Reputation, Diversification, and Organizational Explanations of Performance in Professional Service Firms
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
Growing interest in knowledge as a competitive asset suggests the benefit of studying professional service firms (PSFs). These firms are highly successful examples of organizations whose ability to manage knowledge is critical to their success. Furthermore, they are worthy of study because they constitute a significant sector of the economy, whether measured by their size, numbers, or influence. Despite their significance, little is known of the determinants of their performance. This paper proposes that the core tasks of PSFs raise unusual strategic and organizational challenges, the resolution of which affects organizational performance. We elaborate the effects of reputation and diversification and contrast them to theory for goods-producing industries. We also hypothesize that PSF managers face a choice in designing structures between the retention and motivation of the professional workforce and transferring knowledge from partners to other professionals. These predictions are tested and supported by data from the largest 100 U.S. accounting firms for the period 1991–2000. The paper thus contributes to a theory of professional service firm management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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