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Market Entry and Competition Under Network Effects

Author

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  • Yinbo Feng

    (Research Institute for Interdisciplinary Sciences, School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai 200433, China)

  • Ming Hu

    (Rotman School of Management, University of Toronto, Toronto, Ontario M5S 3E6, Canada)

Abstract

We consider a three-stage game in which, first, a large number of potential firms make entry decisions, then those who choose to stay in the market decide on the investment (quality) level in each product, and last, customers with heterogeneous preferences arrive sequentially to make (random) purchase decisions based on product quality and historical sales under the network effect according to a discrete choice model. We characterize such a random purchase process and show that a growing network effect always contributes to more sales concentration ex post on a small number of products. Perhaps surprisingly, we further show several phase-changing phenomena regarding equilibrium outcomes with respect to the network effect’s strength. In particular, the equilibrium product variety (respectively, quality investment) first decreases (respectively, increases) and then increases (respectively, decreases) as the network effect grows. Specifically, when the strength of the network effect is below a threshold, an increasing network effect would shift more sales toward those products with higher quality, preventing more products from entering the market ex ante and inducing firms to adopt the high-budget equilibrium strategy by making a small number of high-quality products, which is consistent with the blockbuster phenomenon. When the strength of the network effect is above the threshold, the network effect would easily cause the market to be concentrated on a few products ex post; even some low-quality products may have a chance to become a “hit.” Interestingly, in this case, when the network effect is growing, the ex ante equilibrium product variety will be wider, and firms adopt the low-budget equilibrium strategy by making a (relatively) large number of low-quality products, a finding consistent with the long tail theory. We then establish the robustness of the previous main insights by accounting for endogenized pricing and multiproducts carried by each firm.

Suggested Citation

  • Yinbo Feng & Ming Hu, 2024. "Market Entry and Competition Under Network Effects," Operations Research, INFORMS, vol. 72(6), pages 2467-2487, November.
  • Handle: RePEc:inm:oropre:v:72:y:2024:i:6:p:2467-2487
    DOI: 10.1287/opre.2022.0275
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    References listed on IDEAS

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    1. Maldonado, Felipe & Van Hentenryck, Pascal & Berbeglia, Gerardo & Berbeglia, Franco, 2018. "Popularity signals in trial-offer markets with social influence and position bias," European Journal of Operational Research, Elsevier, vol. 266(2), pages 775-793.
    2. Alejandro Zentner & Michael Smith & Cuneyd Kaya, 2013. "How Video Rental Patterns Change as Consumers Move Online," Management Science, INFORMS, vol. 59(11), pages 2622-2634, November.
    3. Ming Hu & Joseph Milner & Jiahua Wu, 2016. "Liking and Following and the Newsvendor: Operations and Marketing Policies Under Social Influence," Management Science, INFORMS, vol. 62(3), pages 867-879, March.
    4. Gérard P. Cachon & Christian Terwiesch & Yi Xu, 2008. "On the Effects of Consumer Search and Firm Entry in a Multiproduct Competitive Market," Marketing Science, INFORMS, vol. 27(3), pages 461-473, 05-06.
    5. Laurina Zhang, 2018. "Intellectual Property Strategy and the Long Tail: Evidence from the Recorded Music Industry," Management Science, INFORMS, vol. 64(1), pages 24-42, January.
    6. Nicholas Economides, 1997. "The Economics of Networks," Brazilian Electronic Journal of Economics, Department of Economics, Universidade Federal de Pernambuco, vol. 1(0), December.
    7. Tom Fangyun Tan & Serguei Netessine & Lorin Hitt, 2017. "Is Tom Cruise Threatened? An Empirical Study of the Impact of Product Variety on Demand Concentration," Information Systems Research, INFORMS, vol. 28(3), pages 643-660, September.
    8. Daniel Fleder & Kartik Hosanagar, 2009. "Blockbuster Culture's Next Rise or Fall: The Impact of Recommender Systems on Sales Diversity," Management Science, INFORMS, vol. 55(5), pages 697-712, May.
    9. Matthew O. Jackson & Leeat Yariv, 2007. "Diffusion of Behavior and Equilibrium Properties in Network Games," American Economic Review, American Economic Association, vol. 97(2), pages 92-98, May.
    10. Toker Doganoglu, 2003. "Dynamic Price Competition with Consumption Externalities," Netnomics, Springer, vol. 5(1), pages 43-69, May.
    11. Kostas Bimpikis & Asuman Ozdaglar & Ercan Yildiz, 2016. "Competitive Targeted Advertising Over Networks," Operations Research, INFORMS, vol. 64(3), pages 705-720, June.
    12. Hinz, Oliver & Eckert, Jochen & Skiera, Bernd, 2011. "Drivers of the Long Tail Phenomenon: An Empirical Analysis," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 56544, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    13. Xin Geng & Xiaomeng Guo & Guang Xiao, 2022. "Impact of Social Interactions on Duopoly Competition with Quality Considerations," Management Science, INFORMS, vol. 68(2), pages 941-959, February.
    14. Erik Brynjolfsson & Yu (Jeffrey) Hu & Michael D. Smith, 2010. "Research Commentary --- Long Tails vs. Superstars: The Effect of Information Technology on Product Variety and Sales Concentration Patterns," Information Systems Research, INFORMS, vol. 21(4), pages 736-747, December.
    15. Ming Hu & Zizhuo Wang & Yinbo Feng, 2020. "Information Disclosure and Pricing Policies for Sales of Network Goods," Operations Research, INFORMS, vol. 68(4), pages 1162-1177, July.
    16. Luís Cabral, 2011. "Dynamic Price Competition with Network Effects," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(1), pages 83-111.
    17. Ying‐Ju Chen & Yves Zenou & Junjie Zhou, 2018. "Competitive pricing strategies in social networks," RAND Journal of Economics, RAND Corporation, vol. 49(3), pages 672-705, September.
    18. Heski Bar-Isaac & Guillermo Caruana & Vicente Cunat, 2012. "Search, Design, and Market Structure," American Economic Review, American Economic Association, vol. 102(2), pages 1140-1160, April.
    19. Ruxian Wang & Zizhuo Wang, 2017. "Consumer Choice Models with Endogenous Network Effects," Management Science, INFORMS, vol. 63(11), pages 3944-3960, November.
    20. Ningyuan Chen & Ying-Ju Chen, 2021. "Duopoly Competition with Network Effects in Discrete Choice Models," Operations Research, INFORMS, vol. 69(2), pages 545-559, March.
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