Bibliographic record
Abstract
Abstract\t \nSmall and medium enterprises (SMEs) create 71% of private sector jobs yet only 40% of them project growth (Ratte, 2015). Believing that a properly constructed brand undergirds SME profitability and sustainability, I asked: What makes strong brands? How might we make these elements accessible to non-experts? I examined these questions through a literature survey spanning 30 years of brand planning models, interviews with contemporary experts, and interviews with current SME executives. \n \nI developed the Brand Actualization Tool (BAT) to make brand development accessible and thereby to enhance SMEs’ opportunities for growth and sustainability. BAT consists of five stages: Motivate – define the organization’s authentic brand vision; Embed – operationalize purpose across the organization; Engage – connect the brand and offering to customers; Evaluate – measure success with analytics; adjust activities; and Impact – project activities’ impact into the future. Next steps include validating the positive impact I found that BAT has by increasing the number of SMEs using it and studying their results. \n \nKey words: brand, branding, marketing, SME branding, brand models, brand planning tool, customer purchase behavior, purpose, vision
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.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".