S. Gupta et al., Modeling the evolution of markets with indirect network externalities: An application to digital television, MARKET SCI, 18(3), 1999, pp. 396-416
The usefulness of a technology product for an end-user often depends on the
availability of complementary software products and services. Computers re
quire software, cameras require film, and DVD players require movie program
ming in order for customers to value the whole product. This phenomenon, wh
ere the demand for hardware products is mediated by the supply of complemen
tary software products, is called an indirect network externality. Indirect
network externalities create a two-way contingency between the demand for
the hardware product and the supply of software products, and result in a s
trategic interdependence between the actions of hardware manufacturers and
the actions of software providers. Indirect network externalities are gaini
ng economic significance in technology markets, because hardware and softwa
re are typically provided by independent firms, and both sets of firms have
an incentive to free-ride on each others' demand creation efforts. Despite
the ubiquity of this phenomenon, it has largely been ignored in the market
ing science literature.
We present a conceptual and operational model for the evolution of markets
with indirect network externalities. The key feature of our framework is to
model the market-mediated dependence between the actions of hardware manuf
acturers and software complementers, created by the direct dependence of co
nsumer demand for the whole product on the actions of manufacturers as well
as complementors. In addition, we incorporate marketing-mix effects on con
sumer response, as well as heterogeneity in consumer preferences for hardwa
re and software attributes. We model consumer response using a latent-class
choice model. To estimate the complementer response functions, we use a mo
dified Delphi technique that allows us to convert qualitative response data
into quantitative response functions. We integrate the consumer and comple
menter response models to create a simulation model that generates forecast
s of market shares and sales volumes for competing technologies, as a funct
ion of marketing-mix effects and exogenously specified regulatory scenarios
.
The modeling framework is of interest to new product modelers interested in
creating empirical models and decision-support systems for forecasting dem
and in technology markets characterized by indirect network externalities.
The decision-support aspects of the modeling framework should appeal to man
agers interested in understanding and quantifying the complex interplay bet
ween hardware manufacturers and software complementers in the evolution of
markets with indirect network externalities.
We present an application of the modeling framework to the U.S. digital tel
evision industry, and use the framework to characterize the competition amo
ng analog and digital TV technologies. Our results suggest that complemente
r actions play an important role in the acceptance of digital TV technologi
es in general, and high definition television (HDTV) in particular. We find
that forecasts that ignore the influence of indirect network externalities
would be seriously biased in favor of HDTV. We illustrate how the modeling
framework can be used to identify and profile customer segments in the dig
ital TV market based on their utility for hardware-related features as well
as programming-related features. We also illustrate the decision-support c
apabilities of the modeling framework by evaluating the sensitivity of the
forecasts to varying marketing, regulatory, and complementer response scena
rios. We derive implications for marketing and public affairs policies of t
he hardware manufacturers.
The developments in the digital TV industry generally support our finding t
hat HDTV will be a niche product, and will diffuse slower than originally e
xpected due in part to the lack of programming. The delays in the introduct
ion of digital TV to the marketplace also suggest that most forecasts for i
nfrastructure-intensive technologies like digital TV may be too optimistic
simply because they underestimate the delays in agreeing upon technology st
andards and resolving regulatory debates.