Understanding the Role of Perceived CEO Narcissism Through the Agency-Communion Model
Bibliographic record
Abstract
Employees’ active involvement with the strategy formation process has been thought to be crucial for organizational recovery from the crisis. However, little is known about what shapes employees’ perceptions about the crisis and organization, fostering trust in employees and motivating such behaviors. Drawing from the recent stakeholder view of upper echelons, we propose that a characteristic that people readily detect from CEOs—CEO narcissism—can be a key determinant of employees’ decision to involve with strategy formation process. Specifically, we examine two different presentation styles of narcissism—communal and agentic narcissism—and reveal their nuanced effects. We predict that employees’ perception of communal (agentic) narcissism in their CEOs has positive (negative) relationships with involvement in strategy formation via organizational trust. We also posit that, when employees attribute crisis internally to an organization to a greater degree, these relationships are further amplified. We tested our hypotheses across two studies, involving 258 employees (Study 1; online survey) from US, Canada, and the UK and 77 employees (Study 2; field survey) enrolled in an advanced degree program in a major U.S. university. Results generally supported our hypotheses.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".