CEO Humility: Development of an Unobtrusive Measure and Strategic Implications
Bibliographic record
Abstract
Over the past 30 years, the Upper Echelons perspective of strategic management has sought to explain a given organization’s strategies and effectiveness as a reflection of the differences in personality, background, and other characteristics of the senior executives that guides each organization. An important stream of research within this field has linked a firm’s strategy to the grandiose way that executives are often thought to view themselves – namely through examining the narcissism, core self-evaluations (CSE), and hubris of Chief Executive Officers (CEOs). In this dissertation, I focus on understanding the strategic impact of CEO humility – a trait that has often been erroneously thought of to represent a poor view of oneself. Consistent with ancient writings and recent research, humility is defined herein as a multi-faceted trait that is the common core of four dimensions: self-awareness, developmental orientation/teachability, appreciation of others' strengths and contributions, and low self-focus. In the first essay, I explore the conceptual relevance and various potential implications of executive humility. Drawing on existing empirical research about the humility construct and general behavioral implications of humility, I argue that executive humility is a critical avenue toward a more rich and nuanced understanding of the delicate interplay and implications of executive self-concept. In essay two, I develop and validate an unobtrusive measure of CEO humility. Ten indicators of humility are suggested and then validated using a self-reported survey administered to a sample of 30 U.S. and Canadian CEOs. Two behaviors were found to be significantly positively related to self-reported humility: CEOs who volunteered some of their time for non-profit organizations and CEO’s who reported that part of their own firm’s success was due to the help of the board of directors. In essay three, I examine the relationship between the level of CEO humility and four firm-level outcomes. Employing a sample of 163 CEOs appointed to S&P 500 firms between 2005-2008, I show that firms led by humble CEOs (measured by the unobtrusive indicators) tend to outperform others in regards to corporate social performance, while at the same time showing that their financial performance is generally no better or worse.
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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 | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".