Manager narcissism, target difficulty, and employee dysfunctional behavior
Bibliographic record
Abstract
Abstract We examine whether managers' narcissism explains the difficulty of the performance targets that they set for their subordinate employees and the resulting dysfunctional behaviors of these employees. Utilizing a field‐based data set and a government policy change that imposes higher performance standards, we document both direct and indirect associations between manager narcissism and employee dysfunctional behavior. In particular, we find that managers with a higher degree of narcissism respond to the higher performance standards by setting more difficult targets for their subordinates, which in turn lead to more employee dysfunctional behaviors. Furthermore, after controlling for the effect of target difficulty, we find that manager narcissism also has a direct positive association with employee dysfunctional behavior. Our findings contribute to the management accounting literature by documenting that narcissism, a personality trait that is ubiquitous among managers, plays an important role in affecting managers' control choices and the dysfunctional behaviors of lower‐level employees.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".