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Strategic anonymity and behavior-based pricing

Author

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  • Stefano Colombo
  • Paolo G. Garella
  • Noriaki Matsushima

Abstract

We analyze behavior-based price discrimination (BBPD) where consumers choose between being identified (e.g., by opting in) or remaining anonymous, as opposed to mandatory opt-in. Opting in provides consumers with benefits but also enables firms to apply history-dependent pricing. Under voluntary opt-in, market segmentation becomes more fragmented compared to standard BBPD. Consumer surplus and social welfare are higher with voluntary opt-in, while firm profits increase under mandatory opt-in. However, if consumers heavily discount the future and firms are forward-looking, these results may reverse entirely. Our result implies that policymakers can ensure that consumers retain control over their data along with encouraging them to adopt a more forward-looking perspective.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Stefano Colombo & Paolo G. Garella & Noriaki Matsushima, 2023. "Strategic anonymity and behavior-based pricing," ISER Discussion Paper 1219, Institute of Social and Economic Research, The University of Osaka.
  • Handle: RePEc:dpr:wpaper:1219
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    References listed on IDEAS

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    1. 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.
    2. Rosa-Branca Esteves, 2014. "Price Discrimination with Private and Imperfect Information," Scandinavian Journal of Economics, Wiley Blackwell, vol. 116(3), pages 766-796, July.
    3. Yongmin Chen, 1997. "Paying Customers to Switch," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 6(4), pages 877-897, December.
    4. Didier Laussel & Joana Resende, 2022. "When Is Product Personalization Profit-Enhancing? A Behavior-Based Discrimination Model," Management Science, INFORMS, vol. 68(12), pages 8872-8888, December.
    5. Drew Fudenberg & Jean Tirole, 2000. "Customer Poaching and Brand Switching," RAND Journal of Economics, The RAND Corporation, vol. 31(4), pages 634-657, Winter.
    6. Jiajia Cong & Noriaki Matsushima, 2023. "The effects of personal data management on competition and welfare," ISER Discussion Paper 1201, Institute of Social and Economic Research, The University of Osaka.
    7. Ramon Casadesus-Masanell & Andres Hervas-Drane, 2015. "Competing with Privacy," Management Science, INFORMS, vol. 61(1), pages 229-246, January.
    8. Chongwoo Choe & Stephen King & Noriaki Matsushima, 2018. "Pricing with Cookies: Behavior-Based Price Discrimination and Spatial Competition," Management Science, INFORMS, vol. 64(12), pages 5669-5687, December.
    9. Conti, Chiara & Reverberi, Pierfrancesco, 2021. "Price discrimination and product quality under opt-in privacy regulation," Information Economics and Policy, Elsevier, vol. 55(C).
    10. J. Miguel Villas-Boas, 2004. "Price Cycles in Markets with Customer Recognition," RAND Journal of Economics, The RAND Corporation, vol. 35(3), pages 486-501, Autumn.
    11. J. Miguel Villas-Boas, 1999. "Dynamic Competition with Customer Recognition," RAND Journal of Economics, The RAND Corporation, vol. 30(4), pages 604-631, Winter.
    12. Stefano Colombo, 2016. "Imperfect Behavior‐Based Price Discrimination," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 25(3), pages 563-583, September.
    13. Caminal, Ramon & Matutes, Carmen, 1990. "Endogenous switching costs in a duopoly model," International Journal of Industrial Organization, Elsevier, vol. 8(3), pages 353-373, September.
    14. Vincent Conitzer & Curtis R. Taylor & Liad Wagman, 2012. "Hide and Seek: Costly Consumer Privacy in a Market with Repeat Purchases," Marketing Science, INFORMS, vol. 31(2), pages 277-292, March.
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