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Cited by 441

The DOI matches its Crossref record; 86 of the 86 references it cites were found in a registry or an index.

Overpaid CEOs and Underpaid Managers: Fairness and Executive Compensation

Wade, James B., O'Reilly, Charles A., Pollock, Timothy G.·2006·Organization Science

Abstract

In this study we propose that norms of fairness are salient to top decision makers and show that over- or underpayment of the CEO cascades down to lower organizational levels. Moreover, it appears that CEOs use their own power not only to increase their own salaries, but also those of their subordinates. One implication of such a process may be that the overpayment of a top executive has higher costs than have previously been realized. We also find evidence suggesting that CEOs serve as a key referent for employees in determining whether their own situation is “fair,” and this influences their reactions to their own compensation. More specifically, we find that when lower-level managers are underpaid relative to the CEO—that is, underpaid more than the CEO or overpaid less—they are more likely to leave the organization. Results obtained from testing our hypotheses on a sample of more than 120 firms over a five-year period demonstrates the importance of considering fairness in the setting of CEO pay. Implications for the design of executive compensation packages are discussed.

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Metadata

Authors
Wade, J. B., O'Reilly, C. A., & Pollock, T. G.
Venue
Organization Science
Published
2006-10
Volume
17
Issue
5
Pages
527-544
ISSN
  • 1047-7039 (ISSN-L)
  • 1526-5455
OpenAlex
W2146360602
Cited by
441
References
86
FWCI
17.94
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Overpaid CEOs and Underpaid Managers: Fairness and Executive Compensation. https://app.cochat.ai/papers/10.1287/orsc.1060.0204
The paper
Wade, J. B., O'Reilly, C. A., & Pollock, T. G. (2006). Overpaid CEOs and Underpaid Managers: Fairness and Executive Compensation. Organization Science. https://doi.org/10.1287/orsc.1060.0204

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.