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Record W2059541327 · doi:10.5539/ibr.v3n1p136

Key Drivers to Developing Guanxi in China for Taiwanese Small to Medium Sized Firms

2009· article· en· W2059541327 on OpenAlexvenueno aff
Lanying Huang, Hyunmi Baek, Soonhong Min

Bibliographic record

VenueInternational Business Research · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsnot available
Fundersnot available
KeywordsGuanxiEmbeddednessBusinessChinaCompetition (biology)Industrial organizationGovernment (linguistics)Key (lock)Commerce

Abstract

fetched live from OpenAlex

As Chinese economy has become one of the world’s economic powerhouse, research on guanxi, social or business ties in China, has been gaining ground in business research. The study is couched in the theoretical framework of social embeddedness in which the flows of information, resources, and opportunities occur across recognized members of a social network to create mutual benefits. This study empirically tests the major impetus for Taiwanese small to medium sized firms (SMEs) to utilize guanxi networks with business community, local governments, and the central government in China. The study results indicate the extent to which Tawanese firms utilize different types of guanxi differ by firm characteristics (i.e., resources, capabilities, and entry mode) and market factors (i.e., market stability and competition).

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.723
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.083
GPT teacher head0.420
Teacher spread0.337 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations11
Published2009
Admission routes1
Has abstractyes

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