Flat or gradient? The impact of packaging color palette presentation on consumer purchase intent for utilitarian versus hedonic products
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The current research examines two distinct color palette presentations frequently featured in packaging design: flat versus gradient. Gradient color palettes feature a smooth, gradual transition from one color to another, while flat color palettes feature discrete static blocks of colors placed next to one another. Across four experimental studies using both self-report measures (Studies 1 and 3a-3b) and eye-tracking technology (Study 2), the authors show that the use of gradient color palette in the brand’s packaging enhances consumer purchase intent for hedonic products, while the use of flat color palette enhances consumer purchase intent for utilitarian products. Further, the underlying mechanism for this shift in purchase intent is due to the higher arousal level elicited by gradient (vs. flat) color palettes (Studies 3a and 3b). The present research contributes novel theoretical insights to the color research stream by demonstrating how subtle changes in color palette presentations can influence consumer purchase intent for specific product categories. Managerially, this research reveals how brands can strategically affect consumers’ arousal levels through different color palette presentations and highlights the possible increase in overconsumption or indulgence of hedonic products via color gradients, which consumers and policymakers should caution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.048 | 0.047 |
| 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 it