The DOI matches its Crossref record; 82 of the 82 references it cites were found in a registry or an index.
The Impact of Performance Management on Performance in Public Organizations: A Meta‐Analysis
Open accessAbstract
Performance‐based management is pervasive in public organizations; countless governments have implemented performance management systems with the hope that they will improve organizational effectiveness. However, there has been little comprehensive review of their impact. This article conducts a meta‐analysis on the impact of performance management on performance in public organizations. It contributes to the current literature in three ways. First, it examines the effect of the “average” performance management system. Second, it examines the influence of management: whether beneficial performance management practices moderate the average effect. Third, it examines the effect of “time” on performance management. Using 2,188 effects from 49 studies, the analysis finds that performance management has a small average effect. However, the effect is substantially larger when indicators of best practices in high‐quality studies are included, indicating that management practices have an important impact on the effectiveness of performance management systems. Evidence for the effect of time is mixed.
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Cites
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Does Strategic Planning Improve Organizational Performance? A Meta‐Analysis
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Johnsen, Å., Solholm, K., & Tufte, P. A. (2024) · Public Performance & Management Review · doi:10.1080/15309576.2024.2360158 · Cited by 32
Metadata
- Authors
- Gerrish, E.
- Venue
- Public Administration Review
- Publisher
- Wiley
- Published
- 2015-08-18
- Volume
- 76
- Issue
- 1
- Pages
- 48-66
- ISSN
- 0033-3352 (ISSN-L)
- 1540-6210
- OpenAlex
- W3124136940
- Cited by
- 319
- References
- 82
- FWCI
- 47.11
- Type
- journal article
- Language
- en
- Open access
- green
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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.
