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Record W2781837136 · doi:10.1111/jsbm.12390

External Financing, Export Intensity and Inter‐Organizational Collaborations: Evidence from Canadian SMEs

2018· article· en· W2781837136 on OpenAlexafffundabout
Josée St‐Pierre, Ouafa Sakka, Moujib Bahri

Bibliographic record

VenueJournal of Small Business Management · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersCanada Research Chairs
KeywordsBusinessR&D intensityFinanceIndustrial organizationMarketingEconomicsManagement

Abstract

fetched live from OpenAlex

Drawing on institutional theory, resource-based perspective and internationalization theory, we propose that the domestic collaborations of small and medium-sized enterprises (SMEs) have a direct positive effect on their export intensity, as well as an indirect effect through enhancing these firms' access to external financing. We test our hypotheses on a sample of 151 Canadian manufacturing SMEs and find partial support for the indirect relationship. Overall, our results suggest that domestic collaborations positively affect SMEs' access to equity financing but not to bank financing. While both equity and bank financing are found to enhance these firms' export intensity, bank financing seems to have a greater impact. The implications of these results are discussed.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.022
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.024
GPT teacher head0.220
Teacher spread0.196 · 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

Citations37
Published2018
Admission routes3
Has abstractyes

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