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Cited by 478

The DOI matches its Crossref record; 203 of the 203 references it cites were found in a registry or an index.

A High Performance Work Practices Taxonomy: Integrating the Literature and Directing Future Research

Posthuma, Richard A., Campion, Michael C., Masimova, Malika, Campion, Michael A.·2013·Journal of Management

Abstract

High Performance Work Systems are designed to enhance organizational performance by improving employee capability, commitment, and productivity. Yet there is very little consensus about the structure of these systems and the practices therein. The lack of structure may be inhibiting the growth of knowledge in this field and the degree to which organizations adopt these systems. To address these concerns we develop a comprehensive High Performance Work Practices (HPWPs) taxonomy. We analyzed 193 peer-reviewed articles published over the past 20 years (1992-2011). We classified 61 specific practices into nine categories. We analyze the usefulness of this taxonomy using frequency, time, and countries. Directions for future research are provided.

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Metadata

Authors
Posthuma, R. A., Campion, M. C., Masimova, M., & Campion, M. A.
Venue
Journal of Management
Published
2013-03-19
Volume
39
Issue
5
Pages
1184-1220
ISSN
  • 0149-2063 (ISSN-L)
  • 1557-1211
OpenAlex
W2152167791
Cited by
478
References
203
FWCI
69.79
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A High Performance Work Practices Taxonomy: Integrating the Literature and Directing Future Research. https://app.cochat.ai/papers/10.1177/0149206313478184
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Posthuma, R. A., Campion, M. C., Masimova, M., & Campion, M. A. (2013). A High Performance Work Practices Taxonomy: Integrating the Literature and Directing Future Research. Journal of Management. https://doi.org/10.1177/0149206313478184

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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.