustrates self-preferencing within a digital ecosystem. The Commission's competition-policy materials identify the case as a major 2017 digital competition enforcement action.

Principle

A platform acting simultaneously as:

1. infrastructure provider, and
2. competitor,

may create a conflict between its gatekeeper function and its downstream commercial interests.

12. Facebook/Meta – FTC Case, United States

The U.S. Federal Trade Commission brought an antitrust action alleging that Facebook maintained a personal-social-networking monopoly through a course of conduct that included the acquisitions of Instagram and WhatsApp and restrictions imposed on software developers.

The case illustrates the ecosystem expansion theory of harm:

dominant platform → acquisition of emerging competitive threats → increased ecosystem control.

The case remains an important example of how merger policy and unilateral-conduct analysis can intersect in digital ecosystems.

13. Comparative Legal Principles

14. Intelligent Ecosystems and “Leveraging” Theory

A central competition-law concern is leveraging.

Suppose an undertaking has substantial power in Market A:

AI operating infrastructure

and uses that position to strengthen its position in Market B:

AI applications

and Market C:

cloud services.

Competition authorities may examine whether conduct in Market A artificially protects or extends the undertaking's position in Markets B and C.

The analysis becomes stronger where the undertaking controls a bottleneck resource.

15. The Role of Algorithms

Algorithms create several distinctive competition issues.

Algorithmic exclusion

An algorithm may:

• reduce a rival's ranking;
• restrict access to users;
• reduce visibility;
• alter commissions;
• discriminate between sellers.

Algorithmic coordination

Competing platforms may use algorithms to coordinate prices or other competitive parameters.

China's 2026 Internet Platform Antitrust Compliance Guidelines expressly identify algorithms, AI, shared data pools, interoperability arrangements and other technological mechanisms as potential means through which competitively sensitive information or coordinated conduct can arise.

Algorithmic opacity

The difficulty is that traditional evidence may not reveal the mechanism by which exclusion occurred.

Consequently, competition compliance increasingly requires:

• algorithm audits;
• access logs;
• model documentation;
• version histories;
• ranking records;
• pricing records;
• data-use records.

16. Essential-Facility Dimension

An intelligent ecosystem may become particularly problematic where a platform controls infrastructure that competitors cannot reasonably reproduce.

Potential examples include:

• critical cloud infrastructure;
• app distribution;
• payment infrastructure;
• proprietary technical interfaces;
• indispensable datasets;
• interoperability infrastructure.

China's platform-economy guidance states that whether a platform constitutes an essential facility should be assessed by considering factors including data holdings, substitutability of other platforms, potential platforms, feasibility of developing competing platforms, dependence of counterparties and the impact of opening the platform.

17. Merger-Control Dimension

Ecosystem dominance also creates a special problem in merger review.

A transaction may appear small when considered solely in terms of current revenue but may be strategically important because the target possesses:

• valuable data;
• innovative technology;
• AI capabilities;
• users;
• developers;
• complementary infrastructure;
• potential future competition.

Accordingly, competition authorities may examine whether the acquisition removes a potential competitive constraint.

The Huya–DouYu decision illustrates this ecosystem-based merger analysis, with SAMR examining not merely horizontal overlap but also Tencent's upstream position and the possibility of vertical foreclosure.

18. Network Effects and Tipping

Intelligent ecosystems can experience market tipping.

A simplified cycle is:

More users
↓
More data
↓
Better algorithms
↓
Better recommendations/services
↓
More merchants/developers
↓
More users

This positive feedback loop can produce substantial competitive advantages.

Competition law therefore has to distinguish between:

Legitimate ecosystem efficiencies

and

Artificial exclusion.

The existence of a large ecosystem is not by itself unlawful. The critical question is whether the undertaking's conduct excludes or restricts competition without adequate legal or economic justification.

19. Consumer Welfare and Innovation

Intelligent ecosystems can simultaneously generate:

Benefits

• lower transaction costs;
• better recommendations;
• integrated payment;
• faster delivery;
• improved cybersecurity;
• personalised services;
• technological innovation.

