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Record W2084163284 · doi:10.1002/smj.357

Geographic scope and multinational enterprise performance

2003· article· en· W2084163284 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.

Bibliographic record

VenueStrategic Management Journal · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsWestern UniversityUniversity of Victoria
Fundersnot available
KeywordsMultinational corporationScope (computer science)Argument (complex analysis)Diversity (politics)Asset (computer security)Economic geographyInternalization theoryIndustrial organizationSample (material)BusinessStructural equation modelingEconomicsSociologyComputer science

Abstract

fetched live from OpenAlex

Abstract Through an internalization theory lens, an argument is developed to suggest that the traditional concept of geographic scope should be split into two related, but more precise, elements of international asset dispersion and country environment diversity . Subsequently, these new concepts are tested using a structural equation modeling approach on a sample of 580 large multinational enterprises (MNEs). We find that the relationship between economic performance and international asset dispersion is positive, but that country environment diversity is negatively associated with performance, with a positive interaction between them. This study adds to our theoretical understanding of MNEs, and also provides a bridge between the mixed findings of prior research on multinationality by disentangling the unique effects of the latent subcomponents of geographic scope on firm performance. Copyright © 2003 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.521
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.015
GPT teacher head0.221
Teacher spread0.205 · 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