Identifying consumers' engagement with renewable energy
Bibliographic record
Abstract
Abstract A moral engagement with sustainability enhances consumers' willingness to pay an increased rate for renewable energy when utility firms offer a variety of financial incentives to buy, rent and lease energy solutions to promote the uptake of energy‐efficient technologies. Using structural equation modelling, with data collected from 140 residential energy consumers in Canada, this paper tests and finds evidence that consumers' moral disengagement with environmental concerns negatively influences their willingness to pay more for renewable energy. Furthermore, it is observed that a consumer's perceived sense of control when evaluating energy solutions further accentuates the effects of moral disengagement on willingness to pay. These findings also illuminate the socio‐economic factors that encourage moral engagement concerning renewables. These findings underscore and build upon the claims of the theory of moral self‐regulation. The results and implications guide energy suppliers in potential niche business models to promote the uptake of energy efficient technologies. Similarly, the findings can guide policy‐makers on the cognitive and psychological factors that shape consumers' moral engagement with environmental concerns.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".