But potential competition concerns include:

• reduced consumer choice;
• higher switching costs;
• exclusion of independent businesses;
• reduced innovation;
• higher commissions;
• discriminatory treatment;
• privacy-related competitive effects;
• reduced interoperability.

Therefore, competition analysis should not assume that integration is inherently anticompetitive.

20. Defences and Legitimate Justifications

An ecosystem operator may have legitimate reasons for:

• security restrictions;
• quality-control standards;
• technical integration;
• fraud prevention;
• privacy protection;
• cybersecurity;
• interoperability limitations;
• exclusive arrangements;
• product bundling.

China's platform guidance expressly recognises possible legitimate reasons for practices such as refusal to deal, tying and differentiated treatment.

The crucial issue is whether the justification is genuine, proportionate and consistent with the competitive effects of the conduct.

21. Remedies

Competition authorities may employ:

Structural remedies

• divestiture;
• prohibition of mergers;
• separation of business units.

Behavioural remedies

• termination of exclusivity;
• non-discrimination obligations;
• interoperability;
• API access;
• data portability;
• prohibition of self-preferencing;
• modification of platform rules.

Compliance remedies

• algorithm audits;
• internal competition-law review;
• data governance;
• merger-control procedures;
• employee training;
• documentation and audit trails.

China's 2026 platform compliance guidelines specifically encourage pre-transaction and pre-business-change competition assessments, platform-rule review and algorithm screening.

22. Key Doctrinal Tests

For an examination or research paper, the following framework is useful:

Step 1 – Identify the ecosystem

↓

Step 2 – Identify relevant product/platform markets

↓

Step 3 – Assess market power

↓

Step 4 – Identify the ecosystem bottleneck

↓

Step 5 – Identify conduct

• tying?
• exclusivity?
• self-preferencing?
• refusal to deal?
• discriminatory access?
• data foreclosure?
• algorithmic exclusion?
• acquisition?

↓

Step 6 – Establish competitive effects

• foreclosure;
• entry barriers;
• innovation effects;
• consumer effects;
• reduction of multi-homing;
• network-effect amplification.

↓

Step 7 – Examine legitimate justification

↓

Step 8 – Assess proportionality and efficiencies

↓

Step 9 – Determine appropriate remedy

23. Overall Legal Significance

The central competition-law problem with an intelligent value ecosystem is not simply that one company becomes large.

Rather, the concern arises when multiple sources of market power reinforce each other:

Data + AI + algorithms + network effects + infrastructure + capital + ecosystem integration + switching costs

can create a self-reinforcing competitive position.

The Alibaba and Meituan cases demonstrate how ecosystem operators can use platform rules, data and algorithms to enforce exclusivity. The Tencent Music case illustrates control over an important upstream input. The Huya–DouYu case demonstrates the merger-control dimension of ecosystem expansion and vertical foreclosure. Google Android and Google Shopping demonstrate comparable concerns concerning leveraging and self-preferencing in another major competition-law jurisdiction.

Conclusion

Intelligent value ecosystems are not inherently monopolistic or unlawful. Competition law becomes engaged where ecosystem integration is used to exclude rivals, foreclose access, discriminate against competitors, lock in users, acquire nascent competitive threats, or extend dominance from one market into another.

For China in particular, the modern platform-competition framework increasingly treats data, algorithms, technology, platform rules, network effects and ecosystem dependence as relevant to assessing market power and abuse. The 2026 SAMR compliance guidance reinforces this approach by calling for competition-risk assessment at the stages of rule-making, algorithm design, business restructuring and investment/M&A.

Key Cases at a Glance

1. Alibaba Group – Online Retail “Choose One from Two” (2021) — exclusive dealing and platform dominance.
2. Meituan – Online Food Delivery “Choose One from Two” (2021) — exclusivity enforced through data, algorithms and platform mechanisms.
3. Tencent/China Music Group (2021) — control over critical copyright resources and downstream market power.
4. Tencent/Huya–DouYu (2021) — ecosystem concentration and vertical foreclosure.
5. Google Android (EU, 2018) — leveraging operating-system power into search.
6. Google Shopping (EU, 2017) — self-preferencing within a search ecosystem.
7. FTC v. Facebook/Meta — ecosystem expansion and acquisitions of potential competitive threats.