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Record W2792256425 · doi:10.1177/0266242618763012

Gender and international entry mode

2018· article· en· W2792256425 on OpenAlexaff
Albena Pergelova, Fernando Angulo‐Ruiz, Desislava Yordanova

Bibliographic record

VenueInternational Small Business Journal Researching Entrepreneurship · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsMacEwan University
Fundersnot available
KeywordsInternationalizationForeign direct investmentAgency (philosophy)BusinessResource (disambiguation)International businessEconomic geographyInternational tradePolitical scienceSociologyEconomicsManagement

Abstract

fetched live from OpenAlex

This article examines whether male- and female-led small and medium-sized enterprises (SMEs) adopt different strategic directions when internationalising. We build on the notion of gendered socialisation and the resource-based view examining gender differences in international entry modes. We also analyse several contingencies in the relationship between gender and internationalisation. Findings indicate that female-led SMEs are more likely to internationalise via export than foreign direct investment (FDI). The results challenge conventional wisdom on the role of resources and capabilities accumulated with manager age in the process of internationalisation; younger female chief executive officers are more likely to internationalise via FDI. The results offer novel insights to the literature on internationalisation of SMEs calling for more attention towards the interplay of social norms and gendered structural arrangements, on the one hand, and entrepreneurial agency, on the other, for a better understanding of the internationalisation of female-led SMEs.

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 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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.270
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.079
GPT teacher head0.322
Teacher spread0.244 · 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 teacher head, not a consensus.

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

Citations48
Published2018
Admission routes1
Has abstractyes

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