Towards the Business Federation in Top Management Consulting in Europe: The Role of Co-creation
Bibliographic record
Abstract
We present the business federation as a new organizational form. We illustrate how management consulting firms can achieve economic growth through operating locally within an international network. We use management consulting firms operating in Western Europe as our empirical setting. Within the business federation local offices gain access to resources through an extreme form of delegation as it is not top management that delegates to local offices but rather local units that give top management the permission to handle certain tasks because it is most efficient to do so. Using questionnaire as instrument, the article illustrates how the business federation is supposed to function through the use of five organizational design parameters. The research shows a support for the claim that firms that operate close to principles of the business federation achieve a stronger economic growth than other firms operating further away from the federation, using profits per partner as the criteria. Firms that started out from strategy consulting achieve a higher growth rate than other firms. The research contradicts claims found in the academic literature as alternatives to the partnership model supports economic growth.
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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 | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.002 |
| 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".