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Relating Cognitive Problem-Solving Style to User Resistance 199
could have allowed this. The only parameter to be measured that the selectors of
the systems in each organization knew of in advance, was that of user resistance.
However, the R-score sample, which is composed of measures of user resistance
by direct observation, tested satisfactorily normal. Bias for covert reasons on the
part of organizational managers was thus considered unlikely. This therefore leaves
the third alternative as a possibility, namely, failure of the seven-interval measuring
technique. Experience with these scales confirmed this reservation. For example,
the respondents at times tried to give intermediate responses, which were discouraged
by the choice-presentation. Quite clearly, this would have limited tying in the
data, enhancing the credibility of the association statistics.
Fortunately, reliable measures of association were still possible in the case of
most of the non-normal, seven-option samples, where the responses could be
meaningfully regrouped. Some sets of responses, for example, could be redefined
as dichotomies or trichotomies. Somewhat more confidence is thus indicated for
measures where the responses can, on some legitimate criterion, be divided into two
giving approximately 50%, or three giving some 33% of the readings in each class.
Effectively, this means that an approximate maximum of 17 out of 34 readings
should be present for anyone of the options 1 to 7; at least a requirement fulfilled
by all the samples considered below.
The Results
The associations were first computed as Kendall’s rank correlation coefficients,
ta and tb. In order to measure the significance of each association t, the
standard normal statistic for zero association, z(t), was calculated. The significance
of t was then determined from standard normal tables (Huntsberger et al, 1973),
as a tail area. The results of this procedure for each hypothesis have been
summarized in Table 4. Table 5 contains a complete summary of the consequent
findings.
The Role of Cognitive Problem-Solving Styles
Hypothesis HI, which posits a significant positive correlation between the user
R-scores and arithmetic difference in analyst and user KAI scores (I KAI I), tested
as significant at the 0.005 significance level. In other words, there is substantially
more than minimal evidence of a positive association between user resistance and
analyst-user cognitive style differences. The implication is immediately obvious: to
minimize user resistance; match users with analysts of similar cognitive style.
However, some caution is in order. Adaptors and innovators, according to Kirton,
have need of each other in many occupational situations; the adaptor to add stability
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