IDEAS home Printed from https://ideas.repec.org/a/eee/iepoli/v60y2022ics0167624522000270.html
   My bibliography  Save this article

Carpe Data: Protecting online privacy with naive users

Author

Listed:
  • Abrardi, Laura
  • Cambini, Carlo

Abstract

In this paper, we study the optimal design of incentives to induce a digital platform to limit the extraction of data from users, whose privacy loss is further aggravated by their naive use of the platform. We show that caps on the amount of data collected can induce the optimal data-saving effort by the platform. If the platform’s effort is not observable, a menu of data caps should be provided and it entails a higher (lower) loss of privacy for less (more) naive users, relative to the first best. We also show that compensating users for their data can efficiently incentivize effort, but might increase the privacy loss of more naive users.

Suggested Citation

  • Abrardi, Laura & Cambini, Carlo, 2022. "Carpe Data: Protecting online privacy with naive users," Information Economics and Policy, Elsevier, vol. 60(C).
    • Handle: RePEc:eee:iepoli:v:60:y:2022:i:c:s0167624522000270
    DOI: 10.1016/j.infoecopol.2022.100988
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167624522000270
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.infoecopol.2022.100988?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jullien, Bruno & Lefouili, Yassine & Riordan, Michael, 2018. "Privacy Protection, Security, and Consumer Retention," TSE Working Papers 18-947, Toulouse School of Economics (TSE), revised Jun 2020.
    2. Rodrigo Montes & Wilfried Sand-Zantman & Tommaso Valletti, 2019. "The Value of Personal Information in Online Markets with Endogenous Privacy," Management Science, INFORMS, vol. 65(3), pages 1342-1362, March.
    3. Marc Bourreau & Bernard Caillaud & Romain De Nijs, 2018. "Taxation of a digital monopoly platform," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 20(1), pages 40-51, February.
    4. Francis Bloch & Gabrielle Demange, 2018. "Taxation and privacy protection on Internet platforms," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 20(1), pages 52-66, February.
    5. Baron, David P & Myerson, Roger B, 1982. "Regulating a Monopolist with Unknown Costs," Econometrica, Econometric Society, vol. 50(4), pages 911-930, July.
    6. Alessandro Acquisti & Hal R. Varian, 2005. "Conditioning Prices on Purchase History," Marketing Science, INFORMS, vol. 24(3), pages 367-381, May.
    7. Mark Armstrong & David E.M. Sappington, 2006. "Regulation, Competition and Liberalization," Journal of Economic Literature, American Economic Association, vol. 44(2), pages 325-366, June.
    8. Choi, Jay Pil & Jeon, Doh-Shin & Kim, Byung-Cheol, 2019. "Privacy and personal data collection with information externalities," Journal of Public Economics, Elsevier, vol. 173(C), pages 113-124.
    9. Shota Ichihashi, 2020. "Online Privacy and Information Disclosure by Consumers," American Economic Review, American Economic Association, vol. 110(2), pages 569-595, February.
    10. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    11. Catherine Tucker, 2018. "Privacy, Algorithms, and Artificial Intelligence," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 423-437, National Bureau of Economic Research, Inc.
    12. Clavorà Braulin, Francesco & Valletti, Tommaso, 2016. "Selling customer information to competing firms," Economics Letters, Elsevier, vol. 149(C), pages 10-14.
    13. Iossa, Elisabetta & Stroffolini, Francesca, 2005. "Price cap regulation, revenue sharing and information acquisition," Information Economics and Policy, Elsevier, vol. 17(2), pages 217-230, March.
    14. Alessandro Acquisti & Curtis Taylor & Liad Wagman, 2016. "The Economics of Privacy," Journal of Economic Literature, American Economic Association, vol. 54(2), pages 442-492, June.
    15. Jentzsch, Nicola, 2016. "State-of-the-Art of the Economics of Cyber-Security and Privacy," EconStor Research Reports 126223, ZBW - Leibniz Information Centre for Economics.
    16. Curtis R. Taylor, 2004. "Consumer Privacy and the Market for Customer Information," RAND Journal of Economics, The RAND Corporation, vol. 35(4), pages 631-650, Winter.
    17. Ramon Casadesus-Masanell & Andres Hervas-Drane, 2015. "Competing with Privacy," Management Science, INFORMS, vol. 61(1), pages 229-246, January.
    18. Laffont, Jean-Jacques, 1994. "The New Economics of Regulation Ten Years After," Econometrica, Econometric Society, vol. 62(3), pages 507-537, May.
    19. Michael R. Baye & David E. M. Sappington, 2020. "Revealing transactions data to third parties: Implications of privacy regimes for welfare in online markets," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 29(2), pages 260-275, April.
