The Impact of Package Color and the Nutrition Content Labels on the Perception of Food Healthiness and Purchase Intention
Bibliographic record
Abstract
Considering the difference between hedonic and utilitarian products, this article presents how the choice of color in food packaging, along with the nutrition content claim (NCC) labeling, can influence the consumer’s perception of food healthiness and purchase intention. The responses of 120 non-color-blind and non-obese college students from two within-subject experiments were analyzed by adopting a mixed model for repeated measurement. The results suggest that utilitarian, but not hedonic, food products in blue-colored packages were perceived to be healthier than those in red-colored packages. The perception of food healthiness, which was sensitive to the package color, also influenced the purchase intention of packaged foods. Moreover, when the NCC label was presented, food in a blue package with health claims in the NCC (e.g., “light” label) was perceived healthier than food in a red package with regular labels. This article also discusses the managerial implications of the findings for packaging and advertising professionals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".