Competition Law and Behavioural Influence on Market Power

1. Introduction

Behavioural influence in competition law refers to the ability of an undertaking—particularly a firm with substantial market power—to shape how consumers, suppliers, competitors, or business users behave through pricing, defaults, rankings, interface design, recommendations, personalised advertising, loyalty mechanisms, bundling, algorithms, or other forms of choice architecture.

Traditional competition law often assumes that consumers respond rationally to prices and quality. Behavioural economics shows that actual decision-making may be affected by status-quo bias, inertia, loss aversion, framing, salience, anchoring, information overload, default effects and switching costs. These effects become particularly significant in digital markets, where a platform can control the environment in which choices are presented.

The competition-law question is therefore not simply:

“Does the firm have market power?”

It is also:

“Can the firm use that market power to influence behaviour in a way that weakens competitive constraints?”

This is especially relevant to Article 102 TFEU, abuse-of-dominance law, digital-platform regulation, tying, self-preferencing, exclusionary conduct and interoperability.

2. Meaning of Behavioural Influence

Behavioural influence may arise when a firm designs its commercial environment so that consumers or business users are more likely to select one option over another.

Important mechanisms include:

1. Default effects – users tend to retain pre-selected options.
2. Status-quo bias – users disproportionately remain with an existing service.
3. Inertia – users do not switch despite technically available alternatives.
4. Salience – prominently displayed options receive disproportionate attention.
5. Framing effects – presentation of information affects decisions.
6. Loss aversion – consumers may avoid switching because they perceive potential losses.
7. Choice overload – excessive complexity may discourage comparison.
8. Personalisation – firms use behavioural data to tailor offers and rankings.
9. Switching costs – technical, financial or psychological costs discourage movement to rivals.
10. Social or network effects – the popularity of a platform itself encourages continued use.

The CMA has specifically recognised that online choice architecture can influence consumer choices and, indirectly, the competitive conditions faced by businesses.

3. Relationship Between Behavioural Influence and Market Power

Behavioural influence does not automatically constitute an antitrust violation.

A firm may legitimately use:

• attractive product design;
• recommendations;
• discounts;
• loyalty programmes;
• personalised services;
• convenient defaults;
• advertising;
• product bundling in appropriate circumstances.

The competition concern arises where behavioural influence is combined with market power and is capable of weakening competition.

The basic relationship can be represented as:

Market Power → Control over Choice Architecture → Behavioural Influence → Reduced Switching/Reduced Visibility of Rivals → Competitor Foreclosure → Greater Entrenchment of Market Power

This can create a feedback loop:

Market Power → Behavioural Steering → More Users → Stronger Network Effects/Data Advantages → Higher Entry Barriers → Greater Market Power

Thus, behavioural influence may help a dominant firm maintain or extend an existing position.

4. Behavioural Economics and the Traditional Competition Model

Traditional economic models frequently assume that consumers:

• possess adequate information;
• compare alternatives;
• respond to price and quality;
• switch when another product is superior;
• punish firms that provide inferior products.

Behavioural economics qualifies these assumptions.

For example, suppose:

• Search Engine A is pre-installed;
• Search Engine B is technically available;
• B provides a potentially attractive alternative.

Under a perfectly rational model, users might simply switch to B.

But if users exhibit status-quo bias, many may continue using A merely because it is already installed.

Consequently, the incumbent may retain market share not solely because of superior performance but partly because of the way the choice is presented.

Recent scholarship identifies precisely this connection between behavioural economics, Article 102 TFEU and digital-platform regulation.

5. Behavioural Influence as a Source of Market Power

Behavioural influence can strengthen market power in several ways.

A. Increasing customer retention

Defaults and inertia may make customers less likely to switch.

B. Raising effective switching costs

Even when formal switching costs are zero, behavioural friction can make switching less attractive.

C. Reducing competitive visibility

A platform controlling search rankings or recommendations can make competing products less salient.

D. Leveraging dominance into adjacent markets

A firm dominant in one market can steer users towards its own product in another market.

