A geographic relational perspective on the internationalization of emerging market firms
Bibliographic record
Abstract
Abstract The growth of outward foreign direct investment from emerging markets has led to increased scholarly attention on the internationalization of emerging market firms (EMFs). We break from the recent strategic approach on internationalizing EMFs to develop a problematization approach, which permits us to introduce a geographic relational perspective. We use this perspective to highlight process thinking, complex social realities, and relational practice as means by which to better develop theory on the internationalization of EMFs. Our emergent approach emphasizes the need to view EMF internationalization as deeply situated in multifaceted contextual influences, as influenced by path dependence and as manifested in practice. These three relational tenets (contextuality, path dependence, and practice) are central to our geographic relational approach’s ability to generate new challenging research questions for understanding EMF internationalization. Consequently, we add novelty to the international business domain by bringing space and process to the forefront of the EMF research agenda.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".