Investigations on the growth of early internationalizing firms
Bibliographic record
Abstract
This dissertation presents investigations on the existence and growth of early internationalizing firms. The thesis is structured in essays. The first essay explores the evolution of early internationalization literature in the last decade, through a systematic review of articles published in leading journals on this topic. Emerged almost thirty years ago, the literature on early internationalization has evolved rapidly, rising the interest of both academics and policy makers. The article finally provides a thematic map serving as a starting point for academics approaching this issue. \nThe second essay presents an exploratory qualitative research aimed at investigating the growth processes of six Italian manufacturing born globals. Among early internationalizing firms, born globals are young companies that enter foreign markets soon and rapidly increase their presence abroad. These companies have captured the interest of academics because they get the jump on larger, established players in the marketplace. The study provides several insights on how the success factors that influence the growth of these companies change during their lifecycles. \nThe third and final essay examines the drivers of performance among a sample of Italian manufacturing exporting small and medium sized firms, by considering drivers at the individual, firm and strategic levels. Results show that internationally experienced founders, organizational marketing skills in international markets and an aggressive approach towards international markets drive companies to superior performances. Practical implications and future research directions are discussed.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".