Between hesitation and decisiveness—Understanding consumers' ego, altruism, and eagerness to pay for renewable energy
Bibliographic record
Abstract
Abstract In our study, we examined the role of consumers' egoism and social and biospheric altruism in influencing their willingness to adopt renewable energy. Past research has suggested that the social, biospheric, and egoistic values and beliefs of energy consumers influence their cognitive decision‐making mechanisms. However, studies have not compared and contrasted the effects of different altruistic values on specific environmental behaviors. To address this problem, we drew on the theories of value–belief–norm and paradox to propose that social and biospheric altruistic values have diverse effects on renewable energy adoption. We observed that biospheric altruism is positively associated with the adoption of renewable energy and social altruism is negatively associated with the adoption of renewable energy. Contrary to the propositions of the theory of paradox, we observed that egoistic values measured in terms of financial scarcity reduced the paradoxical nature of social and biospheric altruism. In our study, we used partial least squares structural equation modeling to analyze the data. We analyzed 140 responses from the residential energy consumers of New Brunswick, Canada. Our study underscores the claims of value–belief–norm theory. Further, it adds to the theory of paradox. The findings from this study help guide utilities on how to approach different consumers with specific new sustainable and renewable energy products and services. Moreover, the study throws light on how the policy makers should design energy policy‐related messages to specific consumer segments.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".