FIELDS, DAVID MICHAEL; PHD
UNIVERSITY OF ARKANSAS, 1986
BUSINESS ADMINISTRATION, MARKETING (0338)
The focus of this dissertation was the study of the adoption decision associated
with acceptance of the
symbolic character of a largely unmarketed technological innovation. In this
context, the familiar adoption
process (i.e., awareness - information - evaluation - trial - adoption) must
be viewed as two separate
phases. The first phase would take the adopting unit through the evaluation
stage, at which point a
decision to symbolically adopt or reject the idea associated with the innovation
would be made. Symbolic
adopters would move to the second phase which includes the trial and adoption
stages. The objective of
this study was to: Determine whether significant differences exist and can be
identified for symbolic
adopters and symbolic rejectors of the idea component for a specific innovation
(i.e., home video
ordering). Diffusion literature has identified a series of measures that differentiate
between adopter
groups at the final level of adoption. Six of the variables, some with multiple
measurements, were
examined to determine the extent of their value in differentiating at the symbolic
level. The variables
were: (1) Demographics; (2) Characteristics of Innovations, (a) relative advantage,
(b) compatibility, (c)
complexity, (d) trialability, (e) observability; (3) Perceived Risk; (4) Perceived
Need; (5) Personality
Variables; (a) dogmatism, (b) social character, (c) venturesomeness; (6) Social
Interaction, (a) social
integration, (b) cosmopoliteness, (c) opinion leadership. Hypotheses were developed
for each of the six
variables. Symbolic adopters and symbolic rejectors were identified as the upper
and lower quartiles on
the spectrum developed by a three-item symbolic adoption measure. The hypotheses
were tested with
cross classification and discriminant analysis methodologies. Results indicated
each of the six
hypotheses should be rejected, indicating differences between the two groups.
The final discriminant
function demonstrated an accuracy rate of 97.6 percent. The same function was
applied to a hold-out
sample for validation purposes. The original function correctly classified 96.6
of the adopter classes in
the hold-out sample.
Social
Systems Simulation Group
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