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Relating Cognitive Problem-Solving Style to User Resistance 199<br />
could have allowed this. The only parameter to be measured that the selectors of<br />
the systems in each organization knew of in advance, was that of user resistance.<br />
However, the R-score sample, which is composed of measures of user resistance<br />
by direct observation, tested satisfactorily normal. Bias for covert reasons on the<br />
part of organizational managers was thus considered unlikely. This therefore leaves<br />
the third alternative as a possibility, namely, failure of the seven-interval measuring<br />
technique. Experience with these scales confirmed this reservation. For example,<br />
the respondents at times tried to give intermediate responses, which were discouraged<br />
by the choice-presentation. Quite clearly, this would have limited tying in the<br />
data, enhancing the credibility of the association statistics.<br />
Fortunately, reliable measures of association were still possible in the case of<br />
most of the non-normal, seven-option samples, where the responses could be<br />
meaningfully regrouped. Some sets of responses, for example, could be redefined<br />
as dichotomies or trichotomies. Somewhat more confidence is thus indicated for<br />
measures where the responses can, on some legitimate criterion, be divided into two<br />
giving approximately 50%, or three giving some 33% of the readings in each class.<br />
Effectively, this means that an approximate maximum of 17 out of 34 readings<br />
should be present for anyone of the options 1 to 7; at least a requirement fulfilled<br />
by all the samples considered below.<br />
The Results<br />
The associations were first computed as Kendall’s rank correlation coefficients,<br />
ta and tb. In order to measure the significance of each association t, the<br />
standard normal statistic for zero association, z(t), was calculated. The significance<br />
of t was then determined from standard normal tables (Huntsberger et al, 1973),<br />
as a tail area. The results of this procedure for each hypothesis have been<br />
summarized in Table 4. Table 5 contains a complete summary of the consequent<br />
findings.<br />
The Role of Cognitive Problem-Solving Styles<br />
Hypothesis HI, which posits a significant positive correlation between the user<br />
R-scores and arithmetic difference in analyst and user KAI scores (I KAI I), tested<br />
as significant at the 0.005 significance level. In other words, there is substantially<br />
more than minimal evidence of a positive association between user resistance and<br />
analyst-user cognitive style differences. The implication is immediately obvious: to<br />
minimize user resistance; match users with analysts of similar cognitive style.<br />
However, some caution is in order. Adaptors and innovators, according to Kirton,<br />
have need of each other in many occupational situations; the adaptor to add stability<br />
Copyright © 2003, Idea Group Inc. Copying or distributing in print or electronic forms without written<br />
permission of Idea Group Inc. is prohibited.