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Social Contagion in New Product Diffusion: Network
Structure vs. Mere Geography
Raghuram Iyengar
The Wharton School of the University of Pennsylvania
3730 Walnut Street
Philadelphia PA, 19104-6340
[email protected]
Christophe Van den Bulte
The Wharton School of the University of Pennsylvania
3730 Walnut Street
Philadelphia PA, 19104-6340
[email protected]
Jeonghye Choi
The Wharton School of the University of Pennsylvania
3730 Walnut Street
Philadelphia PA, 19104-6340
[email protected]
Marketers have become very keen on using longitudinal individual-level data
to document and better understand social contagion processes in various forms
of customer behavior, especially the adoption of new products. While some
studies use data on the actual social network ties connecting customers, other
use geographical propinquity as a proxy for social connectedness. There is
little or no work that compares the two types of data (network vs. geography),
leaving three important questions unanswered. First, to what extent is
geographical distance a good proxy for social connectivity? Second, when
geographical and social network data do not show high concordance, does that
mean that one is more informative than the other, or that that each captures a
different kind of contagion process? Third, to what extent are both network
and geographical contagion effects spurious artifacts stemming from
unobserved geographical heterogeneity?
Our research answers these questions in the context of the adoption of a new
prescription drug. We have data on both social network ties (discussion and
patient referral) among physicians within three large cities and on the
geographical distance among their places of practice within those cities. We
find evidence of social contagion over social network ties. We also find
evidence of geographical contagion, but it is highly localized, i.e., operating
only at very short distances. Of particular note is that the geographical
contagion effect becomes non-significant after adding fixed effects controlling
for the co-location of physicians. This suggests that while there is a spatial
effect in our data, it is not a spatial contagion effect. The social network
effect, in contrast, remains significant after controlling for unobserved spatial
heterogeneity. Consistent with prior theory in sociology and research on social
influence in medicine, this pattern suggests that spatial effects might be driven
by either social-normative pressures or heterogeneity across practices,
whereas network contagion is driven by social learning to mitigate functional
and physical risk. From a practical and methodological point of view, our
results indicate there is value in collecting information on both social and
spatial networks rather than on only one or the other.