Equity‐based incentives and collaboration in the modern multibusiness firm
Bibliographic record
Abstract
Research summary : This paper examines the role of equity‐based incentives in fostering cross‐business‐unit collaboration in multibusiness firms. We develop a formal agency model in which headquarters offers equity and profit incentives to business‐unit managers with the objective of maximizing total expected firm returns. The resulting compensation contract provides a rich mechanism for aggregating value from collaborative interactions across business units, aligning managers' efforts with the firm's growth prospects and organization structure and managing the dual risks in profits and firm market value. The inclusion of equity incentives elicits higher levels of own‐unit and collaborative efforts over the profits‐only contract. Our results suggest that equity‐based incentives are most beneficial when profitability is uncertain relative to long‐term growth prospects, in firms pursuing related diversification strategies, and in periods of rising equity markets. Managerial summary : Equity‐based compensation such as restricted stock grants and options are increasingly common, not only for CEOs and other top executives, but also for business unit managers and other non‐ C‐s uite employees. The paper studies the role of such “global” incentives in enabling multibusiness firms to benefit from cross‐unit collaboration. Results from our model show that managerial contracts that include appropriate levels of equity incentives, in addition to profit‐based incentives, generate higher own‐unit and collaborative efforts. We also find that equity incentives are likely to be most beneficial for large firms in high‐growth sectors, for firms pursuing a related diversification strategy, and in periods of rising stock markets. The model can also provide useful guidance on designing return‐maximizing compensation contracts for business unit managers in different firm, organizational, and industry contexts. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.001 | 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 | 0.001 | 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".