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(5) a serious problem (4) a rather serious problem (3) a significant problem (2) a slight problem (1) not really a problem Relating Cognitive Problem-Solving Style to User Resistance 193 In the light of the previous discussion, the R-score was assumed to be a valid measure of user resistance, despite its novelty. Of course it can be argued that the R-score might change with the nature of the researcher conducting the interview. It was beyond the scope of this study to investigate such a conjecture, but since it was sufficient to show resistance in the relative sense only (comparing resistance between systems investigated by the same person), this criticism was not considered significant. The Role of Cognitive Problem-Solving Styles A submission based on A-I theory, made earlier was that user resistance is associated with differences in developer-user cognitive problem-solving styles. This can now be stated as the following hypothesis: HI: The user’s R-score is positively associated with the absolute analystuser KAI score difference for a given information system Further hypotheses were thus formulated for testing. For example, a user should tend to see an analyst who is more innovative than himself spend surprisingly little time studying the system requirements. This follows from the tendency of innovators to not to wed themselves too long to any system, and to seek continued novelty of activity. Since the user will consider the analyst an “expert” (lacking in the beginning a frame of reference to consider him anything else), he should also assume that the analyst has absorbed all the details in this surprisingly short time. The degree to which a user will see the analyst as more innovative or adaptive than himself is measurable as the algebraic difference between their KAI scores. Hence the hypothesis: H2(a): The analyst-user KAI score difference is positively associated with the user’s seven- point rating of how quickly the analyst absorbed (grasped) the system requirements According to Kirton (1984), innovators tend to pursue a course of action with more apparent certainty than do adaptors. This leads to the obvious conjecture that Copyright © 2003, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.
194 Mullany and Lay an innovative analyst, when dealing with an adaptive user, will tend to follow his own ideas rather than to pay over-much attention to the user. The adaptor, prone to high self-doubt, would be expected to give in to the analyst’s views. Hence: H2(b): The analyst-user KAI score difference is positively associated with the user’s seven-point rating of the extent to which the analyst followed his own ideas and/or ignored the user’s opinions Innovators, with the predilection for novelty, would be expected to add to the system development effort extraneous features, which the more adaptive user would consider unnecessary and time wasting. This suggested the hypothesis: H2(c): The analyst-user KAI score difference is positively associated with the user’s seven-pointrating of the extent to which the analyst wasted time on peripheral issues Innovators are often seen as abrasive, creating dissonance. Hence, a measure of dissonance would be expected to exist between individuals who differ markedly in cognitive style. In addition, Bailey and Pearson (1983) found that a user’s relationship with the IS staff, as well as the attitude of the IS staff, influenced user satisfaction. By “attitude”, Bailey and Pearson were referring to the analyst’s willingness to assist the user. It is doubtful that a user would report friction between himself and the analyst, and then describe their relationship as sound, and the analyst as helpful. Consequently, the user’s ratings of these three factors should be highly correlated. To test this, the following hypothesis was specified: H2(d): The absolute analyst-user KAI score difference is negatively associated with the user’s seven-point rating of his relationship with the analyst The key factors thought by Pearson to play a role in user satisfaction were identified earlier. As it is of interest to see how their approaches compared with that of this study, a short-list of user-satisfaction factors was drawn up. Negative associations were then postulated between these factors and the R-score. The hypotheses tested in respect of the above were thus: H3(a): There is a negative association between the user’s R-score and his seven-point rating of the system’s level of accuracy Copyright © 2003, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.
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Acquisition Editor: Mehdi Khosrow-P
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The Economic and Social Impacts of
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About the Authors 259 Eric Cloete B
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