Biomedical Engineering Reference
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More research is needed to shed light on the interaction between WOM and
traditional marketing, i.e., how traditional marketing affects the effectiveness of
WOM and vice versa. Such research can help firms design multichannel marketing
campaigns that synergize WOM with traditional marketing.
In the offline context, collecting word of mouth data to study the influence of
WOM is a challenge for researchers. Offline WOM occurs in private conversations,
so it cannot be directly observed. However, online WOM that takes place through
social media are becoming more readily available nowadays. When researchers
embrace the rich online WOM data, they need to determine if the same WOM
mechanisms operate in both the online and offline settings, and whether the assump-
tions and findings from traditional marketing hold for social media marketing as
well. For example, in the realm of traditional advertising, firms spend more resources
promoting their superior products, resulting in advertising being a credible signal of
quality (Milgrom and Roberts 1986 ; Nelson 1974 ). However, analysis of social
media marketing suggests that firms promote their inferior products anonymously
in online communities (Mayzlin 2006 ).
16.3.1
WOM in the Pharmaceutical Industry
In the pharmaceutical industry, WOM influence can emanate from different players
such as patients, physicians, healthcare providers, insurers, regulatory authorities,
general public, and others. There are many intriguing research questions about
WOM in the pharmaceutical industry that await researcher attention. For example,
how does the WOM among physicians and patients affect prescription decisions of
drugs? How do peer effects change over a drug's product life cycle? Who in the
physician and patient networks are opinion leaders and what are their characteris-
tics? How can firms efficiently identify the connections among physicians and
patients? How should firms allocate sales force resources by leveraging the social
influence among physicians and patients? However, studies on WOM and social
influence in the pharmaceutical industry are limited, mainly because of lack of ade-
quate data to infer connections among physicians or patients.
Physician-to-physician connections are unobservable to researchers. Researchers
have defined networks in terms of geographical proximity (Bell and Song 2007 ;
Manchanda et al. 2008 ), and nominated opinion leader and physicians pairs (Iyengar
et al. 2011b ; Nair et al. 2010 ). In the former approach, researchers use the zip codes
of physicians' primary practices to identify physicians' locations, compute the dis-
tance between each pair of physicians, and define physicians located within a speci-
fied mileage to be in each other's reference group. In the latter approach, researchers
conduct surveys to ask physicians to nominate a few other physicians who are their
opinion leaders or with whom they discuss medical questions. However, both meth-
ods have limitations. Using geographic proximity based on limited radius around
the location of a physician's primary practice to identify reference group assumes
all physicians within the location have equal influences on the focal physician.
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