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Record W4307260320 · doi:10.5539/jms.v12n2p67

Financial Performance and Characteristics: A Comparison of Born Global and Gradual Internationalization Firms in China

2022· article· en· W4307260320 on OpenAlexvenueno aff
Yanmei Zhang, Minho Kim, Wenzheng Chen

Bibliographic record

VenueJournal of Management and Sustainability · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
Fundersnot available
KeywordsProfit marginProfitability indexChinaInternationalizationBusinessMargin (machine learning)Debt ratioDebtProfit (economics)Gross marginEconomicsFinanceInternational trade

Abstract

fetched live from OpenAlex

This study examines the financial performance and characteristics of born global firms (BGs) in China. While the literature on BGs is growing, few systematic studies have investigated their financial performance, especially for BGs from developing economies like China. This study compares the financial ratios and rates of BGs with those of gradual internationalization firms (GIs) using analysis of variance and data on 1,069 listed companies in China’s manufacturing industry. The results show that BGs are inferior to GIs in profitability, debt paying ability, growth potential, and asset quality but are similar to GIs in terms of asset management capabilities. Born global firms’ ROA, operating profit margin ratio, gross profit margin ratio, current ratio, quick ratio, P/BV, Tobin’s q, and growth ratios are lower than those of GIs; their debt ratio is higher than that of GIs, but their operating activity ratios are not statistically significantly different. The study also finds that ownership and size differences exert significantly impacts on the financial performance of BGs.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.241
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2022
Admission routes1
Has abstractyes

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