Collaborative Market Driving: How Peer Firms Can Develop Markets Through Collective Action
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Firms often aim to develop markets as part of their long-term strategies. Conventionally, research in marketing has explained this complex process by stressing firms’ efforts to outdo their peers. While this emphasis is valuable, it overlooks the role of another major force in market evolution: collective action among peer firms. To address this oversight, this article conceptualizes “collaborative market driving,” defining it as the collective strategy in which peer firms consistently cooperate among themselves and with other actors to develop markets in ways that increase their overall competitiveness. This conceptualization includes the triggers that lead peer firms to mobilize for collective action and coalesce with other market actors; it also identifies how this coalition converts collective resources into market-driving power. These theoretical contributions, based on a multimethod analysis of the rise of U.S. craft breweries, offer an alternative course of action for firms interested in driving new markets when they lack adequate resources to do so individually.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it