2nd Week

• Teasers

• Freemium

• two sided pricing

• exchange data for advertising

• Predatory pricing

mixes “free” + “premium”

• Examples: Duolingo + YouTube

• Attract a large user base quickly

• Premium Version is paid

Spotify Example:

• Free: Advertising, no downloads, “less sound quality”

• Premium: all advantages

free viewing to see what (great) content is there, but access only with subscription.

Multiple functions:

• create trust for experience goods

• increase willingness to pay

• A “digital showroom”

• Problem: Competition with multiple competitors offering subscriptions

Business model is old

• organized markets where sellers and buyers meet

• intermediation: real estate agents, auctions, shopping

The platform:

• provides a mechanism for interaction

• Catalyzez “cross-platform externalities” betwenn parties

• derives revenues from memberhsip or transaction

• Auction sites: ebay

• Seller hosting: amazon

• Payments: Paypal

• Transport: Uber, Bolt

Platform offer free games:

• sell display advertising

• comissions on in-game sales

• Example: Roblox

The secret of a platform business is to find the right way to create and monetize the maximum amount of cross-network externalities

• Users on side A benefit from more users on side B and vice versa

• needs to weigh entry and participation incebtives

Often the two sides areasymetric:

• one side pays very little (difficult to attract) other a lot (TV)

• Examples: Shopping malls, amazon, credit & debit cards, Advertising

• Much bigger “bang for the buck”

• Spend only on targets with likely response

• Tailored content and pricing [more later]

• Possibility of immediate measurement of response

-> Google and Facebook have won more than 30% of the

US advertising market

more usage and more data <-> more accumulated data

Advantages:

• more usage -> better personalization and innovation

Disadvantags:

• forecloses market entry for innovators and competitors

• Facebook collects user data to sell targeted advertising (90% of its revenue)

• It also uses the data to sell targeting of content

• Also sells data to aggregators producing statistics on user behaviour, such as political preferences, personality type, personal economy, and attitudes

There is an additional, less visible set of firms in the “plumbing” of the data economy, the brokers

• Collect and match data on pretty much everybody, buy and sell data

Foreclosure: -> Business Strateg (BS)y, to eliminate the possibility of entry, enacted through unfair means

• exclusive contracts

• control over excessive pricing of inputs

• scale and network effects

Predatory pricing: -> BS eliminate competitors by charging low prices

• target firm gives up when it can no longer support the losses

• predator makes losses as well, recoup them through higher profits later

Foreclosure and predation are particulary simple with DS

• zero MC -> predadtion does not cause additional losses

• High FC and low margins discourage entry

• accumulation of data and infro lead increasing knowledge and quality advantage even more difficult to surpass

Example: Miceosft and netsapce, browser war

• 3/4 of combined market value from Facebook an Google comes from user data and its mining

• Aggregation and analysis of data create

  large value for firms, consumers, and societies

• non-linear value -> each new piece of data adds more than just its own small bit of value

• Data about conusmer and business choices and characteristics are essential inputs for digi goods

• demands, trends can be better forcasted, products better designes, services personalized

• Data on different consumers are complements

  -> It is the joint processing of data of millions of transactions and observations that creates value

• Algorithms use this data (Likes, follows, shared) to maximize engagement – keeping you watching or scrolling longer

• Can become addictive – designed to hold attention

• Hurts competitors – data advantage is hard to match

• Reduces privacy – protecting privacy cuts into profits

  
  

  
  

  
  

Social Media Addiction reduction technology

• time on SM reduced to 30 minutes

• ban on infinite scroll and autoplay of videos

Reasons:

• studies: more time on SM more loneliness and levels of depression and anxiety

• comparuson lead to low self -esteem, esp. among teenagers

Conflicting objectives:

• Maximum efficiency in information gathering points to ownership by firms

• Protection of consumer rights and privacy points to ownership by individuals

Can data be individually attributed?

• Yes, if names, addresses, actions taken, etc

• No, if patterns derived by machine-learning from individual observations

• Consumer data is hoovered up in huge amounts

• Search, social media and online shopping have become quasi-monopolies

• Data scale effects hinder entry of new competitors

• Start-ups are bought up by the giants, instead of launching IPOs

-> all the issues are realted, and data are the heart of these problems

• The US protects the “right to know” as a form of free speech (1st Amendment)

• Included in the GDPR [see below] as the “right to erasure”

• ePrivacy Directive 2009 -> directive is no law, need to be transposed into law by individual countries

• Purpose: safeguard the right to privacy, as stated in Article 8 of the EU Charter of Fundamental Rights

• Objective: protect against online tracking, personal profiling, unsolicited marketing, and harvesting of personal data without consent

Implementation:

• Limits on usage of data

• explicit consent needed for harvesting data -> cookie banners

Usage of data:

• What data can be used for, e.g. marketing

• How data is handled, i.e. anonymized and protected unless consented

• How and for what purpose data can be shared

• No use of email addresses for unsolicited marketing (“spam”)

Users can demand:

• Access and insight

• Rectification

• Deletion of their data

• Defines principles for data processing and storage (all data – not only digital!)

• Type and amount of personal data that may be processed depend on the (legal) reason for processing and the intended use.

1. Lawfulness, fairness and transparency

2. Purpose limitation, also afterwards not be used for different purpose

3. Data minimization

4. Accuracy

5. storage limitation

6. Integrity and confidentiality

-> applies to all firms that do business with users in the EU

Similar to the GDPR, looser on some points:

• No requirement of “legal basis” for data collection

• No organizational requirements for data confidentiality

• No removal of public personal information from the internet

Secures new privacy rights for Cali consumers, including:

• The right to know about the personal information a business collects about them and how it is used and shared;

• The right to delete personal information collected from them (with some exceptions);

• The right to opt-out of the sale of their personal information; and

• The right to non-discrimination for exercising their CCPA rights.”

Stronger than GDPR:

• Wider definition of “personal information”

• Explicit prohibition of discrimination as a function of consent

• Explicit “do not sell data” option on consent banners

• Each and every website needs to ask every user repeatedly for consent

• Websites have an incentive to present consent banners featuring only an “OK” button, instead of providing users an opportunity to choose

• Consent fatigue: users click “ok” just to get quickly to web content

-> Result: Websites still collect personal information unhindered, while users have the hassle of

all those banners and pop-ups getting in their way

• Transposes GDPR and EU e-Privacy Directive (2002) into German law.

• Regulates data & privacy protection in telecoms and electronic media.

• Plans for a new, improved consent system for storing/accessing data (future reform).

• Introduces rules on “digital inheritance” → relatives can access digital accounts of deceased persons.

• Strengthens independent data protection authority (Datenschutz-Aufsichtsbehörde) with power to impose fines.

• Telecom regulator applies TTDSG when no personal data is involved.

Main points:

• Recognizes that firms can be economically dependent on large platforms (even if the platform isn’t a monopoly).

• Defines “relative market power” → when a company controls vital data or services that smaller firms must access.

• Expands the essential facility doctrine → refusing data access can count as unfair hindrance.

• Applies even when data are not traded commercially.

• Example: Amazon vs. marketplace sellers → sellers rely on Amazon’s platform and data to reach customers.

-> Prevent big digital platforms from blocking competitors’ access to critical data needed for fair competition.