The impact of moral intelligence on green purchase intention
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
In this article, the impacts that moral intelligence has on green purchasing intentions in Jordan was investigated based on three moral theories (Utilitarianism, Deontology, Virtue Ethics), as well as the theory of Planned Behavior. Furthermore, four key areas of moral intelligence (compassion, forgiveness, responsibility and integrity) were discussed. A questionnaire was used to obtain the necessary primary data from 191 customers in Jordan. To analyze the results, partial least squares structural equation modeling was carried out. It was concluded that the four key aspects of moral intelligence (compassion, forgiveness, responsibility and integrity) positively impact green purchasing intentions. This research has practical significance in the fields of green marketing and moral intelligence, especially with regard to the dimensions of compassion, forgiveness, responsibility and integrity. These dimensions can thus serve as a guide for improving customers' green purchase intentions in future. Moreover, the research is important for investigations into individual and company-based environmental sustainability.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| 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