Estimating Management Practice Complementarity between Decentralization and Performance Pay
Bibliographic record
Abstract
The existence of complementarity across management practices has been proposed as one potential explanation for the persistence of firm-level productivity differences.However, thus far no conclusive population-level tests of the complementary joint adoption of management practices have been conducted.Using unique detailed data on internal organization, occupational composition, and firm performance for a nationally representative sample of firms in the Canadian economy, we exploit regional variation in income tax progression as an instrument for the adoption of performance pay.We find systematic evidence for the complementarity of performance pay and decentralization of decision-making from principals to employees.Furthermore, in response to the adoption of performance pay, we find a concentration of decision-making at the level of managerial employees, as opposed to a general movement towards more decentralization throughout the organization.Finally, we find that adoption of performance pay is related to other types of organizational restructuring, such as greater use of outsourcing, Total Quality Management, re-engineering, and a reduction in the number of layers in the hierarchy.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".