The Predictors and Consequences of Personal Norms in Context of Organic Food Among Pakistani Consumers
Bibliographic record
Abstract
Purpose: The primary aim of this research is to identify the influence of environmental belief (awareness of consequences, injunctive social norms, environmental concern, environmental self-identity and aspiration of responsibility) on personal norms and subsequent effect on organic food purchase intentions with mediation outcome of personal norms and moderating role of willingness to pay.Design/methodology/approach: The data was collected from individual Pakistani consumers with 430 effective questionnaires. Further the responses were analysed through SPSS, V-22, smart PLS-3.Findings: The results showed that awareness of consequences, injunctive social norms, environmental concern, environmental self-identity and aspiration of responsibility showed significant influence to personal norms towards organic food. Subsequently, personal norms had a significant effect on consumer purchase intentions. Furthermore, organic food willingness to pay proved to be significant and positive moderator between personal norms and organic food purchase intentions.Research implications: This study provides organic food marketers to understand the consumer’s demand from the consumers’ moral perspective and suggests the basis for the future development of organic food.Originality/value: The study implications suggest the need for policy makers to educate and positively promote organically produced foods to consumers through messages based on morality.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".