Inaugural lecture of newly appointed KLU professors: "Did They Tell Their Friends?"

On Wednesday, 27 April, 2011 Christian Barrot, Assistant Professor of Marketing and Innovation, (THE KLU) will give a lecture on the topic "Did They Tell Their Friends? - Using Social Network Analysis to Detect Contagion Processes". The lecture is open to the public. Space is limited, so please register ahead of time.

Past event — 27 April 2011

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Prof. Dr. Christian Barrot

Professor of Marketing and Innovation & Dean of Programs

Kühne Logistics University - KLU

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Social contagion processes such as word-of-mouth (WOM) are widely regarded as key success factors for innovation diffusion. Aspects of these processes have been thoroughly explored in empirical studies on the actor or dyad levels of analysis. While such studies offer valuable insight into the motivations and contents of WOM, they are not able to include social network structures in their analysis. Contagion processes, however, require an underlying social networks infrastructure to unfold their potential for innovation diffusion. Although marketing managers strongly believe in social contagion processes, and studies on both actor and dyad levels strongly suggest their existence, marketing scientists have been unable to find conclusive evidence of such effects in network-level studies, which are most appropriate for this purpose.
To address this research gap, we propose a new approach for empirical research in this field: the quantitative determination of communication activity, reach, speed, and epidemicity of observed diffusion processes by using social network analysis. We apply this approach empirically by analyzing anonymized customer data from an innovative telecommunications provider. The resulting social network of adopters, consisting of 55,065 customers and 7.8 million individual phone calls, is analyzed and compared to simulated random networks of similar dimensions. We find strong support for significant social contagion influences on adoption decisions and an epidemic pattern of innovation diffusion.

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