Presentation 11: Exercise of platform owner power

Power relations in digital platform ecosystems & government regulation of platforms

How platform owner realise rent extraction as a different perspective on Subsidization?

• Rent extraction = platform owner uses its gatekeeper position to capture a larger share of the value created by others

• Platforms often subsidize one side of the market to attract users

  • Once these users are locked in, the platform can monetize access to them by charging the other market side

  • e.g. Subsidize Side A (e.g. Riders) → More riders join → Strong network effects → Market dominance → Gatekeeper position (e.g. controls access to riders for drivers) → Complementors become dependent (e.g. drivers can not leave because riders are here) → Platform increases comissions & fees → rent extraction

→ rent extraction through pricing power enabled by gatekeeping

→ Subsidization as a mechanism to enable rent extraction

What is the relationship between subsidization and rent extraction?

• occur at different stages of platform evolution

• Subsidization → Growth → Network effects → Market dominance → Gatekeeper → Rent extraction

Explain how Uber uses pricing-based Rent extraction.

Lower rider prices (subsidized demand) → Large rider base → Drivers depend on Uber to reach customers → Uber controls access to riders → Monetization through pricing

Once riders are locked in Uber monetizes access through:

• Higher commissions

• Booking/service fees

• Surge pricing

→ Uber's pricing power comes from controlling access to a large, locked-in customer base—not simply from providing the matching service

What are examples to realise rent extraction?

• Pay for visibility and attention

• Self-Preferencing

• higher commissions, API fees or advertising fees

• mandatory (verpflichtende) payment systems

Define Walled Gardens. What are characteristics of it?

= A closed digital ecosystem where users are encouraged (ermutigt) or required to stay within a platform's environment

Characteristics:

• Strong control over access, distribution, and interactions

• Reliance (Abhängigkeit, Verlass) on proprietary (firmeneigene) standards, technologies, and services

• Limited interoperability with competing platforms

• High switching costs can increase user dependency

→ look users in, limit competition and strengthen platform power

What are typical mechanisms of Walled Gardens?

• Proprietary (firmeneigene) operating systems and standards

• Restricted APIs and developer rules

• Exclusive app stores and payment systems

• Tight integration of hardware, software, and services

What Walled Gardens often requires?

Forced Bundling:

• Bundling = The practice of selling or providing multiple products or services together

• Forced Bundling = Users or business partners may need to accept one product to get access to another

• Example: Microsoft Teams being bundled with Microsoft 365 subscriptions

  • Companies that only wanted Office also had to get Teams

  • harder for competitors like Slack because customers already have Teams

→ Forced Bundling keep user inside the ecosystem (best compatibility, high switching cost)

Explain Apple as a Walled Garden.

• Controlled App Distribution - iOS apps are generally distributed through the App Store

• Proprietary Ecosystem - Apple devices work most effectively with Apple services such as iCloud, AirDrop, FaceTime, and iMessage

• Limited Interoperability - Some services and functionalities work better within Apple's ecosystem than with competing platforms

• Vertical Integration - Apple designs hardware, operating systems, application frameworks, and many core services, creating a highly integrated user experience

• Switching Costs - Moving to another ecosystem may require effort and data migration

→ Apple focused in the AppStore on privacy and security to produce a trusted environment for users and complementors through a higly controlled environment → Apple as a Walled Garden

How do platforms use walled gardens?

Platforms use Walled garden to:

• increase user lock-in

• reduce switching

• control access to complements

• capture more value

• maintain quality/security

• strengthen their gatekeeper position

What are the three potential/common (häufige) misuse (Misbrauch) of Platform Power?

1. Platform Governance Abuse (Missbrauch) → Gatekeeping Misuse

2. Misuse over ranking and visibility

3. Data misuse → Data asymmetry Misuse

Explain the Platform Governance Abuse of platform power.

• Platform owners control access to the ecosystem and may selectively exclude competitors or restrict complementor participation through governance mechanisms such as account suspensions and API restrictions = Uses rules to exclude competitors

• e.g. Apple: Developer → Apple reviews app → App rejected (ablehnen) → No access to iPhone user

Explain the misuse of platform control over Ranking and visibility.

• Algorithmic recommendation and search systems determine which products or services are visible to users, meaning small ranking changes can dramatically change market outcomes = Uses recommendation systems to favor own products

• e.g. Content providers (netflix + external Studios) → Netflix recommendation Algorithms → Netflix originals appear first on homepage → Higher visibility → More views

Explain the data misuse of platform power.

• Platform owners collect ecosystem-wide data while complementors have limited visibility, enabling the platform to identify successful products and enter these markets = Uses ecosystem-wide data to compete against complementors

• e.g. Independent Seller → Develops successfull product → Sales data generated on Amazon Marketplace → Amazon observes market demand → Amazon launches similar product (Amazon Basic) → Amazon gives own product featured placement

What critic exist of platform power?

• Platforms should be managed by government because they have monopoly power and broad social influence

• Misuse of Platform government → e.g. banning accounts could seem as the attack on the freedom of speech, to silence someone

• Manipulating ranking or recommendation algorithms for political or strategic purpose → e.g. higher visibility of Republican content