Bibliographic record
Abstract
近几年，中国餐饮市场发展状态跌宕起伏，发展格局不均衡。行业集中度不断下降的背后，是餐饮业进入门槛低、同质化竞争严重、互联网入侵等深层次原因。特别在风险资本和O2O模式的助推下，餐饮业新进入者呈几何级数增加，行业也陷入了传统思维与新思维、新技术碰撞的混沌状态。 连锁餐饮王品集团计划2022年要在中国大陆市场拥有1,000家店，而截至2016年8月底，这个在中国大陆市场发展14年的企业，在这里仅拥有149家店、5个品牌。案例(A)主要描述王品2012年底之前在大陆市场的发展，其中遭遇的主要问题，以及当时只拥有两个品牌的王品不得不面临的品牌战略抉择；案例（B）主要描述王品自2013年起在大陆市场品牌多元战略的实践，以及相关能力的培养及所面临的挑战。实际上，所有这些挑战都关系到：王品如何能在自2017年开始的6年内开店851家？是通过创建多品牌在多城市开店，还是通过多品牌在有限城市开店？或者，通过聚焦有限品牌在多城市开店，还是通过聚焦有限品牌在有限城市开店？不同的战略选择无疑会带来企业不同的发展结果。
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 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 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".