Wowprime: The Crossroads of Diversification Strategies in Mainland China
Bibliographic record
Abstract
本案例主要描写了王品在中国大陆市场20年的战略发展历程，同时呈现了王品在中国台湾地区的创业发展背景。王品进驻大陆地区市场前十年（2003-2012年），主要依靠从中国台湾总部引进的品牌发展，存活下来的是王品牛排和西堤牛排。2012年起，王品选择了品牌多元化战略，并制定了目标，要在2022年拥有，1000家店。此后，它陆续进入了日料、粤菜、川菜、中式快餐和火锅等领域。然而，在与大陆餐饮同行鏖战十年后，它在大陆只拥有121家店，业绩不如预期。因此，2022年12月底，王品集团董事兼大陆市场中心总经理英美惠跟她的同事们不得不坐下来商议：在中国大陆市场，王品要想发展成为餐饮行业的头部品牌，接下来该如何行动？是继续兼顾中西餐市场？还是回归并聚焦自己所擅长的西餐市场？是否需要投入资源开发西餐下沉市场？
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.006 |
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".