Beyond the bin: overcoming the intention–behavior gap in zero-waste living
Bibliographic record
Abstract
Purpose The zero-waste lifestyle (ZWL) is considered a reasonable step towards controlling waste generation and minimizing the consequences of human activities on the environment. The main aim of this study is to examine the behavioral antecedents of ZWL. Design/methodology/approach The study draws on the theoretical underpinnings of the theory of planned behavior (TPB) and the norm activation model (NAM) to develop a conceptual framework to understand the antecedents to ZWL. A cross-sectional survey among 349 randomly-selected consumers provided data analyzed with the partial least square-structural equation modeling (PLS-SEM) methodology. Findings The results demonstrate that personal norms, attitude, subjective norms and perceived behavioral control positively influenced the intention to adopt ZWL. Additionally, the study showed that the awareness of consequences influenced personal norms, attitudes and subjective norms. However, the study identified an intention–behavior gap in adopting ZWL. Originality/value This study serves as a pioneering exploration of the behavioral factors that impact the adoption of ZWL. Additionally, the paper endeavors to elucidate the underlying reasons behind the intention–behavior gap within this particular context. Consequently, the study offers substantial theoretical and practical implications aimed at promoting and fostering greater adoption of ZWL practices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".