E. Creating tipping effects

Behaviourally reinforced network effects can cause users and suppliers to converge on one platform.

F. Increasing entry barriers

New entrants may struggle to attract users when the incumbent controls defaults, rankings and access to data.

6. Behavioural Influence and Abuse of Dominance

Under Article 102 TFEU, dominant firms are prohibited from abusing their dominant position. The provision addresses exclusionary conduct that can exclude competitors and exploit market power.

Behavioural influence can therefore become relevant to questions such as:

• Is the undertaking dominant?
• What is the relevant market?
• Does the conduct make rival products less visible?
• Does it reduce switching?
• Does it exploit consumer inertia?
• Does it foreclose competitors?
• Does it leverage dominance into another market?
• Are the effects sufficiently substantial to affect competition?
• Can the conduct be objectively justified?

7. Major Forms of Behavioural Influence

7.1 Default Bias

A consumer frequently accepts a pre-selected option rather than actively choosing an alternative.

This becomes competition-sensitive where a dominant undertaking:

• pre-installs its own product;
• makes its own service the default;
• makes changing the default difficult;
• places alternatives behind additional steps.

The Google Android litigation is a major illustration.

7.2 Self-Preferencing

A platform can manipulate rankings or presentation to make its own products more visible.

The behavioural mechanism is salience.

If consumers disproportionately select prominently displayed results, then preferential placement may influence competition even when rival products technically remain available.

7.3 Tying and Bundling

Bundling can influence consumer behaviour by making the bundled product the natural or convenient choice.

Behavioural economics is particularly relevant where consumers are reluctant to undertake the effort necessary to obtain alternatives separately.

7.4 Loyalty and Switching Costs

A firm may structure its commercial environment so that leaving becomes difficult.

Examples include:

• accumulated loyalty benefits;
• technical incompatibility;
• loss of data;
• loss of personalised recommendations;
• contractual commitments;
• ecosystem-specific purchases.

7.5 Personalised Behavioural Steering

Data can allow firms to identify:

• likely switchers;
• price-sensitive consumers;
• consumers with high switching costs;
• consumers susceptible to particular offers.

Personalisation therefore creates the possibility of individualised market influence.

8. Six Major Case Laws

Case 1: Google Search (Shopping) — European Commission

Google Search (Shopping), Commission Decision of 27 June 2017

This is one of the most important cases concerning behavioural influence and market power.

The Commission found that Google had abused its dominant position in general search by giving prominent positioning to its own comparison-shopping service while competing comparison-shopping services were subject to Google's generic search-ranking mechanisms.

The behavioural dimension concerned salience and ranking.

Users do not necessarily examine every search result rationally. Position, prominence and presentation influence which results receive attention and clicks.

The Commission's analysis therefore connected Google's control over search presentation with the competitive position of comparison-shopping rivals. Subsequent EU litigation largely upheld the Commission's conclusions, with the General Court confirming the central finding of abuse.

Competition-law significance

The case demonstrates:

Dominance in search → control over ranking → behavioural influence → increased traffic to own service → reduced competitive opportunities for rivals.

The CMA similarly identifies Google Shopping as a seminal example of an algorithm being used to favour a platform's own service.

Case 2: Google Android — European Commission / General Court

Google Android, Commission Decision of 18 July 2018

Google required, among other things, manufacturers to pre-install Google Search and the Chrome browser in connection with licensing arrangements for Google's Play Store.

The Commission's reasoning recognised the significance of status-quo bias.

Although users could theoretically download alternative search engines, the practical reality was that many users continued using the pre-installed Google Search.

The behavioural mechanism was therefore:

Pre-installation → default effect/status-quo bias → reduced switching → reinforcement of Google's position.

The General Court subsequently addressed Google's arguments concerning user behaviour and the competitive effects of pre-installation.

Behavioural economics is particularly relevant because a purely theoretical assumption that users always switch to better alternatives would underestimate the competitive importance of defaults.

Case 3: Microsoft — Tying of Windows Media Player

Microsoft Corp. v Commission, Case T-201/04

Microsoft's conduct concerning Windows and Windows Media Player remains an important EU tying case.

