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Cited by 324

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

Justice, Fairness, and Employee Reactions

Colquitt, Jason A., Zipay, Kate P.·2015·Annual Review of Organizational Psychology and Organizational Behavior

Abstract

Of all the issues that employees consider in organizational life, justice and fairness are among the most salient. Justice reflects the perceived adherence to rules that represent appropriateness in decision contexts (e.g., equity, consistency, respect, truthfulness). Fairness reflects a more global perception of appropriateness that lies downstream of justice. Our review integrates justice theories (fairness heuristic theory, the relational model, the group engagement model, fairness theory, deonance theory, uncertainty management theory) and broader theories (social exchange theory, affective events theory) to examine three questions: (a) Why do employees think about justice issues in the first place? (b) how do employees form fairness perceptions? and (c) how do employees react to those perceptions? We close by describing how justice and fairness can be managed in organizations, especially given new technological trends in how people work.

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Crossref · 10.1146/annurev-orgpsych-032414-111457

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Metadata

Authors
Colquitt, J. A., & Zipay, K. P.
Venue
Annual Review of Organizational Psychology and Organizational Behavior
Published
2015-04-10
Volume
2
Issue
1
Pages
75-99
ISSN
  • 2327-0608 (ISSN-L)
  • 2327-0616
OpenAlex
W2087245834
Cited by
324
References
11
FWCI
7.01
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Justice, Fairness, and Employee Reactions. https://app.cochat.ai/papers/10.1146/annurev-orgpsych-032414-111457
The paper
Colquitt, J. A., & Zipay, K. P. (2015). Justice, Fairness, and Employee Reactions. Annual Review of Organizational Psychology and Organizational Behavior. https://doi.org/10.1146/annurev-orgpsych-032414-111457

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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.