Competition Law and Ecosystem Competition Indicators

1. Meaning

Ecosystem competition indicators are the economic, structural, technological and behavioural measures used to determine whether competition within an interconnected business ecosystem is strong, weakening, or being potentially foreclosed.

Traditional antitrust analysis may ask:

“What is the firm's market share?”

Ecosystem analysis asks a wider set of questions:

“How many markets does the firm connect?”
“How dependent are users and complementors?”
“Can rivals interoperate?”
“Can customers multi-home?”
“Does data reinforce the firm's position?”
“Can the firm leverage power from one market into another?”

This is particularly important for digital ecosystems, platforms, payment systems, app stores, cloud services, e-commerce, advertising and data-driven businesses.

2. Core Formula

ECOSYSTEM COMPETITION INDICATORS =

Market Structure + Network Effects + User Dependence + Interoperability + Multi-Homing + Data + Entry Conditions + Conduct + Competitive Effects

A high value on one indicator does not automatically establish an antitrust violation. The indicators are evidence used within the applicable legal test.

3. Why Ecosystem Indicators Matter

An ecosystem can contain several interconnected markets.

Example

Operating System       ↓   App Store       ↓ Applications       ↓   Payments       ↓ Consumer Data       ↓ Advertising

Looking at only the app-store market may miss important competitive relationships.

A competition authority may therefore examine the entire competitive ecosystem.

4. Major Ecosystem Competition Indicators

Indicator 1 — Market Share

The starting point remains market share.

Market Share=Firm′s SalesTotal Market Sales×100Market\ Share = \frac{Firm's\ Sales}{Total\ Market\ Sales}\times100

Market share can indicate:

scale;

customer reach;

bargaining power;

potential dominance.

But:

Market share alone is not sufficient for ecosystem analysis.

5. Indicator 2 — Market Concentration

A common quantitative indicator is the HHI:

HHI=∑si2HHI=\sum s_i^2

where sis_i represents each firm's market share.

Example

Four firms:

A = 40%

B = 30%

C = 20%

D = 10%

HHI=402+302+202+102HHI=40^2+30^2+20^2+10^2 =1600+900+400+100=3000=1600+900+400+100=3000

But an ecosystem investigation should not stop at HHI.

A market with moderate HHI may still contain a powerful ecosystem operator because of network effects or vertical integration.

6. Indicator 3 — Network Effects

A network effect exists when the value of a service changes as participation changes.

Direct network effect

More users → greater value

Example:

social networks;

communication services.

Indirect network effect

More users on Side A → greater value for Side B

Example:

Consumers ↔ Platform ↔ Merchants

Competition indicator

Ask:

How strongly does the existing user base reinforce the platform's position?

7. Indicator 4 — User Base

A large installed user base may create an important competitive advantage.

Relevant measurements include:

active users;

monthly active users;

daily active users;

customer retention;

transaction volume;

percentage of industry users;

growth rate.

Formula

User Penetration=Platform UsersPotential Users×100User\ Penetration = \frac{Platform\ Users}{Potential\ Users}\times100

A very high user base can indicate strong network effects, but again, large scale is not synonymous with unlawful dominance.

8. Indicator 5 — Multi-Homing

Multi-homing means users participate in multiple competing ecosystems.

Example

A merchant uses:

Platform A;

Platform B;

its own website.

High multi-homing

Competition may remain stronger because customers can maintain multiple relationships.

Low multi-homing

A platform may have greater ability to lock in customers.

Therefore:

Multi-homing rate is an important ecosystem competition indicator.

9. Indicator 6 — Switching Costs

Switching costs measure the difficulty of moving from one ecosystem to another.

Examples:

data migration costs;

retraining;

lost contacts;

lost customer reviews;

incompatible software;

contractual penalties;

loss of accumulated rewards.

Formula

Switching Cost=Financial+Technical+Contractual+BehaviouralCostsSwitching\ Cost = Financial + Technical + Contractual + Behavioural Costs

High switching costs can strengthen incumbent power.

10. Indicator 7 — Interoperability

Interoperability measures whether different systems can communicate or function together.

Open system

Platform A ↔ Platform B ↔ Platform C

Closed system

Platform A   ↓ Own ecosystem only

Low interoperability may:

increase lock-in;

prevent entry;

reduce consumer choice;

make multi-homing difficult.

The Court of Justice's 2025 Alphabet and Others, C-233/23 judgment specifically addressed the competition-law significance of interoperability between a dominant digital platform and third-party applications. (curia)

11. Indicator 8 — Data Concentration

Data can become a strategic competitive asset.

Data flywheel

More users

↓

More data

↓

Better analytics

↓

Better product/service

↓

More users

A competition assessment may therefore examine:

volume of data;

uniqueness;

quality;

freshness;

replicability;

access by competitors;

portability;

cross-market combination.

