SME Internationalization in Emerging Markets: Formal Institutions and Foreign Market Entry Strategy
Bibliographic record
Abstract
Extant research pertaining to the relationship between formal institutions and the governance of equity-based subsidiary investments (wholly-owned subsidiary, or joint venture (JV) partnership) established by small-to-medium sized enterprises (SMEs) in foreign markets has generated equivocal results. To reconcile these disparate findings, we propose a more fine-grained conceptualization of the formal institutions construct. To do so, we employ an uncertainty-grounded lens to categorize formal institutions in terms of the distinct varieties of uncertainty (environmental versus behavioral) and transaction costs (information costs versus monitoring and enforcement costs) that they foster. More specifically, we theorize that formal institutions can be unbundled into environmentally-oriented formal institutions (EOFI) and behaviorally-oriented formal institutions (BOFI). We detail the distinct transaction cost-reduction mechanisms through which these two different types of formal institutions impact upon the equity-based governance choices of foreign-investing entrepreneurial firms in emerging markets. In brief, we propose that weaker BOFI foster both greater behavioral uncertainty and heightened monitoring and enforcement costs for these firms which will precipitate a preference for full ownership. Conversely, weaker EOFI induce greater environmental uncertainty and more pronounced information costs which will motivate these investors to engage in a JV with a local partner. The results of our tests of these hypotheses provide empirical support for the main effects of EOFI and BOFI, but only partial support for our hypothesis pertaining to the interaction effect between these two categories of formal institutions.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| 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".