The Two Facets of Collaboration: Cooperation and Coordination in Strategic Alliances
Bibliographic record
Abstract
This paper unpacks two underspecified facets of collaboration: cooperation and coordination. Prior research has emphasized cooperation, specifically partners' commitment and alignment of interests, as the key determinant of collaborative success. Scholars have paid less attention to the critical role of coordination—the effective alignment and adjustment of partners' actions. To redress this imbalance, we conceptually disentangle cooperation and coordination in the context of inter-organizational collaboration, and examine how the two phenomena play out in the partner selection, design, and post-formation stages of an alliance's life cycle. As we demonstrate, a coordination perspective helps resolve some empirical puzzles, but it also represents a challenge to received wisdom grounded in the salience of cooperation. To stimulate future research, we discuss alternative conceptualizations of the relationship between cooperation and coordination, and elaborate on their normative implications.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.026 |
| Scholarly communication | 0.013 | 0.019 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".