Competing for Influencers in a Social Network
This paper studies the competition between firms for influencers in a network. Firms spend effort to convince influencers to recommend their products. The analysis identifies the offensive and defensive roles of spending on influencers. The value of an influencer only depends on the in-degree distribution of the influence network. Influencers who exclusively cover a high number of consumers are more valuable to firms than those who mostly cover consumers also covered by other influencers. Firm profits are highest when there are many consumers with a very low or with very high in-degree. Consumers with an intermediate level of in-degree contribute negatively to profits and high in-degree consumers increase profits when market competition is not intense. Prices are generally lower when consumers are covered by many influencers, however, firms are not always worse off with lower prices. The nature of consumer response to recommendations makes an important difference. When first impressions dominate, firm profits for dense networks are higher, but when recommendations have a cumulative influence profits are reduced as the network becomes dense.
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- Raghuram Iyengar & Christophe Van den Bulte & Thomas W. Valente, 2011. "Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 195-212, 03-04.
- Varian, Hal R, 1980. "A Model of Sales," American Economic Review, American Economic Association, vol. 70(4), pages 651-659, September.
- Juanjuan Zhang, 2011. "The Perils of Behavior-Based Personalization," Marketing Science, INFORMS, vol. 30(1), pages 170-186, 01-02.
- Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
- Yuxin Chen & Ganesh Iyer, 2002. "Research Note Consumer Addressability and Customized Pricing," Marketing Science, INFORMS, vol. 21(2), pages 197-208, November.
- Yuxin Chen & Yogesh V. Joshi & Jagmohan S. Raju & Z. John Zhang, 2009. "A Theory of Combative Advertising," Marketing Science, INFORMS, vol. 28(1), pages 1-19, 01-02.
- Ganesh Iyer & David Soberman & J. Miguel Villas-Boas, 2005. "The Targeting of Advertising," Marketing Science, INFORMS, vol. 24(3), pages 461-476, May.
- Narasimhan, Chakravarthi, 1988. "Competitive Promotional Strategies," The Journal of Business, University of Chicago Press, vol. 61(4), pages 427-449, October.
- Peter Zubcsek & Miklos Sarvary, 2011. "Advertising to a social network," Quantitative Marketing and Economics (QME), Springer, vol. 9(1), pages 71-107, March.
- Yuxin Chen & Chakravarthi Narasimhan & Z. John Zhang, 2001. "Individual Marketing with Imperfect Targetability," Marketing Science, INFORMS, vol. 20(1), pages 23-41, November.
- Nair, Harikesh S. & Manchanda, Puneet & Bhatia, Tulikaa, 2006. "Asymmetric Peer Effects in Physician Prescription Behavior: The Role of Opinion Leaders," Research Papers 1970, Stanford University, Graduate School of Business.
- Hema Yoganarasimhan, 2012. "Impact of social network structure on content propagation: A study using YouTube data," Quantitative Marketing and Economics (QME), Springer, vol. 10(1), pages 111-150, March.
- Catherine Tucker, 2008. "Identifying Formal and Informal Influence in Technology Adoption with Network Externalities," Management Science, INFORMS, vol. 54(12), pages 2024-2038, December.
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