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Susceptibility and influence in social media word-of-mouth

Author

Listed:
  • Claussen, Jörg
  • Engelstätter, Benjamin
  • Ward, Michael R.

Abstract

Peer influence through word-of-mouth (WOM) plays an important role in many information systems but identification of causal effects is challenging. We identify causal WOM effects in the empirical setting of game adoption in a social network for gamers by exploiting differences in individuals' networks. Friends of friends do not directly influence a focal user, so we use their characteristics to instrument for behavior of the focal user's friends. We go beyond demonstrating a large and highly significant WOM effect and also assess moderating factors of the strength of the effect on the sender and receiver side. We find that users with the most influence on others tend to be better gamers, have larger social networks, but spend less time playing. Interestingly, these are also the users who are least susceptible to WOM effects.

Suggested Citation

  • 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.
  • Handle: RePEc:zbw:zewdip:14129
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    References listed on IDEAS

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    1. 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.
    2. Giacomo De Giorgi & Michele Pellizzari & Silvia Redaelli, 2010. "Identification of Social Interactions through Partially Overlapping Peer Groups," American Economic Journal: Applied Economics, American Economic Association, vol. 2(2), pages 241-275, April.
    3. Brown, Jacqueline Johnson & Reingen, Peter H, 1987. " Social Ties and Word-of-Mouth Referral Behavior," Journal of Consumer Research, Oxford University Press, vol. 14(3), pages 350-362, December.
    4. Lancaster, Tony, 2000. "The incidental parameter problem since 1948," Journal of Econometrics, Elsevier, vol. 95(2), pages 391-413, April.
    5. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," Review of Economic Studies, Oxford University Press, vol. 60(3), pages 531-542.
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    Cited by:

    1. Nosal, K., 2016. "Physician Group Practices and Technology Diffusion: Evidence from New Antidiabetic Drugs," Health, Econometrics and Data Group (HEDG) Working Papers 16/22, HEDG, c/o Department of Economics, University of York.

    More about this item

    Keywords

    Word-of-Mouth; Peer Effects; Adoption; Social Networks; Video Games;

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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