Formal international contracts in the presence of cultural distance: An empirical analysis of biopharmaceutical alliances
Bibliographic record
Abstract
Formal contracts are designed to manage the moral hazard issues and inherent risks that come with relationships between organizations. These contracts play an important role in nonequity international alliances, where greater cultural distance between the partners gives rise to more uncertainty in the relationship. At the same time, the contract is the outcome of a negotiation process, and this process is affected by the cultural distance between the partners. This article addresses whether cultural distance affects contract design and content. Rather than test an established model, we use an inductive approach to conduct a detailed empirical analysis of 135 two‐party international research‐and‐development contracts for clinical development in the biopharmaceutical industry. The results show that cultural distance wields complex effects on the contract and its content. They also indicate that a contract will be less detailed—with fewer monitoring clauses and a narrower definition of the collaborative scope—when the partnering firms operate in highly distant national cultures.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".