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Opposing Influences of YouTube Influencers: Purchase and Usage Effects in the Video Game Industry

Author

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  • Nan Li

    (Advanced Institute of Business, School of Economics and Management, Tongji University, Shanghai 200092, China)

  • Avery Haviv

    (Simon Business School, University of Rochester, Rochester, New York 14627)

  • Mitchell J. Lovett

    (Simon Business School, University of Rochester, Rochester, New York 14627)

Abstract

Influencers promote firms’ products by posting content such as videos on social media platforms. For entertainment products, these posts could substitute or complement demand for the original entertainment product. We study video games, the largest entertainment product category comprising one third of YouTube traffic, using a large daily panel data set on thousands of video games. Leveraging a supply shock on YouTube called the “Adpocalypse,” we measure the impact of influencer videos on purchase and usage of games. We provide plausibly causal evidence that, on average, influencer video posts substitute to video games for purchases but complement for usage. We also find that influencer effects differ across firms. Managers can use these results to align the influencer effects they face with their revenue models, such as using in-game purchases or a subscription model when facing complements on usage.

Suggested Citation

  • Nan Li & Avery Haviv & Mitchell J. Lovett, 2025. "Opposing Influences of YouTube Influencers: Purchase and Usage Effects in the Video Game Industry," Marketing Science, INFORMS, vol. 44(4), pages 894-915, July.
  • Handle: RePEc:inm:ormksc:v:44:y:2025:i:4:p:894-915
    DOI: 10.1287/mksc.2021.0242
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    References listed on IDEAS

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    1. Avery Haviv & Yufeng Huang & Nan Li, 2020. "Intertemporal Demand Spillover Effects on Video Game Platforms," Management Science, INFORMS, vol. 66(10), pages 4788-4807, October.
    2. Michael Anderson & Jeremy Magruder, 2012. "Learning from the Crowd: Regression Discontinuity Estimates of the Effects of an Online Review Database," Economic Journal, Royal Economic Society, vol. 122(563), pages 957-989, September.
    3. Mingyu Joo & Kenneth C. Wilbur & Bo Cowgill & Yi Zhu, 2014. "Television Advertising and Online Search," Management Science, INFORMS, vol. 60(1), pages 56-73, January.
    4. Simon, Daniel H. & Kadiyali, Vrinda, 2007. "The effect of a magazine's free digital content on its print circulation: Cannibalization or complementarity?," Information Economics and Policy, Elsevier, vol. 19(3-4), pages 344-361, October.
    5. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    6. Hasan Bakhshi & David Throsby, 2014. "Digital complements or substitutes? A quasi-field experiment from the Royal National Theatre," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 38(1), pages 1-8, February.
    7. Mitchell J. Lovett & Richard Staelin, 2016. "The Role of Paid, Earned, and Owned Media in Building Entertainment Brands: Reminding, Informing, and Enhancing Enjoyment," Marketing Science, INFORMS, vol. 35(1), pages 142-157, January.
    8. Stephan Seiler & Song Yao & Wenbo Wang, 2017. "Does Online Word of Mouth Increase Demand? (And How?) Evidence from a Natural Experiment," Marketing Science, INFORMS, vol. 36(6), pages 838-861, November.
    9. Matthew Gentzkow, 2007. "Valuing New Goods in a Model with Complementarity: Online Newspapers," American Economic Review, American Economic Association, vol. 97(3), pages 713-744, June.
    10. Anna E. Tuchman & Harikesh S. Nair & Pedro M. Gardete, 2018. "Television ad-skipping, consumption complementarities and the consumer demand for advertising," Quantitative Marketing and Economics (QME), Springer, vol. 16(2), pages 111-174, June.
    11. Thales Teixeira & Rosalind Picard & Rana el Kaliouby, 2014. "Why, When, and How Much to Entertain Consumers in Advertisements? A Web-Based Facial Tracking Field Study," Marketing Science, INFORMS, vol. 33(6), pages 809-827, November.
    12. Pradeep K. Chintagunta & Shyam Gopinath & Sriram Venkataraman, 2010. "The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets," Marketing Science, INFORMS, vol. 29(5), pages 944-957, 09-10.
    13. Seshadri Tirunillai & Gerard J. Tellis, 2012. "Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance," Marketing Science, INFORMS, vol. 31(2), pages 198-215, March.
    14. Mina Ameri & Elisabeth Honka & Ying Xie, 2019. "Word of Mouth, Observed Adoptions, and Anime-Watching Decisions: The Role of the Personal vs. the Community Network," Marketing Science, INFORMS, vol. 38(4), pages 567-583, July.
    15. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
    16. Garrett P. Sonnier & Leigh McAlister & Oliver J. Rutz, 2011. "A Dynamic Model of the Effect of Online Communications on Firm Sales," Marketing Science, INFORMS, vol. 30(4), pages 702-716, July.
    17. Bradley T. Shapiro & Günter J. Hitsch & Anna E. Tuchman, 2021. "TV Advertising Effectiveness and Profitability: Generalizable Results From 288 Brands," Econometrica, Econometric Society, vol. 89(4), pages 1855-1879, July.
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    2. He, Lifeng & Li, Xinmiao & Li, Yuzhuo & Liu, Yu & Zhang, Ning & Zhou, Xiaohang, 2026. "Is more always better? The effect of audience size on sales performance in live streaming commerce: A multimethod study," Journal of Retailing and Consumer Services, Elsevier, vol. 89(PA).

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