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New Study
Reveals Current Predictions for U.S. Online Shopping Are
Overstated
NEW
YORK--(BUSINESS WIRE)-- Online consumer purchasing in the United
States will grow about 50 percent this year, 30 percent over the
next year or two, and 20 percent for a year or two after that,
according to a study conducted at New York University's Stern
School of Business. This new study challenges the current
predictions of many research vendors and public opinion leaders
who have high expectations for online consumer shopping and
buying. For example, the Gartner Group's Dataquest division
projects that U.S. online shopping revenues will increase more
than ten fold by 2003.
"The
omnipresence of the Internet in society today certainly lends
some credibility to the possibility of explosive growth for
online purchasing. But the question everyone is really trying to
answer is `How much?'" says Joel Steckel, professor of
marketing at NYU Stern and author of the study. "The
results of this study show that the rate of growth in this area,
while considerable, may be less than what is currently being
predicted, at least domestically. Dataquest thinks ten times the
money will be spent online three years from now. I think three
times the number of people will be buying online four years from
now. It's hard to completely reconcile those numbers. Those that
buy online would have to buy an awful lot more."
Steckel
notes that many of the current predictions are hard to accept
because their numbers are either:
- presented
without methodological descriptions, prompting questions
about their validity;
- one-shot
studies that do not permit longitudinal investigations; or
- inconsistent
with numbers from other sources.
Many
research companies do not completely expose their methodologies
to public scrutiny. This is clearly understandable since their
competitive advantage in the marketplace depends on their
proprietary methodologies. Nevertheless, from a scientific
viewpoint it is unfortunate, since it is difficult to evaluate
their results without knowing more about how they were obtained.
Steckel's
study develops model-based, five-year "forecasts" of
online shopping and buying in the United States. The forecasts
are not based on what people say they will do or on some
proprietary model. Rather, the study uses standard marketing
methodology applied to data collected from people who tell what
they have already done.
The
paper highlights some useful generalizations as main results.
In
particular, the study asserts the following:
- Domestic
online purchasing will grow about 50 percent in the year
2000, 30 percent over the next year or two after that, and
20 percent for a year or two after that.
- Personal
computer ownership and Internet access are approaching
plateaus in the United States.
- By
the year 2004, at least 60 percent of those having access to
PCs in the United States will have bought over the Internet.
- Within
five years, 90 percent of the American population with PC
access will have Internet access as well.
These
findings raise serious doubts about the predictions for
explosive growth in the area of domestic online shopping and
buying. According to Steckel, our knowledge on this subject is
likely to be misguided. "While the data from this study
does show that there may be substantial growth in online
purchasing over the next few years, I am skeptical about the
current predictions for explosive growth in this area. What I
think most people are missing is that PC penetration in the U.S.
consumer population has already slowed, despite the
proliferation of free PCs. Until other (probably wireless)
technologies become available, online shopping is still
constrained by PC ownership. Even then, new technologies will
take a while to diffuse."
Steckel
uses diffusion models to forecast the number of people
participating in online shopping rather than using sales revenue
for two reasons. First, sales revenues are composed of the
number of people and how much they spend. By focusing on just
one of these factors, there is a better chance of being
successful. Second, diffusion models are the standard technology
for forecasting the number of people to study first-time product
adoption.
The
result of the diffusion modeling process is a lifecycle curve
for the innovation under consideration. The premise behind these
models is that an innovation is adopted by a small, select group
of adopters in the population based on mass media
communications. These adopters, called innovators, then
influence others to adopt via word-of-mouth. As time goes on and
more people adopt the innovation, all non-adopters are subject
to the same type of word-of-mouth, which continues until all
members of the population who will eventually adopt the
innovation have done so.
A
working paper of this study can be found at www.stern.nyu.edu/Faculty/workingpapers/
The
Leonard N. Stern School of Business at New York University is a
world leader in business education. Stern's New York City
location promotes close relationships with the international
business community, offering students unique educational and
professional opportunities. Now in its 100th anniversary year,
NYU Stern has graduated a large number of alumni who are
prominent among the ranks of America's top CEOs. For further
information, visit NYU Stern's website at www.stern.nyu.edu
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