12. Indicator 9 — Data Portability

Ask:

Can customers take their data to a competing ecosystem?

High portability

Exit easier → competition stronger

Low portability

Exit harder → lock-in stronger

Data portability is therefore an important indicator of ecosystem contestability.

13. Indicator 10 — Entry Barriers

Important ecosystem entry barriers include:

network effects;

high capital requirements;

access to data;

intellectual property;

infrastructure;

interoperability;

customer switching costs;

brand recognition;

regulatory requirements.

Ecosystem entry formula

Effective Entry = Technology + Capital + Users + Data + Distribution + Interoperability

A technically capable entrant may still fail if it cannot obtain enough users.

14. Indicator 11 — Centrality

A company may become a central node connecting many participants.

Example

Supplier A ─┐ Supplier B ─┼── Platform X ── Customer A Supplier C ─┤               └─ Customer B Supplier D ─┘

Platform X may have high network centrality.

Relevant measurements can include:

degree centrality;

betweenness centrality;

closeness centrality;

eigenvector centrality.

15. Indicator 12 — Gateway Control

A gateway indicator asks:

How necessary is the platform for reaching customers?

Examples:

app store;

search engine;

payment network;

online marketplace;

operating system;

advertising exchange.

The stronger the gateway function, the greater the potential importance of access conditions.

16. Indicator 13 — Vertical Integration

An ecosystem operator may control several levels:

Infrastructure      ↓ Platform      ↓ Distribution      ↓ Retail

This may create efficiencies.

But it may also create opportunities for:

foreclosure;

discrimination;

tying;

self-preferencing;

margin squeeze.

Therefore:

Vertical integration is an indicator of potential ecosystem leverage, not proof of illegality.

17. Indicator 14 — Self-Preferencing

Ask:

Does the platform give its own product an advantage over competing products?

Possible indicators:

ranking position;

default status;

search visibility;

access to data;

technical integration;

pricing;

commission structure.

The Google Shopping case is particularly important here. The Court of Justice upheld the finding that Google had abused its dominant position by favouring its own comparison-shopping service in general search results. (InfoCuria)

18. Indicator 15 — Tying and Bundling

A platform may combine two products.

Example

Product A   + Product B   ↓ Ecosystem Package

Competition analysis asks:

Are the products separate?

Is the firm dominant in A?

Is purchase of B effectively required?

Can rivals compete in B?

Are there efficiencies?

Is foreclosure likely?

The 2026 Google Android, C-738/22 P judgment is an important modern authority concerning contractual restrictions, tying, exclusive pre-installation payments and Android-fork restrictions. (InfoCuria)

19. Indicator 16 — Exclusivity

Exclusivity may prevent ecosystem participants from using rivals.

Example

Supplier   ↓ Exclusive Platform A   X Platform B

Important measurements include:

percentage of customers covered;

contract duration;

renewal rate;

market coverage;

availability of alternative channels.

20. Indicator 17 — Churn Rate

Churn measures how quickly customers leave a platform.

Churn Rate=Customers LostCustomers at Beginning×100Churn\ Rate= \frac{Customers\ Lost}{Customers\ at\ Beginning}\times100

High churn

May indicate:

weak lock-in;

strong competition;

low switching costs.

Low churn

May indicate:

customer loyalty;

strong product quality;

network effects;

high switching costs.

Low churn cannot by itself prove market power.

21. Indicator 18 — Customer Dependency

Measure:

How economically dependent are customers on the ecosystem?

Possible measures:

percentage of business revenue generated through platform;

percentage of transactions through platform;

number of alternative platforms;

cost of leaving;

availability of alternative distribution channels.

22. Indicator 19 — Complementor Dependence

An ecosystem may contain:

developers;

merchants;

advertisers;

suppliers;

content providers.

Ask:

How dependent are these complementors on the ecosystem owner?

Example

100,000 Developers       ↓     App Store       ↓   1 Billion Users

The platform may possess substantial bargaining power over developers because access to users is concentrated.

23. Indicator 20 — Developer/Complementor Growth

A strong ecosystem often attracts complementary businesses.

Indicators include:

number of developers;

number of apps;

number of sellers;

number of merchants;

number of advertisers;

developer revenues;

growth rate.

Feedback mechanism

More users → more developers → more products → more users

24. Indicator 21 — Cross-Market Leverage

This is one of the most important indicators.

Example

A firm has power in:

Market A

and uses that position to strengthen:

Market B

Market A Dominance    ↓ Leverage    ↓ Market B Competitive weakening

Google Shopping is a leading authority illustrating the legal significance of leveraging dominance from general search into comparison-shopping. (InfoCuria)

25. Indicator 22 — Ecosystem Coverage

Measure the number of connected markets in which the firm operates.

