International new ventures: Beyond definitional debates to advancing the cornerstone of international entrepreneurship
Bibliographic record
Abstract
International entrepreneurship—the field dedicated to the discovery, enactment, evaluation, and exploitation of opportunities across national borders to create future goods and services—is as inextricably linked to firm activity as entrepreneurship, strategy, or international business. However, for much of the past 30 years the field has been hampered by confusion and inconsistency over definitions and existential questions such as, “What is a born global?”; “what is an international new venture?”; and “how does one distinguish emerging firm types?” While many of these questions have been previously answered in isolation, confusion remains, as the field lacks a coherent unified perspective of firm activity. In this introduction to our thematic issue on international entrepreneurship, we address this need, present a unified model of international new ventures drawn from the latest definitions and distinctions, and call for future research that fully integrates form into the conversations of opportunity, technology, liability, and the unique network and value-chain alignments that exist across borders. We also discuss how we can better integrate and add value to nascent trends more broadly from neuroscience, deglobalization, intercultural arbitrage, and other areas.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.037 |
| Scholarly communication | 0.021 | 0.030 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.009 |
| 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".