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Cited by 490

The DOI matches its Crossref record; 98 of the 98 references it cites were found in a registry or an index.

Personnel Psychology: Performance Evaluation and Pay for Performance

Rynes, Sara L., Gerhart, Barry, Parks, Laura·2005·Annual Review of Psychology

Abstract

Although there is a voluminous psychological literature on performance evaluation (PE), surprisingly little of this research examines the consequences of linking pay to evaluated performance in work settings. Rather, PE research has been dominated by cognitive processing, measurement, and construct validity issues. At the same time, a large literature on pay-for-performance (PFP) linkages does exist, but most of it has been conducted in disciplines other than psychology. We think this pattern should change. To this end, we briefly trace the origins of the general separation of PE research from PFP research in psychology. From there, we review recent research on the relationship between PE and performance improvement, particularly with respect to multisource or 360-degree evaluation. We then turn to research on various PFP systems, such as merit pay and individual and group incentives. We conclude with suggestions as to how psychological research can make useful contributions to knowledge of PE, PFP, and performance improvement.

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Crossref · 10.1146/annurev.psych.56.091103.070254

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Metadata

Authors
Rynes, S. L., Gerhart, B., & Parks, L.
Venue
Annual Review of Psychology
Published
2005-02-01
Volume
56
Issue
1
Pages
571-600
ISSN
  • 0066-4308 (ISSN-L)
  • 1545-2085
OpenAlex
W2101696501
Cited by
490
References
98
FWCI
4.80
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Personnel Psychology: Performance Evaluation and Pay for Performance. https://app.cochat.ai/papers/10.1146/annurev.psych.56.091103.070254
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Rynes, S. L., Gerhart, B., & Parks, L. (2005). Personnel Psychology: Performance Evaluation and Pay for Performance. Annual Review of Psychology. https://doi.org/10.1146/annurev.psych.56.091103.070254

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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.