Biomedical Engineering Reference
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(see, e.g., Van den Bulte (
2000
) for studies on internal infl uence diffusion models
and Van den Bulte and Lilien (
2001
) and Desiraju et al. (
2004
) for studies on inter-
nal infl uence diffusion models in pharmaceutical markets). We now discuss the
studies that explicitly incorporate pharmaceutical marketing variables into macro-
level diffusion models of mixed infl uence and emphasize those parts that are related
to marketing variables. When models are trial-repeat models, we distinguish
between trial or adoption rate and repeat rate. The studies are listed in Table
20.2
.
Lilien et al. (
1981
) propose a trial-repeat diffusion model where own and competi-
tive detailing efforts are taken into account. In their model, detailing affects the trial
rate through external infl uence, whereas competitive promotion affects repeat sales.
The authors fi nd signifi cant, although small, own and competitor effects of detailing.
Rao and Yamada (
1988
) provide support for Lilien et al. (
1981
) by analyzing 21
prescription drugs (results for two drugs are not shown) and showing that “own”
and competitive promotional activities affect the diffusion process.
Hahn et al. (
1994
) include the effects of two aggregate promotional variables
(“own” and competitive expenditures on detailing and medical journal advertising)
on external infl uence. In the most extensive version of their model both “own” and
competitor's promotional efforts affect the trial rate through external infl uence.
Their model is validated using data for 21 prescription drugs from different unspeci-
fi ed categories. They conclude that promotional efforts affect external infl uence.
Shankar et al. (
1998
) propose a version of the Hahn et al. (
1994
) model to study
the effects of late entry in prescription pharmaceutical markets. Their results sug-
gest that innovative (non-innovative) late mover diffusion has a negative (nonnega-
tive) effect on the effectiveness of the pioneer's marketing spending. They also fi nd
that the effectiveness of pioneer marketing spending is signifi cantly affected by
innovative late mover diffusion but not by non-innovative late mover diffusion.
Berndt et al. (
2003b
) examine the role of consumption externalities in the demand
for four prescription drugs within the US antiulcer drug market. They propose a
dynamic system where diffusion equations are used to describe the dynamic adjust-
ment process. In their model price and detailing affect the potential market, and they
conclude that detailing increases the industry saturation level. They fi nd that the
estimated price elasticities are somewhat low and explain this in terms of the politi-
cal pressure on pharmaceutical pricing (Sect.
20.2.4
). They also suggest that the
large detailing elasticities they fi nd may refl ect a rising marginal cost of detailing.
Vakratsas and Kolsarici (
2008
) propose a switching regime dual-market diffu-
sion model for prescription drugs. They accommodate an “early” market corre-
sponding to prescriptions for patients with severe problems and a “late” market
corresponding to prescriptions for patients with mild problems. Although they use
the Bass model to capture the diffusion process for the fi rst market, only the innova-
tion parameter is considered (i.e., they only accommodate external infl uences).
For the late market, they use the Generalized Bass Model (Bass et al.
1994
) to
incorporate the effect of marketing efforts. They use monthly category level data
comprising the number of new prescriptions within a new therapeutic category of a
lifestyle-related disease (the category name is not revealed). Their fi ndings suggest
that the early market is defi ned by an exponential distribution attributed to
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