The Role of Imagination-Focused Visualization on New Product Evaluation
Bibliographic record
Abstract
In this research, the authors examine the impact of imagination-focused visualization on the evaluation of really new products (RNPs)—that is, products that provide novel benefits but involve high learning costs. They compare imagination-focused visualization with memory-focused visualization and demonstrate that an imaginative focus leads to higher evaluations of an RNP but has no effect on the evaluation of incrementally new products, which involve continuous innovations that are easier to understand. They find that the underlying mechanism for this effect is imagination's impact on the perceived value of new benefits rather than on the learning costs. Furthermore, they show that the advantage of an imaginative focus is not simply due to the increased focus on product benefits, because imagination still leads to higher product evaluation than memory-focused visualization, even if participants in both conditions are asked to think about product benefits exclusively. Finally, an explicit focus on learning costs while using an imaginative approach draws attention away from product benefits and attenuates the advantage of imagination on product evaluation.
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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 | 0.030 | 0.018 |
| 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 | 0.000 |
| 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; both teacher heads agree on what is shown here.
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".