Electronic waste recycling intention, behavior and environmental benefits: Evidence from Middle East
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Significant quantities of electronic waste (e-waste) generated each year have become a global problem, and individuals, organizations, and governments wrestle to find ways of dealing with e-waste. The frequent introduction of new models of electronic gadgets in the market has resulted in a disproportionately large accumulation of obsolete products, escalating the problem of managing e-waste and calling for effective disposal and recycling methods. This study aims to investigate the antecedents to the e-waste recycling intention (EWRI) of individuals. Integrating the theory of planned behavior (TPB) and behavioral reasoning theory (BRT), study developed a conceptual model and tested in the context of a Middle Eastern country, Bahrain. Data was collected from 603 households and analyzed. Hierarchical regression, and PROCESS macros were used to test the hypothesized relationships. The results indicate: (i) attitude, perceived behavioral control, subjective norms, habits, and convenience are positively allied with EWRI, which, in turn, leads to e-waste recycling behavior (EWRB); (ii) EWRB is a precursor to environmental benefits of recycling, and (iii) environmental concern (first moderator) and environmental awareness (second moderator) strengthens the relationship between EWRI and behavior. The findings contribute to the advancement of the theory of sustainability and provide recommendations for administrators and policymakers regarding e-waste recycling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it