MétaCan
Menu
Back to cohort
Record W4245218598 · doi:10.24124/2011/bpgub1519

Small business entry into international markets

2011· dissertation· en· W4245218598 on OpenAlexfundaboutno aff
Dawna Buckman

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
FundersUniversity of Northern British Columbia
KeywordsDiversification (marketing strategy)General partnershipBusinessAllianceGlobalizationInternational businessGlobal strategyCompetitive advantageInternational marketIndustrial organizationNiche marketCompetitor analysisCore competencySmall businessMarketingProcess (computing)International tradeEconomicsManagementFinanceComputer scienceMarket economyPolitical science

Abstract

fetched live from OpenAlex

Small businesses encounter problems unique to their size, limited resources and infrastructure while academic literature is limited on their challenges of globalization and partnership issues. They are often owned by equal partners, creating additional complications. Finding a suitable international strategy for growth and diversification as well as understanding practical business solutions for global operations are key variables to guide the decision process. A literature review and analysis of the international experiences of a small Canadian company were conducted to identify risks and resources for global market strategies. This investigation revealed that small companies should capitalize on network and alliance opportunities to gain access to international markets, and consider exporting to test market environments. Good leadership will provide a successful international strategy that fits the small business operations and the company's strategy, while leveraging their core capabilities and competitive advantage into a global niche strategy. --P. ii.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.037
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0080.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0370.006

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 head0.017
GPT teacher head0.223
Teacher spread0.206 · 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

Citations1
Published2011
Admission routes2
Has abstractyes

Explore more

Same topicInternational Business and FDIFrench-language works237,207