Early Internationalization: A Meta‐Analysis of Antecedents, Dimensions, and Performance
Bibliographic record
Abstract
Abstract More than three decades after Oviatt and McDougall’s pioneering 1994 paper ‘Towards a theory of international new ventures’, the study of early internationalizing firms continues to captivate international business scholars. The research questions we address involve the antecedents of early internationalization, the dimensions of this phenomenon and its performance outcomes. In the present study, we include all three issues in a comprehensive meta‐analysis, thereby gaining a more complete understanding of the early internationalization process while building upon the various partial pathways identified in extant research. We use meta‐analytic structural equation modelling (MASEM) and build upon 426 samples from 378 empirical studies. We distinguish between the effects of individual‐level and firm‐level antecedents on the main dimensions of early internationalization – speed, scope, and intensity – and we assess the impact thereof on post‐entry performance. Our results provide a comprehensive overview of the constructs used in prior research, thereby laying the foundation for future empirical studies on early internationalization.
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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 | 0.056 | 0.105 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.018 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".