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Record W4225701788 · doi:10.5539/ibr.v14n12p160

Effect of International Entrepreneurial Orientation on the Internationalization of SMEs: The Contingent Effect of Export Promotion Programs

2021· article· en· W4225701788 on OpenAlexvenueno aff
Ahmed Ibrahim Karage, Raja Nerina Raja Yusof, Devika Nadarajah

Bibliographic record

VenueInternational Business Research · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
Fundersnot available
KeywordsInternationalizationPromotion (chess)Entrepreneurial orientationBusinessStructural equation modelingSmall and medium-sized enterprisesMarketingIndustrial organizationEntrepreneurshipInternational tradePolitical science

Abstract

fetched live from OpenAlex

The study argues that the role of export promotion programs (EPPs) is indirectly exhibited by enhancing the influence of managerial and organizational resources on the internationalization of SMEs. This study proposes that the dimensions of international entrepreneurial orientation (innovativeness, pro-activeness and risk-taking) will show varied strengths as predictors of the internationalization of SMEs’ with the influence of EPPs. Using structural equation modeling, data collected from 266 exporting SMEs in Nigeria were analyzed and it is concluded that SMEs’ risk-taking in internationalization increases with participation in EPPs. Similarly, there was an increase in innovativeness among internationalizing SMEs with increased participation in EPPs. Finally, participation in EPPs did not show any impact in pro-activeness attribute towards internationalization of SMEs. This study demonstrates the supportive role of institutions in SMEs’ managerial capacity building in overcoming internationalization challenges by developing the culture of risk taking and innovativeness.

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)0.009
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.038
GPT teacher head0.344
Teacher spread0.305 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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