The competition issue involved Microsoft's ability to leverage its position in the operating-system market into media-player functionality.

From a behavioural perspective, bundling can reduce the likelihood that consumers will actively search for alternatives because the bundled product is already available and convenient.

The case therefore illustrates how:

Dominance + bundling + consumer convenience/inertia → reduced opportunities for competing products.

The case is important because it predates the contemporary digital-platform debate while providing an early foundation for understanding how control over one technological environment can influence consumer choice in another.

Case 4: Apple — App Store / Anti-Steering

Apple App Store Practices — European Commission

Apple's App Store conduct illustrates a more recent form of behavioural influence.

The competition concern involves restrictions affecting how developers communicate alternative purchasing possibilities to consumers.

Where a platform prevents developers from informing users about cheaper or alternative purchasing options, consumers may not discover those alternatives even though they technically exist.

The behavioural mechanism is therefore:

Information restriction → reduced awareness → reduced comparison → reduced consumer choice → weakened competitive constraint.

The European Commission's Apple proceedings have increasingly focused on the relationship between platform rules, developer access and consumer choice. Recent scholarship specifically identifies Apple's conduct concerning alternative subscription information as an example of competition law becoming concerned with effective rather than merely theoretical choice.

Case 5: Amazon Buy Box — European Commission

Amazon Marketplace — Buy Box Commitments, 2022

The European Commission investigated Amazon's treatment of offers displayed through the Buy Box.

The Buy Box is highly important because the offer prominently presented to consumers can receive substantial commercial attention.

The Commission's concerns included the possibility that Amazon's algorithms favoured its own retail products and offers from sellers using Amazon's logistics services.

The behavioural mechanism involves:

Algorithmic ranking → salience → increased probability of selection → increased sales → stronger platform position.

The case demonstrates that behavioural influence does not require an explicit instruction to consumers.

An algorithm can influence consumer decisions simply by determining which option is most visible.

The relationship between Amazon's conduct and self-preferencing has been identified in contemporary analysis of behavioural economics and EU competition law.

Case 6: Intel — Loyalty Rebates

Intel Corp. v European Commission, Case C-413/14 P

Intel concerned rebates granted to major computer manufacturers and distributor Media-Saturn.

The case is important for behavioural influence because loyalty rebates can affect the incentives of customers to purchase from competing suppliers.

A rebate structure can create an economic and behavioural incentive to remain with the incumbent, particularly where customers perceive losing the rebate as a significant disadvantage.

The Supreme Court of the EU required the Commission to examine the capability of the rebates to foreclose an equally efficient competitor where such analysis was requested and supported by the evidence.

Behavioural relevance

The case demonstrates that competition law may need to examine:

• customer incentives;
• switching;
• effective purchasing choices;
• foreclosure;
• economic inducements.

It is therefore useful for understanding behavioural influence beyond digital interfaces.

9. Additional Important Case: Booking.com

Booking.com and Hotel Online Distribution Restrictions

Competition authorities in Europe have investigated hotel-booking platforms and restrictions involving price parity and similar contractual mechanisms.

The behavioural dimension concerns the platform's ability to influence where consumers search and purchase accommodation.

A platform with substantial traffic can become an important gateway between hotels and consumers.

Once users develop a habit of searching through the same platform, platform familiarity, convenience and network effects can strengthen the platform's market position.

The resulting concern is not merely the contractual restriction itself but whether it contributes to:

• reduced platform competition;
• reduced entry;
• increased dependency of hotels;
• weakened consumer choice.

10. Behavioural Influence and Digital Platforms

Digital markets are particularly susceptible because platforms control:

• interface design;
• ranking;
• recommendation algorithms;
• defaults;
• notifications;
• search results;
• advertising;
• personalised offers;
• data collection;
• payment systems;
• account architecture.

This produces an important distinction.

Traditional market

Consumer preference → product choice → market outcome

Digital platform

Platform design → consumer attention → consumer choice → market outcome

Therefore, competition authorities increasingly examine the architecture through which competition occurs.

