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Record W7132621537

Wowprimes's Brand Diversification Strategy

2018· other· en· W7132621537 on OpenAlexaff
Soo-Hung Terence Tsai, Qiong Zhu, Yunlu Zhang, Jie Liu

Bibliographic record

VenueCEIBS Institutional Repository · 2018
Typeother
Languageen
Field
Topic
Canadian institutionsCentre Casa
Fundersnot available
KeywordsDiversification (marketing strategy)Mainland ChinaChinaMainlandStrategic planningChinese market
DOInot available

Abstract

fetched live from OpenAlex

Wowprime plans to have 1,000 stores in the China mainland market by 2022. As of August 2016, the company, which had been in the Chinese market for 14 years, had only 149 stores and 5 brands. Case A mainly describes the development of Wowprime products in mainland China before the end of 2012, the key problems Wowprime encountered, and its limited strategic choices. Case B describes the company's brand diversification strategy in mainland China since 2013, corresponding capacity-building efforts, and challenges faced. Different strategic choices are bound to have different developmental results.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.033

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.

Opus teacher head0.020
GPT teacher head0.252
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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