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Record W2904350910 · doi:10.1111/1467-8551.12326

Regional Integration, Multinational Enterprise Strategy and the Impact of Country‐level Risk: The Case of the EMU

2019· article· en· W2904350910 on OpenAlexaff
Jenny Hillemann, Alain Verbeke, Won‐Yong Oh

Bibliographic record

VenueBritish Journal of Management · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMultinational corporationSubsidiaryBusinessEquity (law)InsiderInternational businessInternational economicsEuropean unionInternational tradeIndustrial organizationEconomicsFinance

Abstract

fetched live from OpenAlex

Abstract The European Monetary Union (EMU) provides a new macro‐level, institutional setting for multinational enterprises (MNEs). The authors investigate the impact of regional integration on MNE strategy by analysing Belgian firms’ entry‐mode choices in foreign markets, both EMU and non‐EMU ones, with a focus on what impact remains of country‐level risk. They demonstrate that regional integration has altered the impact of country‐level institutional risk on MNE entry‐mode choices inside the EMU. The conventional predictions of international business theory have been reversed, with higher country‐level risk inside the EMU driving a preference for wholly owned subsidiaries. Within the integrated region, insider firms now view higher country‐level risk as the equivalent of higher, micro‐level contracting risk. Such risk can best be mitigated through full internalization, combined with arm's length contracts, rather than through equity joint ventures.

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)0.004
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 score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0060.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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

Citations18
Published2019
Admission routes1
Has abstractyes

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