The accentuated CEO career horizon problem: evidence from international acquisitions
Bibliographic record
Abstract
Abstract We develop a conceptual model of the career horizon problem of CEOs approaching retirement and discuss its implications on firm risk taking, specifically in engagement in international acquisitions. Based on prospect theory and agency theory, we emphasize the legacy conservation and wealth preservation concerns of CEOs and investigate how their holdings of in‐the‐money unexercised options and firm equity accentuate or mitigate the career horizon problem. The model is tested in the context of international acquisitions with a sample of 293 U.S. firms over a five‐year period (1995–1999). We find that a longer CEO career horizon is associated with a higher likelihood of international acquisitions. We also find that CEOs nearing retirement with high levels of in‐the‐money unexercised options and equity holdings are less likely to engage in international acquisitions than CEOs with low levels of in‐the‐money options and equity holdings. The study raises important considerations about the implications of CEOs' equity and in‐the‐money option holdings on firm risk taking at various stages of their career horizon. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".