Complementarity of Performance Pay and Task Allocation
Bibliographic record
Abstract
Complementarity between performance pay and other organizational design elements has been argued to be one potential explanation for stark differences in the observed productivity gains from performance pay adoption. Using detailed data on internal organization for a nationally representative sample of firms, we empirically test for the existence of complementarity between performance pay incentives and decentralization of decision-making authority for tasks. To address endogeneity concerns, we exploit regional variation in income tax progressivity as an instrument for the adoption of performance pay. We find systematic evidence of complementarity between performance pay and decentralization of decision making from principals to employees. However, adopting performance pay also leads to centralization of decision-making authority from nonmanagerial to managerial employees. The findings suggest that performance pay adoption leads to a concentration of decision-making control at the managerial employee level, as opposed to a general movement toward more decentralization throughout the organization. This paper was accepted by Bruno Cassiman, business strategy.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".