    20. David Laibson, 1997. "Golden Eggs and Hyperbolic Discounting," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(2), pages 443-478.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yassine Lefouili & Leonardo Madio & Ying Lei Toh, 2024. "Privacy Regulation and Quality‐Enhancing Innovation," Journal of Industrial Economics, Wiley Blackwell, vol. 72(2), pages 662-684, June.
    2. Yassine Lefouili & Leonardo Madio & Ying Lei Toh, 2024. "Privacy regulation and quality-enhancing innovation," Post-Print hal-04774302, HAL.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Flavio Pino, 2022. "The microeconomics of data – a survey," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(3), pages 635-665, September.
    2. Didier Laussel & Ngo Van Long & Joana Resende, 2023. "Profit Effects of Consumers’ Identity Management: A Dynamic Model," Management Science, INFORMS, vol. 69(6), pages 3602-3615, June.
    3. Dengler, Sebastian & Prüfer, Jens, 2021. "Consumers' privacy choices in the era of big data," Games and Economic Behavior, Elsevier, vol. 130(C), pages 499-520.
    4. Yiquan Gu & Leonardo Madio & Carlo Reggiani, 2022. "Data brokers co-opetition [The impact of big data on firm performance: an empirical investigation]," Oxford Economic Papers, Oxford University Press, vol. 74(3), pages 820-839.
    5. Shuaicheng Liu, 2024. "Privacy regulation in asymmetric environments," Journal of Regulatory Economics, Springer, vol. 66(2), pages 157-173, December.
    6. Alessandro Bonatti, 2023. "The Platform Dimension of Digital Privacy," NBER Chapters, in: The Economics of Privacy, National Bureau of Economic Research, Inc.
    7. Dengler, Sebastian & Prüfer, Jens, 2021. "Consumers' privacy choices in the era of big data," Games and Economic Behavior, Elsevier, vol. 130(C), pages 499-520.
    8. Conti, Chiara & Reverberi, Pierfrancesco, 2021. "Price discrimination and product quality under opt-in privacy regulation," Information Economics and Policy, Elsevier, vol. 55(C).
    9. Loertscher, Simon & Marx, Leslie M., 2020. "Digital monopolies: Privacy protection or price regulation?," International Journal of Industrial Organization, Elsevier, vol. 71(C).
    10. Daniel Krähmer & Roland Strausz, 2023. "Optimal Nonlinear Pricing with Data-Sensitive Consumers," American Economic Journal: Microeconomics, American Economic Association, vol. 15(2), pages 80-108, May.
    11. Jiadong Gu, 2024. "Data Trade and Consumer Privacy," Papers 2406.12457, arXiv.org, revised Jul 2024.
    12. Rodrigo Montes & Wilfried Sand-Zantman & Tommaso Valletti, 2019. "The Value of Personal Information in Online Markets with Endogenous Privacy," Management Science, INFORMS, vol. 65(3), pages 1342-1362, March.
    13. Florian Morath & Johannes Münster, 2018. "Online Shopping and Platform Design with Ex Ante Registration Requirements," Management Science, INFORMS, vol. 64(1), pages 360-380, January.
    14. Choi, Jay Pil & Jeon, Doh-Shin & Kim, Byung-Cheol, 2019. "Privacy and personal data collection with information externalities," Journal of Public Economics, Elsevier, vol. 173(C), pages 113-124.
    15. Jin, Ginger Zhe & Wagman, Liad, 2021. "Big data at the crossroads of antitrust and consumer protection," Information Economics and Policy, Elsevier, vol. 54(C).
    16. Michael Kummer & Patrick Schulte, 2019. "When Private Information Settles the Bill: Money and Privacy in Google’s Market for Smartphone Applications," Management Science, INFORMS, vol. 65(8), pages 3470-3494, August.
    17. Jean-Marc Zogheib & Marc Bourreau, 2021. "Privacy, Competition, and Multi-Homing," EconomiX Working Papers 2021-15, University of Paris Nanterre, EconomiX.
    18. Morlok, Tina & Matt, Christian & Hess, Thomas, 2017. "Privatheitsforschung in den Wirtschaftswissenschaften: Entwicklung, Stand und Perspektiven," Working Papers 1/2017, University of Munich, Munich School of Management, Institute for Information Systems and New Media.
    19. Masuyama, Ryo, 2023. "Endogenous privacy and heterogeneous price sensitivity," MPRA Paper 117316, University Library of Munich, Germany.
    20. Bonatti, Alessandro & Argenziano, Rossella, 2020. "Information Revelation and Privacy Protection," CEPR Discussion Papers 15203, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    Data extraction; Incentives; Users’ naivety; Privacy;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D86 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Economics of Contract Law
    • L12 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Monopoly; Monopolization Strategies
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:iepoli:v:60:y:2022:i:c:s0167624522000270. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/505549 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.