Governance and Management of Collective User‐Based Enterprises: Value‐Creation Strategies and Organizational Configurations
Bibliographic record
Abstract
Abstract The evolution of the collective enterprise may be conceptualized in three phases throwing into relief five strategies for the creation of value. The first corresponds to the emergence of a collective enterprise, an innovation in itself. The second, the spread of the innovation by replication, is linked to federalization and to the beginning of standardization. The tension between innovation and standardization begin to make a difference as early as this replication phase, but later it becomes more critical. It forces the collective enterprise to avoid wholesale standardization, an outmoded option, and instead allows space for considering one of the two strategies for the creation of value in keeping both with its distinctive social economy identity and with the new strategic approaches centred on the competences of the enterprise and the creation of value for the user. Thus, the collective user enterprise may move forward by focusing, i.e., by even greater innovation in its provision for a target group of members. The collective enterprise may also progress by hybridization, i.e., through re‐combining in a better way the innovation and standardization required to respond, effectively and efficiently, to a group of owners that is not only very large, but also highly diversified. The authors identify the organizational configuration for each pattern of value‐creation by concentrating on governance structures and the role of managers.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".