Creating and taming discord: How firms manage embedded competition in alliance portfolios to limit alliance termination
Bibliographic record
Abstract
Research Summary : Firms with resources that make them attractive allies are also desirable partners for competitors so that competition among partners is embedded in alliance portfolios. We develop a framework in which competition within a portfolio creates benefits for a focal firm but threatens partners, increasing the hazard of alliance termination. We then propose four mechanisms for managing the threat of competition to partners reflecting aspects of portfolio configuration: alliance governance, social cohesion, social structure of competition, and partner similarity. We test our framework using a sample of 204 biopharmaceutical firms with alliance portfolios comprising 1,621 alliances between 1990 and 2000. The study addresses the interplay of competition and cooperation in alliance portfolios, and more generally, key aspects of value chain integration strategy. Managerial Summary : Alliance portfolios comprise a focal firm's set of direct partners, some of which compete with each other because of overlapping resources, capabilities, and strategies. The threat of actual or perceived competition from other partners may cause some firms to terminate their alliance with the focal firm. We develop a framework comprising four mechanisms related to alliance portfolios—alliance governance, social cohesion, social structure of competition, and partner similarity—that allows focal firms to attenuate the hazard of termination of their alliances. We find support for our framework in a study of 204 biopharmaceutical firms with alliance portfolios comprising 1,621 alliances between 1990 and 2000. We improve understanding of how firms can manage competition and cooperation within their alliance portfolios.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".