The Impact of Analyst-User Cognitive Style Differences on User Satisfaction
Bibliographic record
Abstract
This study explored the relationship between user satisfaction and cognitive style as applied to users and systems analysts over the time of system usage. Based on a sample of 62 âusersystemsâ this study found that the absolute differential in analyst-user cognitive style, or cognitive gap, generally impacts user satisfaction negatively throughout the period of system usage. However, this effect was found to be only particularly strong at two stages of system use; in the third and twenty-first months of system usage. It is thus suggested that analysts should be allocated to users with similar cognitive styles, as one means of optimizing user satisfaction during system usage. Also, that if this precaution is not taken, the system is most likely to stall during the third and twenty-first months of usage. This study thus has important implications for IS team choice during system usage, as well as for system development and maintenance. The results are discussed and conclusions are drawn.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".