Bibliographic record
Abstract
Subject area Entrepreneurship, entrepreneurialism, marketing strategy, strategic stakeholder engagement. Study level/applicability Entrepreneurship policy makers, post-graduate level, practitioners interested in MENA region. Case overview Yogen Früz is a leading frozen-yogurt franchising network started in 1986 in Ontario, Canada, as a small business adventure. It then grew to be the largest frozen-yogurt company in the world after acquiring many of its smaller competitors locally and internationally. In 2002, new key players entered the market and set new benchmarks in the frozen-yogurt industry, which led to Yogen Früz losing its dominance and closing many shops. This case study is written to show how Yogen Früz, the world's largest frozen-yogurt chain, was outperformed by new, small-sized rivals in the industry. This case explains the successful strategic move made by Yogen Früz to adopt a rebranding strategy and reintroduce itself with a totally new brand image. Yogen Früz specializes in frozen yogurt and now has more than 100 flavors and 1,300 outlets around the world. Expected learning outcomes This case study will expose students to a strategically successful example of expansion and critical thinking beyond the daily operation of a business. The students will be able to apply business process models, SWOT analysis. Supplementary materials Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.244 | 0.072 |
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".