Are You Environmentally Conscious Enough to Differentiate between Greenwashed and Sustainable Items? A Global Consumers Perspective
Bibliographic record
Abstract
Environmentally sustainable (green) products are frequently advertised to consumers, yet it is debatable whether the consumers are aware whether these green labelled products are environmentally friendly or not. Greenwashing is a phenomenon used by companies to sell their products. Through stratified (probability) and purposive and convenience (non-probability) sampling techniques, an online survey was circulated to gather information from 768 participants from the UK, Canada, and Pakistan to determine consumers’ perspectives on subjects including awareness, trust, and effectiveness regarding greenwashed labelled products. The results were tested using the Chi-Square test for ranked data and structural equation modelling (SEM) for ordinal data. The study found that participants ranking themselves High environmentalists in comparison to Low and Moderate environmentalists, despite being skeptical, fall into the trap of identifying greenwashed products as sustainable. It has been proven that greenwashing negatively impacts the green purchasing behavior of the consumers. Participants reported that products are believed to be sustainable due to the overall perception of the product labelled as greenwashed. There is statistical evidence that purchase intent is not affected by greenwashing. It is also reported that younger people in comparison to older people have less trust and often believe greenwashing is problematic. Consumers were found to be vulnerable and more sensitive when their attention was drawn towards greenwashing. There is a need to educate consumers and improve policies to ensure consumers understand the real labels as greenwashed products are used in daily life.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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, 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".