The microfoundations of the innovation-internationalisation nexus: insight from SME manufacturers in Canada
Bibliographic record
Abstract
Faced with the changing dynamics of the current global environment, small and medium-sized enterprises (SMEs) have increasingly realised the need to distinguish themselves through their capacity for innovation, but also internationalisation. Within research on SMEs, more and more studies are trying to explain the nature of the links between innovation and internationalisation (Athreye and Fassio, 2019; Basic, 2021; Pastelakos et al., 2023; Do et al., 2023). However, the mechanisms by which innovation promotes and influences the internationalisation of SMEs have received scant scholarly attention. Hence the following question: How do microfoundations contribute to fostering innovation within SMEs in an internationalization perspective? To fill this gap, this paper aims to better understand the mechanisms (individual, structural and process) that engender innovation and their role in SME engagement in foreign markets. Five case studies were conducted at Quebec SMEs operating in the manufacturing sector. The results provide insights about some important microfoundations: cognitive capital, open innovation culture, strategic intelligence, organic and agile structure.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".