An Eco-Label Can Matter More Than Buying Green: An Experiment on Consumers' Recycling Behaviour After Tasting Eco-Labeled Coffee
Bibliographic record
Abstract
An experiment was conducted to test whether a coffee package bearing a Rainforest Alliance Certified (RAC) label triggered affective responses favoring the coffee and further influenced the pro-environmental behaviour of participant consumers in convenience stores. One group of customers viewed an RAC-labeled package and tasted the coffee while the other group viewed a non-labeled package and tasted the coffee. Both groups filled out a questionnaire collecting Likert-type scale data on their affective responses to, perceived flavors of, and willingness to pay for the coffee during the tasting and viewing. Whether they disposed of the paper cup for the trial taste in a recycling box or a trash box was observed. A logit model was employed to estimate the probabilities of their recycling the cup over discarding the cup. Results revealed that more positive feelings were expressed and recycling behaviour was increased among customers exposed to the package with an RAC label, although the two groups did not differ significantly in their perceived flavors and willingness to pay. It was estimated that the probability of the RAC-labeled group to recycle the paper cup was 2.89 times higher than that of the non-labeled group. Based on the theory of central and peripheral routes of information processing, the mechanisms of the behavioural influence of the label are discussed with a few possible factors such as involvement and self-identity. This study contributes to the advancement of eco-label research by shifting the focus to the non-purchasing behavioral effects of eco-labels on consumers and observing the behaviors in real, rather than laboratory, settings. It might also inform the promotion of sustainable consumption of the merits of employing experiential marketing.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".