Privacy and Platform Competition

Arbeitspapier

We analyze platform competition where user data is collected to improve adtargeting. Considering that users incur privacy costs, we show that the equilibrium level of data provision is distorted and can be inefficiently high or low: if overall competition is weak or if targeting benefits are low, too much private data is collected, and vice-versa. Further, we find that softer competition on either market side leads to more data collection, which implies substitutability between competition policy measures on both market sides. Moreover, if platforms engage in two-sided pricing, data provision is efficient.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Discussion Paper ; No. 67

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Market Structure, Pricing, and Design: Oligopoly and Other Forms of Market Imperfection ; Oligopoly and Other Imperfect Markets ; Antitrust Issues and Policies: General ; Information and Internet Services; Computer Software
• Thema: ad targeting ; platform competition ; privacy ; user data

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Dimakopoulos, Philipp ; Sudaric, Slobodan
• Ereignis: Veröffentlichung
• (wer): Ludwig-Maximilians-Universität München und Humboldt-Universität zu Berlin, Collaborative Research Center Transregio 190 - Rationality and Competition
• (wo): München und Berlin
• (wann): 2018

Weitere Informationen

• Handle: http://hdl.handle.net/10419/185737
• Letzte Aktualisierung: 10.03.2025, 11:42 MEZ