Impacts of consumers’ perceived risks in eco-design packaging on food wastage behaviors
Bibliographic record
Abstract
Purpose Packaging links products to consumers by delivering messages to promote healthy food consumption and reduce wastage. However, studies point to a knowledge gap and skepticism among consumers regarding the impact of eco-design packaging on food wastage reduction. To demystify this skepticism and fill the knowledge gap, this study aims to examine consumers’ perceived risks in eco-design packaging and their impact on consumer food wastage. Design/methodology/approach A survey was conducted to identify consumer-perceived risks in eco-design packaging and explain whether, and why, some dimensions of perceived risk are more influential on consumer food wastage decisions. Findings Consumers are prevented by financial, physical, functional, temporal and social factors from adopting eco-design packaging. Through structural equation modeling, we find consumer perceived risks in eco-design packaging influence their food wastage decisions through health consciousness and environmental awareness. Practical implications This study provides practical suggestions for packaging manufacturers, the food industry and policymakers. Originality/value Drawing on the perceived risk theory, this research highlights that the impacts of consumer-perceived risks differ, depending on the dimensions considered in their food wastage decision.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".