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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.