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Record W3008390125 · doi:10.1177/0972150919887250

Internationalization of Service SMEs: Perspectives from Canadian SMEs Internationalizing in Asia

2020· article· en· W3008390125 on OpenAlexaffabout
Michael Roberts, Etayankara Muralidharan

Bibliographic record

VenueGlobal Business Review · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsMacEwan UniversityMount Royal University
Fundersnot available
KeywordsInternationalizationBusinessService (business)ChinaSmall and medium-sized enterprisesEmerging marketsMarketingIndustrial organizationInternational tradeEconomic geographyEconomicsPolitical scienceFinance

Abstract

fetched live from OpenAlex

This study investigates how service small and medium-sized enterprises (SMEs) overcome challenges of internationalizing when expanding to markets that are both institutionally and geographically distant. The data is qualitative and collected through a forum on the internationalization of service SMEs. We examine high tech service SMEs from Alberta, Canada where most internationalization has occurred within North American Free Trade Agreement (NAFTA). We develop an understanding of how these firms need to consider the unique environments in institutionally distant economies to successfully enter Asian markets. Using industry and country experts, we develop a 4P (Potential, Proposition, Presence and Policy) framework for service SME strategies to expand to China, India and Korea. The article contributes to the sparse literature on the internationalization of service SMEs into institutionally distant markets.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0100.003
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.260
Teacher spread0.236 · 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 designQualitative
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

Citations11
Published2020
Admission routes2
Has abstractyes

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