IJV Partner Trustworthy Behaviour: The Role of Host Country Governance and Partner Selection Criteria
Bibliographic record
Abstract
abstract This study provides new insight into the interplay between partner‐ and institution‐level bases of trustworthy behaviour in international joint ventures (IJVs). The results of the study, based on survey and archival data collected on 144 IJVs across six Asian countries, revealed that host country governance quality directly and positively influences IJV partner trustworthy behaviour. It was also found that weak host country governance undermined the effectiveness of certain partner selection criteria in serving as a tool for establishing an IJV with a trustworthy partner. Furthermore, through distinguishing between two dimensions of trustworthiness (benevolence and competence), it was demonstrated that partner benevolence is facilitated by relationship‐oriented criteria, whereas partner competence is facilitated by task‐oriented criteria. The implications of these results for the establishment and management of IJVs are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".