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New product adoption in social networks: Why direction matters

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  • Hinz, Oliver
  • Schulze, Christian
  • Takac, Carsten

Abstract

Marketing managers and researchers generally agree that analyzing data from social networks and using them to influence consumers' purchase decisions are useful strategies. However, not all social network data may identify the most influential customers. This empirical study of more than 300 students reveals the low explanatory power of friendship networks (e.g., Facebook) and undirected-advice networks (e.g., LinkedIn). Only directed-advice networks (e.g., Google+) clearly identify influential consumers. In addition, the results challenge conventional wisdom that firms should target advisers assuming that they have the strongest influence on new product adoption. This study contradicts this common assumption and reveals that structural equivalence drives product adoption more than cohesion because advisees' adoption pressures advisers to purchase the product as well. Finally, the study shows the value of social network data beyond the traditional ego-centric psychographic metrics, such as innovativeness or opinion leadership.

Suggested Citation

  • Hinz, Oliver & Schulze, Christian & Takac, Carsten, 2014. "New product adoption in social networks: Why direction matters," Journal of Business Research, Elsevier, vol. 67(1), pages 2836-2844.
    • Handle: RePEc:eee:jbrese:v:67:y:2014:i:1:p:2836-2844
    DOI: 10.1016/j.jbusres.2012.07.005
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    3. Miriam Däs & Julia Klier & Mathias Klier & Georg Lindner & Lea Thiel, 2017. "Customer lifetime network value: customer valuation in the context of network effects," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(4), pages 307-328, November.
    4. Sheikhahmadi, Amir & Nematbakhsh, Mohammad Ali & Shokrollahi, Arman, 2015. "Improving detection of influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 833-845.
    5. Florian Probst & Laura Grosswiele & Regina Pfleger, 2013. "Who will lead and who will follow: Identifying Influential Users in Online Social Networks," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 5(3), pages 179-193, June.
    6. Zhang, Honghong & Fam, Kim-Shyan & Goh, Tiong-Thye & Dai, Xin, 2018. "When are influentials equally influenceable? The strength of strong ties in new product adoption," Journal of Business Research, Elsevier, vol. 82(C), pages 160-170.
    7. Rieple, Alison & Snijders, Sylvia, 2018. "The role of emotions in the choice to adopt, or resist, innovations by Irish dairy farmers," Journal of Business Research, Elsevier, vol. 85(C), pages 23-31.
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    9. Jansen, Nora & Hinz, Oliver, 2022. "Inferring opinion leadership from digital footprints," Journal of Business Research, Elsevier, vol. 139(C), pages 1123-1137.
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