Performance des partenaires locaux dans les coentreprises internationales en Asie : valorisation boursière et application de la théorie des coûts de transaction
Bibliographic record
Abstract
This article proposes an analysis of the performance of local partners in international joint ventures based on the transaction cost theory. This analysis was conducted within the framework of a sampling of 213 local partners that announced between January 2000 and December 2004, the creation of an international joint venture in one of the following five Asian countries: People's Republic of China, South Korea, Malaysia, Singapore, and Taiwan. First, an event study methodology was used to measure the performance of local partners by calculating their abnormal profitability. Second, multiple regression models were developed in order to test the impact of different explicative variables (cf. control, international joint venture industry, partners' experience, and country risk) on the abnormal profitability of local partners. The different empirical findings contribute to contemplating an analysis of the performance of local partners that is different from that of foreign partners. It also emerges from these findings that the transaction cost theory is a framework for analyzing performance that is more applicable to foreign partners than to local partners in international joint ventures. (PUBLICATION ABSTRACT)
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".