Managing team coordination incentives: the effect of payoff differentials
Bibliographic record
Abstract
Purpose The current paper aims to present a formal model illustrating how payoff imbalances among the members of a team of decision makers (DMs) who must undertake a project condition the final outcome obtained. This result builds on the fact that payoffs imbalances would lead to different performance levels among the employees and managers who compose a team. The analysis is applied to a strategic environment, where a project requiring coordination among the DMs within the team must be developed. Design/methodology/approach The intuition behind the strategic framework on which the results are based is twofold. The authors build on the literature on social comparisons and assume that employees and managers acquire information on the payoffs received by other members of the team while being affected by the resulting comparisons, and they follow the economic literature on firm boundaries determined via incomplete contracts. In this case, employees and managers may underperform if they feel aggrieved by the outcome of the contract giving place to deadweight losses when developing the project. Findings The authors illustrate how a team-based performance reward structure may lead to a coordinated equilibrium even when team managers and employees receive different payoffs and exhibit shading incentives based on the payoff differentials between them. The authors will also illustrate how identical shading intensities by both groups of DMs imply that shading by the managers imposes a lower cost on the profit structure of the firm because it leads to a lower decrease in the cooperation incentives of the other members of the team. Finally, the authors show how differences in shading intensity between both types of DMs trigger a strategic defect mechanism within the team that determines the outcome of the project. Originality/value The novel environment of team cooperation and defection through shading introduced in this paper is designed to deal with the strategic decisions taken by DMs when undertaking a project within a group. In particular, the intensity of shading applied by the DMs will be endogenously determined by the relative payoffs received, which allows to account for different scenarios, where relative payoff differentials among DMs determine the outcome of the project.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".