The OECD has similarly identified behavioural considerations as relevant to misleading or deceptive choice architecture and its potential exclusionary effects in digital markets.

11. Dark Patterns and Competition Law

Dark patterns are interface designs that manipulate users into making choices they might not otherwise make.

Examples include:

• difficult cancellation procedures;
• pre-selected purchases;
• confusing buttons;
• disguised advertisements;
• repeated prompts;
• countdown pressure;
• misleading hierarchy;
• difficult rejection options.

Not every dark pattern is an antitrust violation.

The competition-law relevance increases where the firm:

1. possesses substantial market power;
2. controls an important gateway;
3. uses the interface to disadvantage rivals;
4. prevents effective switching;
5. increases dependency;
6. protects or extends its dominant position.

Thus:

Consumer manipulation alone ≠ necessarily competition violation

but

Market power + behavioural manipulation + competitive foreclosure = potential competition concern.

12. Behavioural Influence and Network Effects

Network effects can amplify behavioural influence.

Suppose Platform A has many users.

More users attract:

→ more sellers
→ more products
→ more data
→ better recommendations
→ more consumers
→ more sellers.

This produces:

Network Effects → Behavioural Lock-in → Data Advantages → Increased Market Power

A new entrant may offer a better product but still struggle because consumers have already developed habits and social connections around the incumbent.

This is particularly important in:

• social media;
• marketplaces;
• payment platforms;
• app stores;
• operating systems;
• search engines;
• digital advertising;
• cloud ecosystems.

13. Behavioural Influence and Data

Data creates another important dimension.

A dominant undertaking may possess behavioural information concerning:

• browsing;
• purchases;
• searches;
• clicks;
• abandoned transactions;
• switching behaviour;
• location;
• preferences;
• response to prices;
• response to advertising.

This permits increasingly sophisticated behavioural targeting.

The competition concern may arise where the incumbent can use these data advantages to:

• personalise exclusionary offers;
• disadvantage rivals;
• improve its own ranking systems;
• increase switching costs;
• identify emerging competitors;
• strengthen ecosystem dependence.

14. Behavioural Influence and Entry Barriers

Behavioural influence can become an entry barrier.

A new competitor must not merely offer a competitive product.

It may have to overcome:

• user inertia;
• default settings;
• established habits;
• network effects;
• accumulated data;
• reputation;
• ecosystem compatibility;
• switching costs;
• learning costs.

Therefore, an incumbent may retain market power even where a technically viable substitute exists.

This is one reason behavioural analysis can supplement conventional measures such as market shares and price effects.

15. Behavioural Influence and Consumer Welfare

Behavioural influence can affect consumer welfare through:

Price

Consumers may pay more than they otherwise would.

Quality

Reduced competitive pressure may reduce quality or innovation.

Choice

Consumers may face fewer meaningful alternatives.

Privacy

Consumers may accept data practices they would reject under clearer presentation.

Innovation

Rivals may have reduced incentives to innovate if they cannot reach users.

Transaction costs

Consumers may spend additional time or resources overcoming artificial friction.

Consequently, consumer welfare cannot always be assessed solely through headline prices.

16. Behavioural Evidence in Competition Investigations

Competition authorities may consider evidence such as:

• click-through rates;
• conversion rates;
• A/B testing;
• switching rates;
• default retention;
• consumer surveys;
• experiments;
• ranking data;
• internal company documents;
• algorithmic testing;
• customer complaints;
• churn data;
• elasticity estimates;
• evidence of consumer inertia.

Behavioural evidence is particularly valuable where the alleged harm depends upon how consumers actually behave, rather than how a theoretical rational consumer would behave.

The CMA has specifically encouraged examination of online choice architecture and its effects on both consumer and competitive outcomes.

17. Behavioural Influence and the Digital Markets Act

The EU Digital Markets Act (DMA) demonstrates the movement from traditional ex-post antitrust towards ex-ante regulation of certain gatekeepers.

Several DMA obligations concern how users are presented with choices and how gatekeepers structure their platforms.

