A Sectorial Validation and Application of a Conceptual Framework for Creating a Brand Management Strategy
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
Brands can be one of a company’s most valuable intangible assets and a lever to generate value. As a source of added value, a brand should be strategically built and managed. To fully take advantage of the benefits that the brand provides, it is necessary to propose a brand management strategy. A conceptual framework was developed by the authors as an alternative to propose a brand management strategy according to a specific business scenario. The objective of this study is to validate this conceptual framework and apply it to propose a brand management strategy in a specific business scenario. For this purpose, a sectorial cross-validation was developed by triangulating the application of the framework to two data collection methods: (1) interviews and (2) a literature review. The results suggested that decomposing a complex business scenario into single-dimensioned business scenarios can help to propose, enhance, or reframe a brand strategy. The results also suggested that some brand dimensions can be used to lever other brand dimensions, such as brand relationship, which is at the top of CEO/CMO priorities in this field. This work contributes to theory by cross-validating the conceptual framework for creating brand management strategies through triangulation.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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