Example

Firm X operates in:

OS

Search

Browser

Payments

Cloud

Advertising

Hardware

Greater ecosystem coverage may create greater opportunities for cross-market reinforcement.

But:

Diversification is not automatically anticompetitive.

26. Indicator 23 — Internal Subsidisation

A firm may use profits from one ecosystem market to subsidise another.

Example

Market A profits       ↓ Subsidy       ↓ Market B low prices       ↓ Competitors weakened

The relevant legal question is whether the pricing or conduct satisfies the applicable competition-law test, rather than assuming that cross-subsidisation itself is unlawful.

27. Indicator 24 — Ecosystem Price Relationships

Traditional price analysis may be insufficient.

Authorities may examine:

commissions;

platform fees;

subscription prices;

advertising prices;

cross-subsidies;

zero-price services.

A zero monetary price does not mean the service has no economic value.

Competition may instead occur through:

data;

attention;

quality;

privacy;

innovation.

28. Indicator 25 — Innovation Rate

Possible indicators:

R&D expenditure;

patent activity;

product launches;

technology improvements;

developer innovation;

startup entry.

Concern

If ecosystem control causes:

Entry ↓ + Innovation ↓ + Rival development ↓

there may be a competitive concern.

29. Indicator 26 — Rivals' Growth

One particularly useful indicator is:

Can competitors grow inside the ecosystem?

Measure:

rival user growth;

rival transaction growth;

rival developer adoption;

rival revenue;

rival retention.

The Court's Google Shopping jurisprudence has emphasised the capability of conduct to foreclose competition and the need to assess causal and competitive effects rather than relying merely on formal market position. (InfoCuria)

30. Indicator 27 — Interoperability Requests

A particularly useful qualitative indicator is:

How often do third parties request technical access?

If numerous businesses require access to:

APIs;

operating systems;

payment infrastructure;

data;

technical standards,

this may indicate that the ecosystem has become an important gateway.

The legal test remains fact-specific. In Microsoft, the General Court dealt with refusal to provide interoperability information; the case involved both interoperability and tying issues. (InfoCuria)

31. Indicator 28 — Replicability

Ask:

Can competitors reproduce the ecosystem advantage?

Easily replicable

Competitive advantage may be temporary.

Difficult to replicate

Advantage may become durable.

Relevant factors:

data;

infrastructure;

network size;

intellectual property;

accumulated reputation;

historical transactions.

32. Indicator 29 — Time to Reach Critical Mass

A new entrant may require:

1 million users;

10,000 merchants;

5,000 developers;

before its ecosystem becomes commercially viable.

The longer the time and higher the investment required to achieve this critical mass, the greater the entry barrier may be.

33. Indicator 30 — Ecosystem Dependency Ratio

A useful analytical concept is:

EDR=Transactions Through Dominant EcosystemTotal Relevant TransactionsEDR = \frac{Transactions\ Through\ Dominant\ Ecosystem} {Total\ Relevant\ Transactions}

For example:

If 80% of a seller's relevant transactions occur through one ecosystem:

EDR=80%EDR=80\%

This can indicate substantial commercial dependence.

It is an economic indicator, not a legal threshold by itself.

34. Six Key Case Laws

1. Google Android — C-738/22 P (2026)

Core issue

Android involved interconnected markets for:

general search;

mobile operating systems;

Android app stores.

The Court's 2 July 2026 judgment dealt with contractual restrictions, tying, exclusionary effects, exclusive pre-installation payments and restrictions affecting Android forks. (InfoCuria)

Indicator

Tying + exclusivity + ecosystem integration + entry barriers

Lesson

Ecosystem indicators should be assessed together because several restrictions can reinforce one another.

35. 2. Google Shopping — C-48/22 P (2024)

Google favoured its own comparison-shopping service in general search.

The Court of Justice dismissed Google's appeal and upheld the €2.4 billion fine. (InfoCuria)

Indicators

gateway control;

self-preferencing;

leveraging;

traffic dependence;

rival foreclosure.

Lesson

Control over a central gateway can affect competition in adjacent markets.

36. 3. Microsoft v Commission — T-201/04 (2007)

The case concerned Microsoft's refusal to supply interoperability information and its tying of Windows with Windows Media Player.

The General Court essentially upheld the Commission's infringement findings. (InfoCuria)

Indicators

interoperability;

technical dependency;

tying;

ecosystem closure.

Lesson

Technical compatibility can be a major indicator of ecosystem contestability.

37. 4. Alphabet and Others — C-233/23 (2025)

The case concerned Google's Android Auto platform and access by a third-party electric-vehicle charging application.

