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The effects of the social structure of digital networks on viral marketing performance

Bampo, Mauro, Ewing, Michael T., Mather, Dineli R., Stewart, David and Wallace, Mark 2008, The effects of the social structure of digital networks on viral marketing performance, Information systems research, vol. 19, no. 3, pp. 273-290.

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Title The effects of the social structure of digital networks on viral marketing performance
Author(s) Bampo, Mauro
Ewing, Michael T.
Mather, Dineli R.
Stewart, David
Wallace, Mark
Journal name Information systems research
Volume number 19
Issue number 3
Start page 273
End page 290
Publisher Institute for Operations Research and the Management Sciences
Place of publication East Lansing, Mich.
Publication date 2008-09
ISSN 1047-7047
1526-5536
Keyword(s) digital communication
social structure of digital networks
viral marketing
Summary Viral marketing is a form of peer-to-peer communication in which individuals are encouraged to pass on promotional messages within their social networks. Conventional wisdom holds that the viral marketing process is both random and unmanageable. In this paper, we deconstruct the process and investigate the formation of the activated digital network as distinct from the underlying social network. We then consider the impact of the social structure of digital networks (random, scale free, and small world) and of the transmission behavior of individuals on campaign performance. Specifically, we identify alternative social network models to understand the mediating effects of the social structures of these models on viral marketing campaigns. Next, we analyse an actual viral marketing campaign and use the empirical data to develop and validate a computer simulation model for viral marketing. Finally, we conduct a number of simulation experiments to predict the spread of a viral message within different types of social network structures under different assumptions and scenarios. Our findings confirm that the social structure of digital networks play a critical role in the spread of a viral message. Managers seeking to optimize campaign performance should give consideration to these findings before designing and implementing viral marketing campaigns. We also demonstrate how a simulation model is used to quantify the impact of campaign management inputs and how these learnings can support managerial decision making.
Language eng
Field of Research 010206 Operations Research
Socio Economic Objective 950299 Communication not elsewhere classified
HERDC Research category C1 Refereed article in a scholarly journal
HERDC collection year 2008
Copyright notice ©2008, INFORMS
Persistent URL http://hdl.handle.net/10536/DRO/DU:30017617

Document type: Journal Article
Collections: School of Engineering and Information Technology
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