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Consumer Privacy and Marketing Avoidance: A Static Model

Author

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  • Il-Horn Hann

    (Marshall School of Business, University of Southern California, Los Angeles, California 90089)

  • Kai-Lung Hui

    (Department of Information Systems, City University of Hong Kong, Hong Kong and Department of Information Systems, National University of Singapore, Singapore 117543)

  • Sang-Yong T. Lee

    (College of Information and Communications, Hanyang University, Seoul 133-791, Korea)

  • Ivan P. L. Png

    (Department of Information Systems and School of Business, National University of Singapore, Singapore 117543)

Abstract

We introduce the concept of marketing avoidance--consumer efforts to conceal themselves and to deflect marketing. The setting is one in which sellers market some item through solicitations to potential consumers, who differ in their benefit from the item and suffer harm from receiving solicitations. Concealment by one consumer induces sellers to shift solicitations to other consumers, whereas deflection does not. Solicitations cause two externalities: direct harm on consumers and the (indirect) cost of consumer concealment and deflection. We find that in markets where the marginal cost of solicitation is sufficiently low, efforts by low-benefit consumers to conceal themselves will increase the cost-effectiveness of solicitations and lead sellers to market more. However, concealment by high-benefit consumers leads sellers to market less. Furthermore, concealment by low-benefit consumers increases direct privacy harm, and consumer welfare is higher with deflection than concealment. Finally, it is optimal to impose a charge on solicitations.

Suggested Citation

  • Il-Horn Hann & Kai-Lung Hui & Sang-Yong T. Lee & Ivan P. L. Png, 2008. "Consumer Privacy and Marketing Avoidance: A Static Model," Management Science, INFORMS, vol. 54(6), pages 1094-1103, June.
  • Handle: RePEc:inm:ormnsc:v:54:y:2008:i:6:p:1094-1103
    DOI: 10.1287/mnsc.1070.0837
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    Cited by:

    1. Luc Wathieu & Allan Friedman, 2009. "An empirical approach to understanding privacy concerns," ESMT Research Working Papers ESMT-09-001, ESMT European School of Management and Technology, revised 14 Jan 2009.
    2. 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.
    3. Chen, Yongmin & Hua, Xinyu & Maskus, Keith E., 2021. "International protection of consumer data," Journal of International Economics, Elsevier, vol. 132(C).
    4. Manmohan Aseri & Milind Dawande & Ganesh Janakiraman & Vijay S. Mookerjee, 2020. "Ad-Blockers: A Blessing or a Curse?," Information Systems Research, INFORMS, vol. 31(2), pages 627-646, June.
    5. Anna D’Annunzio & Antonio Russo, 2020. "Ad Networks and Consumer Tracking," Management Science, INFORMS, vol. 66(11), pages 5040-5058, November.
    6. Chiao, Benjamin & MacKie-Mason, Jeffrey, 2012. "Using uncensored communication channels to divert spam traffic," Information Economics and Policy, Elsevier, vol. 24(3), pages 173-186.
    7. Spiegel, Yossi, 2013. "Commercial software, adware, and consumer privacy," International Journal of Industrial Organization, Elsevier, vol. 31(6), pages 702-713.
    8. Felipe Thomaz & Carolina Salge & Elena Karahanna & John Hulland, 2020. "Learning from the Dark Web: leveraging conversational agents in the era of hyper-privacy to enhance marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 43-63, January.
    9. Zike Cao & Kai-Lung Hui & Hong Xu, 2018. "An Economic Analysis of Peer Disclosure in Online Social Communities," Information Systems Research, INFORMS, vol. 29(3), pages 546-566, September.
    10. JiWen Chai & LiHao Wang, 2023. "Evolutionary game analysis of big data discriminatory pricing diffusion based on the supervision of relevant interest parties," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(4), pages 2094-2101, June.
    11. Yue Shen & Weijun Zhong & Shue Mei, 2023. "Advertising strategies of competing firms considering consumer privacy concerns," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(4), pages 2424-2437, June.
    12. Fehrenbach, David & Herrando, Carolina, 2021. "The effect of customer-perceived value when paying for a product with personal data: A real-life experimental study," Journal of Business Research, Elsevier, vol. 137(C), pages 222-232.
    13. Kai A.Konrad, 2010. "Merger Profitability in Industries with Brand Portfolios and Loyal Customers," Korean Economic Review, Korean Economic Association, vol. 26, pages 5-26.
    14. Mark Armstrong & John Vickers & Jidong Zhou, 2009. "Consumer Protection and the Incentive to Become Informed," Journal of the European Economic Association, MIT Press, vol. 7(2-3), pages 399-410, 04-05.
    15. Qiang Fu & Jingfeng Lu, 2012. "Micro foundations of multi-prize lottery contests: a perspective of noisy performance ranking," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 38(3), pages 497-517, March.
    16. Philipp Dimakopoulos & Slobodan Sudaric, 2017. "Privacy and Platform Competition," Working Papers 2017003, Berlin Doctoral Program in Economics and Management Science (BDPEMS).
    17. Khim Yong, Goh & Kai-Lung, Hui & I.P.L., Png, 2008. "Social Interaction, Observational Learning, and Privacy: the "Do Not Call" Registry," MPRA Paper 8225, University Library of Munich, Germany.
    18. Khim-Yong Goh & Kai-Lung Hui & Ivan P. L. Png, 2015. "Privacy and Marketing Externalities: Evidence from Do Not Call," Management Science, INFORMS, vol. 61(12), pages 2982-3000, December.
    19. Nelson-Field, Karen & Riebe, Erica & Newstead, Kellie, 2013. "The emotions that drive viral video," Australasian marketing journal, Elsevier, vol. 21(4), pages 205-211.
    20. Liu, Weihua & Long, Shangsong & Xie, Dong & Liang, Yanjie & Wang, Jinkun, 2021. "How to govern the big data discriminatory pricing behavior in the platform service supply chain?An examination with a three-party evolutionary game model," International Journal of Production Economics, Elsevier, vol. 231(C).
    21. Kesler, Reinhold & Kummer, Michael E. & Schulte, Patrick, 2017. "Mobile applications and access to private data: The supply side of the Android ecosystem," ZEW Discussion Papers 17-075, ZEW - Leibniz Centre for European Economic Research.

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