CEO ethical leadership as a unique source of substantive and rhetorical ethical signals for attracting job seekers: The moderating role of job seekers' moral identity
Bibliographic record
Abstract
Summary Research suggests that CSR is increasingly becoming an ambiguous signal of ethical information for external stakeholders. This is because a variety of firms—including those that are morally responsible and those that have been implicated in corporate scandals—routinely adopt CSR policies and invest in CSR initiatives. Not surprisingly, this trend has contributed to rising public skepticism of CSR. In the current research, we examine the unique role of CEO ethical leadership (i.e., relative to CSR) as an alternate source of substantive and rhetorical ethical signals for an important stakeholder group: job seekers. Integrating signaling theory, and the elaboration likelihood model, we argue that CEO ethical leadership substantively signals how fairly an organization treats its employees and its commitment to social and environmental responsibility. We further propose that ethical CEOs serve as a source of rhetorical signal that triggers moral elevation in job seekers. Using a policy capturing methodology in Study 1, we find that real job seekers place significantly greater weight on CEO ethical leadership in making job pursuit decisions compared to CSR. CEO ethical leadership also uniquely predicts job pursuit intentions relative to traditional factors such as salary, person‐job fit, and person‐organization fit. In a second, quasi‐experimental field study (Study 2), we find support for the three hypothesized signaling mechanisms through which CEO ethical leadership influences job seekers. In a third, quasi‐experimental field study (Study 3), we find that job seekers with strong (versus weak) moral identities are more likely to weigh the nuanced ethical information signaled by CEO ethical leadership compared to CSR. We discuss the implications of proactively advertising CEO ethical leadership during the recruitment process.
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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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".