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Network engagement from learning friends’ preferences: evidence from a video gaming social network

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  • Michael R. Ward

    (University of Texas in Arlington and ZEW Mannheim)

Abstract

Increased similarity with one’s friends’ choices in a social network leads a user to engage further with the social network. Participation is modelled based on user utility derived both from participating in preferred events and from joint participation with friends. The model implies that users will participate more as they learn that they share more interests with their friends. These implications are tested using panel data from an online video gaming network in which users can learn the characteristics of friends’ recent game play behaviour. The focal user’s time on the platform increases substantially as friend’s choices become more similar to the focal user’s behaviour. These results are robust to multiple possible sources of endogeneity.

Suggested Citation

  • Michael R. Ward, 2022. "Network engagement from learning friends’ preferences: evidence from a video gaming social network," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1239-1255, September.
  • Handle: RePEc:spr:elmark:v:32:y:2022:i:3:d:10.1007_s12525-022-00583-7
    DOI: 10.1007/s12525-022-00583-7
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    References listed on IDEAS

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    1. Oded Netzer & James M. Lattin & V. Srinivasan, 2008. "A Hidden Markov Model of Customer Relationship Dynamics," Marketing Science, INFORMS, vol. 27(2), pages 185-204, 03-04.
    2. Yan Huang & Stefanus Jasin & Puneet Manchanda, 2019. "“Level Up”: Leveraging Skill and Engagement to Maximize Player Game-Play in Online Video Games," Information Systems Research, INFORMS, vol. 30(3), pages 927-947, September.
    3. Bramoullé, Yann & Djebbari, Habiba & Fortin, Bernard, 2009. "Identification of peer effects through social networks," Journal of Econometrics, Elsevier, vol. 150(1), pages 41-55, May.
    4. Claussen, Jörg & Engelstätter, Benjamin & Ward, Michael R., 2014. "Susceptibility and influence in social media word-of-mouth," ZEW Discussion Papers 14-129, ZEW - Leibniz Centre for European Economic Research.
    5. Takac, Carsten & Hinz, Oliver & Spann, Martin, 2011. "The Social Embeddedness of Decision Making: Opportunities and Challenges," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 56545, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    6. Markus Mobius & Tanya Rosenblat, 2014. "Social Learning in Economics," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 827-847, August.
    7. Enrico Moretti, 2011. "Social Learning and Peer Effects in Consumption: Evidence from Movie Sales," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(1), pages 356-393.
    8. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    9. Jörg Claussen & Tobias Kretschmer & Philip Mayrhofer, 2013. "The Effects of Rewarding User Engagement: The Case of Facebook Apps," Information Systems Research, INFORMS, vol. 24(1), pages 186-200, March.
    10. Sinan Aral & Dylan Walker, 2011. "Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence in Networks," Management Science, INFORMS, vol. 57(9), pages 1623-1639, February.
    11. Ariel BenYishay & A Mushfiq Mobarak, 2019. "Social Learning and Incentives for Experimentation and Communication," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(3), pages 976-1009.
    12. Bryan S. Graham, 2017. "An Econometric Model of Network Formation With Degree Heterogeneity," Econometrica, Econometric Society, vol. 85, pages 1033-1063, July.
    13. Liye Ma & Ramayya Krishnan & Alan L. Montgomery, 2015. "Latent Homophily or Social Influence? An Empirical Analysis of Purchase Within a Social Network," Management Science, INFORMS, vol. 61(2), pages 454-473, February.
    14. Eva Ascarza & Bruce G. S. Hardie, 2013. "A Joint Model of Usage and Churn in Contractual Settings," Marketing Science, INFORMS, vol. 32(4), pages 570-590, July.
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    Cited by:

    1. Xinyi Lyu & Tiaojun Xiao & Jingquan Li, 2024. "Evolution of direct network effects: A perspective of market thickness of an online freight platform," Electronic Markets, Springer;IIM University of St. Gallen, vol. 34(1), pages 1-16, December.
    2. Rainer Alt, 2022. "Electronic Markets on platform culture," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1019-1031, September.

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    More about this item

    Keywords

    Homophily; Engagement; Video games; Social network;
    All these keywords.

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management

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