Putting Words into Action: Marketing Organic Products with Existing Brand Associations
Bibliographic record
Abstract
As consumer interest in organic products continues to grow, brands are increasingly adding organic variants to their product lines. However, consumer evaluations of these actions are not straightforward and differ for brands with various associations or within different product contexts. Previous research has shown that products with credence attributes, such as organic products, are often judged by brand name and consumers’ existing brand associations. The current study adds to previous work on brand equity and brand associations by explicitly considering the context and characteristics of these branded organic products. First, a pretest determined the existing brands’ corporate social responsibility (CSR) and corporate ability (CA) associations. Next, an online experiment tested consumers’ perceptions of brand equity, consumers’ trust in the brands and consumers’ purchase intentions, which were analyzed using a fully parallel, multiple-mediator process model with the experimental conditions as independent variables. The results show that brand equity increases most when a brand associated with both CA and CSR introduces an organic product. In addition, consumers trust this brand more compared to brands that are less strongly associated with CSR. Moreover, the intention to purchase organic products increases as brand equity increases, but the intention to purchase organic products does not increase as trust increases. Based on these results, we conclude that brands aiming to increase their value to positively affect consumers’ purchase intentions of their organic products benefit most when they are highly associated with both CSR and CA.
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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 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".