Leveraging Peer-to-Peer Networks in Pharmaceutical Marketing - Innovation and Marketing in the Pharmaceutical Industry - page 465

patient referral network). Perhaps a hierarchical model of opinion leaders at the
regional and at the national level may provide a more complete picture of the physi-
cian network. Bhatia and Wang ( 2011 ) find continuous influence of regional opinion
leaders found by tracking patient movements between physicians, while Nair et al.
( 2010 ) find that survey-identified opinion leaders are influential only in the times
following an uncertainty. It could be that the former process is identifying “Market
leaders” while the latter is identifying “Clinical leaders.” Identifying both kinds of
leaders in one research study with different drug categories may be useful to gain a
better understanding of this hierarchy of opinion leaders. There may also be some
benefit to exploring “strong” and “weak” ties between physicians along with network
size. There is some evidence that weak ties lead to stronger contagion than strong ties
(Godes and Mayzlin 2004 ).

15.5.6 Role of Sustained Use in Contagion

Aral ( 2011 ) suggests studying the role of sustained use in creating sustainable
contagions. The sustained use may be correlated with consumer satisfaction,
increasing the probability that a user will persuade others to adopt the product. The
opposite could also be true, where sustained use of the product leads to waning
enthusiasm for the product, making the user less likely to spread word-of-mouth in
later periods. This is also related to the volume contagion findings in Iyengar et al.
( 2011 ). It will be informative to study how the volume of the drug prescribed over
time affects the propensity of the physicians to recommend it to colleagues. The
side effects of drugs and patient match characteristics are revealed later in the life
cycle through physician learning, and physician enthusiasm about the product could
be key to increasing the product market share in a more mature and competitive
market with newer competitors. Also, it may be useful to include feedback effects
in the model. For example, assume that physician X has recommended brand A to
physician Y. How does the performance of brand A as perceived by physician Y
impact continued reliance on word-of-mouth from physician X when he/she recom-
mends a second brand at a later point in time?

15.5.7 Susceptibility to Social Influence

Another avenue for research is to study which customers are more susceptible to
contagion and why (Godes 2011 ). The focus of research so far has been on the
sender and not the receiver of the contagion—the influencer and not the influenced.
It may be interesting to see how self-reported opinion leadership and sociometric
centrality moderate vulnerability to contagion. To propagate the message most
efficiently, those with significant influence need first to adopt it. IVV find that
opinion leaders adopt sooner, but this may not always be the case. If those with
influence are aware of their social status, they may want to wait and have more