Firm performance as a mediator of the relationship between CEO narcissism and positive rhetorical tone
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine how chief executive officers’ (CEOs) narcissism impacts firm performance and how this, in turn, affects a CEO’s positive rhetorical tone. Design/methodology/approach The narcissism score is measured by using an analytical composite score for each CEO based on eight factors. The paper uses textual analysis on a sample of 848 CEO letters of US firms over the period 2010–2019. WarpPLS software, version 7.0 was used to conduct structural equation modeling through the partial least squares because a non-linear algorithm exists between CEO narcissism, firm performance and positive tone, and the values of path coefficients moved from non-significant to significant. Findings The results suggest that performance partially mediates the relationship between CEO narcissism and positive tone. This indicates that not all the positivity expressed by narcissistic CEOs is opportunism; some of it is indeed driven by better performance. The reported findings indicate that firm performance explains one-quarter of a CEO’s positive words, whereas some three-quarters of the positivity is driven by a narcissistic CEO (i.e. opportunism). A comparison of letters signed by highly narcissistic and less narcissistic leaders reveals that among those letters signed by highly narcissistic leaders, firm performance plays a significant mediating role between narcissistic tendencies and positive tone. However, among those with less narcissistic score, there is no evidence that performance mediates the tone and narcissism. Interestingly, both highly narcissistic and less narcissistic CEOs use positive words and optimistic expressions even when their firms perform poorly or negatively. Research limitations/implications The results help shareholders be aware that CEOs may opportunistically use their personal characteristics and language to manipulate them. Data limitations about women CEOs were one of the reasons behind the small proportion of women CEOs in this study, making it low in generalizability. Originality value A comprehensive review showed that none of previous studies examined the more ambiguous relationship between a CEO’s narcissist tendency, the firm’s performance, and CEO rhetorical tone. As one set of studies focused on Narcissism → Performance, and the other one on Performance → Tone, this current study completes the picture with Narcissism → Performance → Tone.
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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 | 0.004 | 0.009 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".