The Impact of Image Dimensions toward Online Consumers’ Perceptions of Product Aesthetics
Bibliographic record
Abstract
ABSTRACT Marketers and industrial designers devote considerable attention to the visual attributes of products, based on the premise that the visual appearance of products influences consumers’ judgments of the products’ attributes. This research investigated consumers’ perceptions about particular types of innovative products (revolutionary technology‐driven products), with 275 consumers sample purchased from an independent marketing company. To achieve the main goal, interrelations among image of product and aesthetics of product have been examined using structural equation modeling with two psychological moderators: consumer innovativeness and needs for uniqueness. The results of this study provide evidence that individual differences in uniqueness motivation moderated how online consumers’ perceptions of a product's image characteristics influenced perceptions of value showing consumers’ need for uniqueness was more influential toward perceptions of the product's value than perceptions of functional value. Consequently, these findings expand understanding of the consumer characteristics that respond to perceptions of products’ epistemic value.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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; 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".