A comparative investigation into the internationalisation of Canadian and UK high‐tech SMEs
Bibliographic record
Abstract
Purpose The purpose of this paper is to provide comparative data from a two‐country study; specifically, into the internationalisation strategies of Canadian and UK high‐tech small and medium‐sized enterprises. Design/methodology/approach The methodology employed involves 24 in‐depth interviews, 12 in each country. Findings These suggest that the differences between the firms in the two countries were limited; more similarities were identifiable. Specifically, strategy formation is not as systematic as some previous studies, notably those that focus on the “stage” models, suggest. Entrepreneurs and management teams recognise and exploit opportunities in different ways, ranging from planned strategy formation through to opportunistic behaviour; as such, no single theory could fully explain international entrepreneurial decisions. Research limitations/implications The implication of the findings is to offer support to the literature that has suggested a more holistic view should be undertaken in international entrepreneurship research. Originality/value The main aspect of originality outside of the comparative data involves accounting for the role of serendipity in unplanned overseas market ventures, an issue lacking in much of the earlier literature.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".