The Internationalization of Small and Medium-Sized Family Enterprises
Bibliographic record
Abstract
This article assesses the role of human asset quality in the internationalization of small and medium-sized family enterprises. Building on mainstream international business theory, we propose a model with three “states” of human asset quality (low, medium, and high) available to the firm that can be linked to particular levels of export intensity. Importantly, achieving higher export intensity is not always associated with higher human asset quality across the board: There is a key difference between generic (generally available) and specialized (highly firm-specific) human asset quality. We empirically test our model through Tobit panel data analyses with random effects, whereby we study a sample of 610 Spanish firms for the period 2006 to 2010. This research represents the first-ever work conceptualizing and empirically testing a nonlinear, cubic relationship between human asset quality and small and medium-sized family enterprises’ internationalization levels. We find an S-shaped relationship between both general and specialized human assets and the level of export intensity.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".