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Cited by 553

The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.

Does Public Service Motivation Really Make a Difference on the Job Satisfaction and Turnover Intentions of Public Employees?

Bright, Leonard·2008·The American Review of Public Administration

Abstract

Many in public administration hypothesize that public service motivation (PSM) has a direct positive impact on the attitudes and behaviors of public employees. However, there are inconsistencies in the PSM literature that challenge this hypothesis. This study sought to find out whether person-organization (P-O) fit can provide a reason for these inconsistencies. Specifically, this study explored whether the relationships among PSM, job satisfaction, and the turnover intentions of public employees were mediated by P-O fit. Using a sample of 205 employees drawn from three public organizations in the states of Oregon, Indiana, and Kentucky, this study found that PSM had no significant relationship to the job satisfaction and turnover intentions of public employees when P-O fit was considered. The implications of this study and areas of future research are discussed.

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Metadata

Authors
Bright, L.
Venue
The American Review of Public Administration
Published
2008-06
Volume
38
Issue
2
Pages
149-166
ISSN
  • 0275-0740 (ISSN-L)
  • 1552-3357
OpenAlex
W1975147895
Cited by
553
References
47
FWCI
51.89
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Does Public Service Motivation Really Make a Difference on the Job Satisfaction and Turnover Intentions of Public Employees? https://app.cochat.ai/papers/10.1177/0275074008317248
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Bright, L. (2008). Does Public Service Motivation Really Make a Difference on the Job Satisfaction and Turnover Intentions of Public Employees? The American Review of Public Administration. https://doi.org/10.1177/0275074008317248

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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.