Value Creation Tension in Coopetition: Virtuous and Vicious Cycles
Bibliographic record
Abstract
Intent to create value is the raison d'être for participation in coopetition, but the complexitiesand challenges of value creation are poorly understood relative to other areas of the coopetitionliterature. Our essay highlights how simultaneous efforts to pursue firm value creation and jointvalue creation leads to challenges and unique tension in coopetition. We develop the conceptof ‘value creation tension’ to explain how efforts towards firm value creation in coopetitioncan undermine joint value creation and vice versa. We also demonstrate how such tensionmanifests in challenges faced by managers, in terms of cognition, behaviour, and emotion.Drawing from the paradox literature, we suggest that attempts to resolve, manage, ormanipulate tension may reinforce the positives, leading to virtuous cycles, or negatives, leadingto vicious cycles. Our essay offers foundations for addressing a critical but currentlyunderexplored tension in coopetition; offering avenues for future research within and beyondthe coopetition literature.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.041 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".