The Court clarified conditions under which refusal to make a dominant digital platform interoperable with a third-party app may constitute abuse and addressed indispensability, effects, objective justification and relevant downstream markets. (curia)

Indicators

interoperability;

platform dependency;

access;

downstream competition.

Lesson

A digital platform can become a competitive gateway to complementary applications.

38. 5. IMS Health — C-418/01 (2004)

IMS Health involved access to a data structure used for pharmaceutical sales information.

The case developed the exceptional circumstances framework for refusal to license intellectual property.

Indicators

data uniqueness;

replicability;

indispensability;

access barriers.

Lesson

Control over a difficult-to-replicate information structure can become competitively important.

39. 6. Bronner — C-7/97 (1998)

The case involved access to a newspaper home-delivery system.

The Court applied demanding conditions before a dominant firm could be required to provide access to its infrastructure. The modern Court continues to cite Bronner for the proposition that indispensability, absence of alternatives, likely elimination of competition and lack of objective justification are important in the relevant refusal-to-access framework. (InfoCuria)

Indicators

infrastructure dependency;

alternatives;

indispensability;

foreclosure.

Lesson

An important ecosystem infrastructure does not automatically have to be opened to competitors.

40. 7. Ohio v American Express — 585 U.S. 529 (2018)

American Express involved a two-sided payment network.

The Supreme Court treated the merchant and cardholder sides as interconnected for purposes of analysing competitive effects.

Indicators

two-sidedness;

indirect network effects;

cross-side demand;

platform participation.

Lesson

Ecosystem competition may require simultaneous analysis of several connected sides.

41. Ecosystem Indicator Matrix

42. Important Distinction: Indicator ≠ Violation

This is extremely important for examinations.

Example

A company has:

80% market share;

strong network effects;

low churn;

high data concentration.

These are indicators of market power.

They do not automatically establish abuse.

The legal analysis still asks:

What is the relevant market?

Is the undertaking dominant?

What conduct occurred?

Does the conduct have the required object/effect?

Is there foreclosure?

Are there efficiencies or objective justifications?

43. Ecosystem Competition Scorecard

For economic analysis, the following non-legal analytical scorecard can help organise evidence:

This should be used as an analytical framework, not as a legal scoring system.

44. UAE Competition-Law Application

The current UAE federal competition framework is Federal Decree-Law No. 36 of 2023 on the Regulation of Competition.

It addresses:

restrictive agreements;

abuse of dominant position;

economic concentrations.

For an ecosystem case, the indicators above can assist in determining whether an undertaking has significant competitive power and whether particular conduct affects competition.

For example, the analysis could examine:

Dominance indicators

Market share + network effects + entry barriers + switching costs.

Abuse indicators

Tying + discrimination + refusal to transact + technological restrictions + exclusionary pricing.

Concentration indicators

Market overlap + vertical integration + data combination + network effects + foreclosure potential.

The existence of an ecosystem itself is therefore not prohibited; the competition-law question concerns the competitive structure, conduct and effects.

45. Practical Example

Suppose Platform X controls:

70% of online marketplace transactions;

65% of digital payments;

60% of merchant advertising;

55% of logistics services.

It also controls the customer data generated by those services.

Ecosystem indicators

Market concentration: High

Network effect: Strong

Data advantage: Strong

Multi-homing: Low

Switching cost: High

Centrality: High

Vertical integration: High

Cross-market leverage: Potentially significant

Interoperability: Must be investigated

Self-preferencing: Must be investigated

The correct legal conclusion cannot simply be:

“Platform X is unlawful.”

Instead, the evidence should be taken into the relevant dominance, conduct and effects analysis.

46. Ultra-Short Exam Answer

Ecosystem competition indicators are measures used to assess competitive conditions in interconnected markets. They include market share, concentration, network effects, user base, multi-homing, switching costs, interoperability, data concentration, centrality, gateway control, vertical integration, self-preferencing, tying, exclusivity, entry barriers, rival growth and innovation. Cases such as Google Android, Google Shopping, Microsoft, Alphabet/Android Auto, IMS Health, Bronner and Ohio v American Express demonstrate how these indicators can be relevant to digital-platform, infrastructure, data and two-sided-market competition. Importantly, an indicator of ecosystem power is not by itself an infringement; the applicable competition law must still be applied to the undertaking's position, conduct and competitive effects.

47. One-Line Memory Trick

“ECOSYSTEM = M-N-S-I-D-E-C”

M — Market concentration
N — Network effects
S — Switching costs
I — Interoperability
D — Data concentration
E — Entry barriers
C — Cross-market leverage

Final formula

Ecosystem Competition Analysis = Structure + Network Effects + Access + Dependency + Conduct + Effects.