HSUEH, KUANG-TAO; PHD
THE PENNSYLVANIA STATE UNIVERSITY, 1983
ECONOMICS, GENERAL (0501)
The purpose of this dissertation is to examine the effect of geographical space
on the diffusion of
innovations. Two issues are studied here. On the one hand, we examine the behavior
of a
profit-maximizing firm toward an innovation and interfirm differences in speed
of response to an
innovation in a spatial context. On the other hand, we also examine the pattern
of innovation diffusion in
a spatial economy. In the first part of the theoretical exploration it is argued
that spatial factors will affect a
firm's attitude toward innovation adoption in the form of urban hierarchy and
neighborhood effects.
Information cost is inversely related to both the location rank of a firm and
the number of neighboring
firms which have adopted an innovation. The amount of information acquired by
a firm to calculate the
expected profit from adoption of innovation is also inversely related to information
cost. Thus the
probability to adopt an innovation by a firm is directly related to its location
rank or the number of
neighboring firms which have adopted the innovation, ceteris paribus. Therefore
interfirm differences in
speed of response to an innovation are due in part to the spatial factor through
the effects of the firm's
location rank and the number of neighboring adopters, in addition to firm size,
growth rate, general
profitability, profit trend, and the regulatory restraints on the adopter industry.
Empirical estimation using
the OLS method tested the theoretical model with data on adoption of computers
by the banking
industry and showed that firm size and urban rank effects are important factors
in explaining interfirm
differences in speed of response to innovation. Less clear are the effects of
the other factors. In the
second part of the theoretical exploration we find that the probability that
at least one firm will innovate at a
place at any time increases monotonically with its size and follows a cumulative
lognormal distribution.
The temporal pattern of innovation diffusion in a spatial economy can be approximated
by a cumulative
normal distribution. Empirical estimation using the minimum normit chi-square
method found the results
supportive of the theoretical model.
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