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Cited by 403

The DOI matches its Crossref record; 82 of the 82 references it cites were found in a registry or an index.

Experimental Evidence on the Relationship between Public Service Motivation and Job Performance

Bellé, Nicola·2013·Public Administration Review

Abstract

This paper responds to recent calls for experimental research into the relationship between public service motivation (PSM) and job performance. We conducted a field experiment on a sample of nurses at a public hospital in Italy to investigate the interplay between job performance, PSM and two conditions – i.e. exposure to contact with beneficiaries and self-persuasion interventions. Both treatments had positive effects on participants’ persistence, output, productivity and vigilance. Baseline PSM strengthened these positive effects. Moreover, both conditions caused an increase in PSM, which partially mediated the positive effects of beneficiary contact and self-persuasion on job performance. We discuss the implications of our experimental findings for both theory and practice.

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Crossref · 10.1111/j.1540-6210.2012.02621.x

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Metadata

Authors
Bellé, N.
Venue
Public Administration Review
Publisher
Wiley
Published
2012-12-05
Volume
73
Issue
1
Pages
143-153
ISSN
  • 0033-3352 (ISSN-L)
  • 1540-6210
OpenAlex
W2017462038
Cited by
403
References
82
FWCI
54.58
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Experimental Evidence on the Relationship between Public Service Motivation and Job Performance. https://app.cochat.ai/papers/10.1111/j.1540-6210.2012.02621.x
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Bellé, N. (2013). Experimental Evidence on the Relationship between Public Service Motivation and Job Performance. Public Administration Review. https://doi.org/10.1111/j.1540-6210.2012.02621.x

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.