Behavioural economics has therefore influenced not only individual competition cases but also the design of digital-market regulation.

The underlying regulatory concern is that where a platform controls an essential digital gateway, apparently small design choices can have large cumulative competitive consequences.

18. Legal Tests for Behavioural Influence

A competition authority should generally examine the following sequence:

Step 1 — Define the relevant market

Determine the product, geographic and temporal dimensions.

Step 2 — Establish market power

Consider:

• market share;
• barriers to entry;
• network effects;
• economies of scale;
• data advantages;
• switching costs;
• countervailing buyer power.

Step 3 — Identify behavioural mechanism

Determine whether the conduct relies upon:

• default bias;
• inertia;
• salience;
• framing;
• loyalty;
• switching costs;
• personalised steering.

Step 4 — Establish causal relationship

Ask whether the behavioural mechanism actually affects consumer or business-user decisions.

Step 5 — Assess competitive effects

Determine whether rivals are:

• foreclosed;
• disadvantaged;
• denied visibility;
• prevented from entering;
• deprived of customers.

Step 6 — Examine duration and scale

A minor behavioural effect may have significant consequences when repeated millions of times.

Step 7 — Consider efficiencies and justification

The firm should have an opportunity to demonstrate legitimate reasons for the conduct.

19. Behavioural Influence vs Legitimate Competition

It is essential not to treat all behavioural influence as unlawful.

Legitimate competition may include:

• attractive user interfaces;
• genuine product recommendations;
• loyalty rewards;
• discounts;
• personalised services;
• better defaults;
• innovation;
• convenience.

Potentially problematic conduct may include:

• discriminatory ranking;
• artificial switching barriers;
• exclusionary defaults;
• tying used to leverage dominance;
• self-preferencing;
• deceptive choice architecture;
• restrictions on alternative purchasing information;
• algorithmic discrimination against rivals.

The crucial question is competitive effect, not merely the existence of behavioural influence.

20. Six-Case Comparative Table

The Google Shopping and Android decisions are particularly important because behavioural economics provides a framework for understanding why theoretical availability of alternatives does not necessarily produce effective competitive constraints.

21. Key Legal Principles

The following principles emerge:

Principle 1

Market power makes behavioural influence more significant.

Principle 2

Theoretical consumer choice is not necessarily effective consumer choice.

Principle 3

Defaults and rankings can have competitive consequences.

Principle 4

Behavioural influence can reinforce network effects and switching costs.

Principle 5

Self-preferencing may exploit behavioural responses to salience.

Principle 6

Tying may exploit consumer inertia and convenience.

Principle 7

Digital platforms can influence competition by controlling choice architecture.

Principle 8

Behavioural evidence should be supported by empirical evidence rather than assumptions about consumer irrationality.

This last point is important: behavioural economics should not mean assuming that consumers are irrational in every situation. Contemporary scholarship emphasises that behavioural effects are context-dependent and should be established through evidence.

22. Conclusion

Behavioural influence has become an increasingly important dimension of market power analysis, particularly in digital markets.

Traditional competition law asks whether a firm possesses market power and whether its conduct harms competition. Behavioural analysis adds a further question:

How does the firm's control over the environment of choice affect the actual behaviour of consumers and business users?

The most important mechanisms are defaults, status-quo bias, inertia, salience, ranking, loyalty incentives, switching costs, personalisation and network effects.

The cases involving Google Shopping, Google Android, Microsoft, Apple, Amazon and Intel demonstrate different ways in which economic power can interact with behavioural responses.

The broader legal development is therefore moving from a conception of competition based solely upon prices and formal availability of alternatives toward a more sophisticated assessment of effective choice, consumer behaviour, platform design and competitive foreclosure. At the same time, behavioural evidence must remain empirically grounded so that competition law does not simply assume that consumers behave irrationally.

In short:

Market Power + Control of Choice Architecture + Behavioural Influence + Competitive Foreclosure = Potential Abuse of Market Power

This framework is particularly important for digital platforms, search engines, app stores, online marketplaces, fintech, AI platforms, advertising technology and other data-intensiv