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Record W4323832222 · doi:10.46697/001c.72797

Mature MNE Subsidiaries in Emerging Markets: An Old Phenomenon with a New Research Agenda

2023· article· en· W4323832222 on OpenAlex
Félix Arndt, Christiaan Röell, Vikas Kumar

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

VenueAIB Insights · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSubsidiaryMultinational corporationBusinessPhenomenonIndigenousEmerging marketsIndustrial organizationInternational businessEmpirical researchEconomic geographyMarket economyEconomicsManagementFinance

Abstract

fetched live from OpenAlex

Subsidiaries that were established in emerging markets many decades ago require different management practices than new market entrants and indigenous firms. The international business (IB) literature lacks both theories that predict the behaviors of mature subsidiaries in host countries as well as a solid empirical base to sufficiently comprehend this distinct category of firms. We explain the phenomenon, its distinct character, and underscore missed opportunities for research on mature subsidiaries in the IB field, with the ultimate goal of promoting research that can better advise managers of these multinational enterprises (MNEs).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.060
GPT teacher head0.300
Teacher spread0.241 · 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