Valor da marca baseado no consumidor : impactos no desempenho de produtos
Bibliographic record
Abstract
The performance of a product may be related to marketing actions taken by each brand and to the value of these actions perceived by the consumer.The branding strategy affects the consumer and he responds by purchasing products, affecting the market share and profit margin.Besides that relevance, not much has been found in terms of formation of vertical knowledge (test and maturation of previous theories) about the metrics of brand equity and its comparison with the brand performance on product level in the market.To acquire managerial relevance it is necessary to test the prediction behavior of previous metrics and link it to product performance.To help consolidate the area knowledge, this paper seeks to verify what are relations between consumer based brand equity measures and brand performance on product level.The study was realized in two steps: one descriptive and other ex post facto, with data retrieved from the documental archive from a supermarket and applied questionnaires on brand equity.As results, it was observed that the Consumer Based Brand Equity is a good predictor of brand performance in the market, influencing it positively.The research demonstrates that the Multidimensional Brand Equity (MBE), formed by the Perceived Quality and Brand Awareness is sufficient to predict the brand performance.Other result is that the Brand Preference dimension (Overall Brand Equity -OBE) is as good as the Multidimensional to evaluate the Consumer Based Brand Equity and its influence on brand performance.The paper discusses the test in the light of theories about brand equity metrics and has contributions to the management of brands in supermarkets.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".