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Record W2113621093 · doi:10.1007/s10843-012-0084-7

The impact of geographic diversification on export performance of small and medium-sized enterprises (SMEs)

2012· article· en· W2113621093 on OpenAlex

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

VenueJournal of International Entrepreneurship · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsBrock University
Fundersnot available
KeywordsDiversification (marketing strategy)InternationalizationBusinessEntrepreneurshipIndustrial organizationSmall and medium-sized enterprisesEmerging marketsDimension (graph theory)LocationKey (lock)MarketingEconomic geographyEconomicsInternational tradeFinance

Abstract

fetched live from OpenAlex

Two alternative diversification strategies—the geographic diversification of export sales and key market concentration—are extensively discussed in management, strategy, entrepreneurship, and economics literature. However, no conclusive evidence currently exists as to how either of these strategies affects the performance of international sales. This paper contributes to a better understanding of geographic diversification as a key dimension of the internationalization process for small and medium-sized enterprises (SMEs). In it, we analyze a comprehensive database of Polish exporters over a 3-year period to better understand the geographic diversification patterns of exporters. Based on this analysis, six propositions emerged from the export patterns examined and two viable strategies for exporting SMEs are identified: (1) concentrating on a single market and (2) a balanced approach aimed at targeting a small number of key markets, combined with a strategy of penetrating other markets. Implications for practice and future research are also discussed herein.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.283

Codex and Gemma teacher scores by category

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

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 head0.021
GPT teacher head0.247
Teacher spread0.225 · 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