Unraveling Factors Affecting Food Waste Globally: A PRISMA-Based Systematic Literature Review and Bibliometric Analysis
Bibliographic record
Abstract
This study utilizes a systematic literature review and bibliometric analysis, following the PRISMA method, to explore behavioral and contextual factors influencing food wastage based on literature published from 2019 to 2024.It identifies key determinants such as perceived control, consumer intention, attitudes, subjective norms, religiosity, and household dynamics.Perceived control notably correlates with up to a 20% reduction in household food waste.The research highlights a scholarly trend towards incorporating sustainability into the food supply chain, with a focus on bioenergy recovery from waste.It also examines sociodemographic, cultural, and psychological influences on food wastage behaviors across various regions, illustrating the complexity of these behaviors and the need for tailored, region-specific approaches.The findings advocate for an interdisciplinary strategy that merges design, technology, and behavioral science to enhance food waste management systems.Such strategies should be adaptable to different cultural contexts and aim to minimize ecological footprints, supporting global sustainability goals.The implications suggest that policymakers and practitioners should develop sustainable, design-oriented solutions that account for local behaviors and systemic capacities to effectively curb food waste.This approach promotes culturally sensitive and environmentally sound interventions, leading to significant reductions in global food wastage.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.092 | 0.252 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.015 | 0.013 |
| Bibliometrics | 0.228 | 0.187 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".