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Cited by 742

The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.

Beyond Motivation: Job and Work Design for Development, Health, Ambidexterity, and More

Open access
Parker, Sharon K.·2014·Annual Review of Psychology

Abstract

Much research shows it is possible to design motivating work, which has positive consequences for individuals and their organizations. This article reviews research that adopts this motivational perspective on work design, and it emphasizes that it is important to continue to refine motivational theories. In light of continued large numbers of poor-quality jobs, attention must also be given to influencing practice and policy to promote the effective implementation of enriched work designs. Nevertheless, current and future work-based challenges mean that designing work for motivation is necessary but insufficient. This review argues that work design can be a powerful vehicle for learning and development, for maintaining and enhancing employees' physical and mental health, and for achieving control and flexibility simultaneously (for example, in the form of ambidexterity); all these outcomes are important given the challenges in today's workplaces. The review concludes by suggesting methodological directions.

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Metadata

Authors
Parker, S. K.
Venue
Annual Review of Psychology
Published
2014-01-03
Volume
65
Issue
1
Pages
661-691
ISSN
  • 0066-4308 (ISSN-L)
  • 1545-2085
OpenAlex
W2121272057
Cited by
742
References
20
FWCI
6.66
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Beyond Motivation: Job and Work Design for Development, Health, Ambidexterity, and More. https://app.cochat.ai/papers/10.1146/annurev-psych-010213-115208
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Parker, S. K. (2014). Beyond Motivation: Job and Work Design for Development, Health, Ambidexterity, and More. Annual Review of Psychology. https://doi.org/10.1146/annurev-psych-010213-115208

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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.