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Record W2072064046 · doi:10.1002/smj.619

International diversification, subsidiary performance, and the mobility of knowledge resources

2007· article· en· W2072064046 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueStrategic Management Journal · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsWestern UniversityYork University
FundersSocial Sciences and Humanities Research Council of CanadaYork University
KeywordsSubsidiaryDiversification (marketing strategy)BusinessKnowledge transferIndustrial organizationParent companyKnowledge managementMarketingMultinational corporationFinanceComputer science

Abstract

fetched live from OpenAlex

Abstract We examine the link between international diversification, organizational knowledge resources, and subsidiary performance. The success of international corporate diversification depends on a firm's capability to transfer knowledge to its subsidiaries, and how its local subsidiaries effectively utilize that knowledge. As knowledge resources are imperfectly mobile, a firm may find it difficult to transfer knowledge to its subsidiaries. In our analysis of 4964 Japanese subsidiaries over a 14‐year period, we find that knowledge that is valuable, but not rare, positively affects subsidiary performance in the short term, but not the long term. In contrast, knowledge that is both valuable and rare affects subsidiary performance in the long term, but not the short term. Copyright © 2007 John Wiley & Sons, Ltd.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.727
Threshold uncertainty score0.345

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.020
GPT teacher head0.234
Teacher spread0.214 · 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