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Record W3006117414 · doi:10.1017/9781316999615.004

Drivers and challenges of internationalising firms

2020· book-chapter· en· W3006117414 on OpenAlexaff
Alain Verbeke, Robin Roberts, Deborah A. Delaney, Peter Zámborský, Peter Enderwick, Swati Nagar

Bibliographic record

VenueCambridge University Press eBooks · 2020
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInternational businessAsia pacificNew business developmentDominance (genetics)BusinessContext (archaeology)Business modelMarketingManagementInternational tradeGeographyEconomics

Abstract

fetched live from OpenAlex

The increasing dominance of the Asia–Pacific region as a source of international business growth has created a dynamic and complex business environment. For this reason, a sound understanding of regional economies, communities and operational challenges is critical for any international business manager working in a global context. With an emphasis on 'doing business in Asia', Contemporary International Business in the Asia–Pacific Region addresses topics that are driving international business today. Providing content and research that is accessible to local and international students, this text introduces core business concepts and comprehensively covers a range of key areas, including trade and economic development, dimensions of culture, business planning and strategy development, research and marketing, and employee development in cross-cultural contexts. Written by authors with industry experience and academic expertise, Contemporary International Business in the Asia–Pacific Region is an essential resource for students of business and management.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0040.003
Scholarly communication0.0210.007
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.036
GPT teacher head0.188
Teacher spread0.153 · 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 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
Published2020
Admission routes1
Has abstractyes

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