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Review of Industrial Organization

, Volume 52, Issue 3, pp 429–450 | Cite as

Sharing Audience Data: Strategic Participation in Behavioral Advertising Networks

  • Steven Schmeiser
Article

Abstract

I consider the incentives of special interest websites to participate in behavioral advertising intermediaries. Participation in the intermediary reveals valuable audience data and allows the intermediary to use those data to target the site’s audience on general interest websites—thus expanding the supply of impressions and decreasing average revenue per impression. I explore monopoly and duopoly settings and highlight the trade-off between sharing audience data and displaying higher-value ads, as well as the strategic interaction between sites serving the same advertising market. The model generates empirical predictions about the choice of intermediary technologies within advertising markets. I also find that higher concentration among special interest websites benefits consumer privacy.

Keywords

Online advertising Online privacy Behavioral advertising 

Notes

Acknowledgements

This paper benefited greatly from discussions with Lou Silversin and comments by the editor and anonymous referees.

References

  1. Athey, S., Calvano, E., & Gans, J. (2014). The impact of the internet on advertising markets for news media, Working paper. National Bureau of Economic Research.Google Scholar
  2. Athey, S., & Gans, J. S. (2010). The impact of targeting technology on advertising markets and media competition. The American Economic Review, 100(2), 608–613.CrossRefGoogle Scholar
  3. Bergemann, D., & Bonatti, A. (2011). Targeting in advertising markets: Implications for offline versus online media. The Rand Journal of Economics, 42(3), 417–443.CrossRefGoogle Scholar
  4. Bergemann, D., & Bonatti, A. (2015). Selling cookies. American Economic Journal: Microeconomics, 7(3), 259–294.Google Scholar
  5. Berman, R. (2013). Beyond the last touch: Attribution in online advertising (November 16, 2017). Available at SSRN: https://ssrn.com/abstract=2384211.
  6. Budak, C., Goel, S., Rao, J. M., & Zervas, G. (2014). Do-not-track and the economics of third-party advertising. Boston University School of Management Research Paper No. 2505643.Google Scholar
  7. Butters, G. R. (1977). Equilibrium distributions of sales and advertising prices. The Review of Economic Studies, 44(3), 465–491.CrossRefGoogle Scholar
  8. Chen, J., & Stallert, J. (2014). An economic analysis of online advertising using behavioral targeting. MIS Quarterly, 38(2), 429–449.CrossRefGoogle Scholar
  9. Englehardt, S., Reisman, D., Eubank, C., Zimmerman, P., Mayer, J., Narayanan, A., & Felten, E. W. (2015). Cookies that give you away: The surveillance implications of web tracking. In Proceedings of the 24th international conference on world wide web, WWW ’15 (pp. 289–299), New York, NY: ACM.Google Scholar
  10. Ghosh, A., Mahdian, M., McAfee, P., & Vassilvitskii, S. (2012). To match or not to match: Economics of cookie matching in online advertising. In ACM EC’12 (pp. 741–753).Google Scholar
  11. Goldfarb, A., & Tucker, C. E. (2011). Privacy regulation and online advertising. Management Science, 57(1), 57–71.CrossRefGoogle Scholar
  12. Johnson, J. P. (2013). Targeted advertising and advertising avoidance. The RAND Journal of Economics, 44(1), 128–144.CrossRefGoogle Scholar
  13. Mayer, J. R., & Mitchell, J. C. (2012). Third-party web tracking: Policy and technology. In 2012 IEEE symposium on security and privacy.Google Scholar
  14. Tucker, C. E. (2012). The economics of advertising and privacy. International Journal of Industrial Organization, 30(3), 326–329.CrossRefGoogle Scholar
  15. Zhang, K., & Katona, Z. (2012). Contextual advertising. Marketing Science, 31(6), 980–994.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Economics DepartmentMount Holyoke CollegeSouth HadleyUSA

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