skip to main content
10.1145/3391403.3399493acmconferencesArticle/Chapter ViewAbstractPublication PagesecConference Proceedingsconference-collections
abstract

Dynamic Privacy Choices

Published:13 July 2020Publication History

ABSTRACT

I study a dynamic model of consumer privacy and platform data collection. In each period, consumers choose their level of platform activity. Greater activity generates more precise information about the consumer, thereby increasing platform profits. Although consumers value privacy, a platform is able to collect much information by gradually lowering the level of privacy protection. In the long-run, consumers become "addicted" to the platform, whereby they lose privacy and receive low payoffs, but continue to choose high activity levels. Competition is unhelpful because consumers have a higher incentive to use a platform to which they have lower privacy.

References

  1. Daron Acemoglu, Ali Makhdoumi, Azarakhsh Malekian, and Asuman Ozdaglar. 2019. Too Much Data: Prices and Inefficiencies in Data Markets. Working Paper 26296. National Bureau of Economic Research.Google ScholarGoogle Scholar
  2. Dirk Bergemann, Alessandro Bonatti, and Tan Gan. 2019. The Economics of Social Data. Cowles foundation discussion paper 2203. Yale University.Google ScholarGoogle Scholar
  3. Jay Pil Choi, Doh-Shin Jeon, and Byung-Cheol Kim. 2019. Privacy and personal data collection with information externalities. Journal of Public Economics, Vol. 173 (2019), 113--124.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Dynamic Privacy Choices

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      EC '20: Proceedings of the 21st ACM Conference on Economics and Computation
      July 2020
      937 pages
      ISBN:9781450379755
      DOI:10.1145/3391403

      Copyright © 2020 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 13 July 2020

      Check for updates

      Qualifiers

      • abstract

      Acceptance Rates

      Overall Acceptance Rate323of1,218submissions,27%

      Upcoming Conference

      EC '24
      The 25th ACM Conference on Economics and Computation
      July 8 - 11, 2024
      New Haven , CT , USA

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader