Rethinking single-use plastic (SUP): Behavioural insights and lessons from a developing nation
Bibliographic record
Abstract
Over the past sixty years, single-use plastic (SUP) waste has emerged as a critical environmental issue globally, with Vietnam ranking among the top contributors to ocean and landfill pollution. This study aims to evaluate the effectiveness of voluntary SUP packaging reduction initiatives in Vietnam, drawing comparisons with international practices through a rapid evidence review and semi-structured interviews with Vietnamese practitioners. Using Bragge et al.’s (2023) evaluation framework, this study identified eight exemplary initiatives: four promoting reusable packaging (through deposit systems, return programs, and refill schemes) and four recycling efforts (using door-to-door collection, voluntary drop-off points, and incentive schemes) in countries such as the Netherlands, Australia, Spain, and Canada. These international initiatives highlight the effectiveness of consumer incentives, stakeholder collaboration, and digital tracking technologies in facilitating behaviour change. In contrast, semi-structured interviews with five Vietnamese practitioners revealed critical challenges, including insufficient government support, inadequate infrastructure, high costs, and the dominance of plastic packaging options, which complicate the implementation of SUP strategies in Vietnam. However, Vietnamese practitioners also noted enabling factors, such as growing consumer awareness, regional green initiatives, and sustainable branding, community support for SUP alternatives. These findings underscore the importance of tailored interventions in developing contexts, suggesting that Vietnam could benefit from enhanced government infrastructure, financial support, and technology integration to improve SUP outcomes. For practitioners, this study provides actionable insights on leveraging consumer engagement and collaborative frameworks to support sustainable practices. Future research should investigate the long-term effectiveness of such interventions within Vietnam's specific socioeconomic landscape, providing data to inform policy and drive practical improvements in SUP strategies.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".