Abstract :
Empirical evidence suggests that the ownership of
related products that form a technology cluster is significantly
better than the attributes of an innovation at
predicting adoption. The treatment of technology clusters,
however, has been ad hoc and study specific:
Researchers often make a priori assumptions about the
relationships between technologies and measure ownership
using lists of functionally related technology,
without any systematic reasoning. Hence, the authors
set out to examine empirically the composition of technology
clusters and the differences, if any, in clusters of
technologies formed by adopters and nonadopters.
Using the Galileo system of multidimensional scaling
and the associational diffusion framework, the dissimilarities
between 30 technology concepts were scored by
adopters and nonadopters. Results indicate clear differences
in conceptualization of clusters: Adopters tend to
relate technologies based on their functional similarity;
here, innovations are perceived to be complementary,
and hence, adoption of one technology spurs the adoption
of related technologies. On the other hand, nonadopters
tend to relate technologies using a stricter
ascendancy of association where the adoption of an
innovation makes subsequent innovations redundant.
The results question the measurement approaches and
present an alternative methodology.
