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The DOI matches its Crossref record; 87 of the 87 references it cites were found in a registry or an index.

Employee well‐being in organizations: Theoretical model, scale development, and cross‐cultural validation

Zheng, Xiaoming, Zhu, Weichun, Zhao, Haixia, Zhang, Chi·2015·Journal of Organizational Behavior

Abstract

Summary: In this study, we explore the theoretical model and structural dimensions of employee well‐being (EWB) in organizations. Specifically, using both qualitative and quantitative methods, we find that EWB comprises three dimensions: life well‐being, workplace well‐being, and psychological well‐being. We establish the reliability and validity of the newly developed EWB scale through a series of quantitative studies, which indicate that EWB is significantly correlated with affective organizational commitment and job performance based on the data collected from multiple sources at two points in time. We find that EWB has measurement invariance (configural invariance) across Chinese and American contexts. We also discuss the theoretical contributions of these findings to cross‐cultural organizational behavior studies, along with the practical implications of our results. Copyright © 2015 John Wiley & Sons, Ltd.

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Metadata

Authors
Zheng, X., Zhu, W., Zhao, H., & Zhang, C.
Venue
Journal of Organizational Behavior
Publisher
Wiley
Published
2015-01-25
Volume
36
Issue
5
Pages
621-644
ISSN
  • 0894-3796 (ISSN-L)
  • 1099-1379
OpenAlex
W1863216925
Cited by
716
References
87
FWCI
15.85
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Employee well‐being in organizations: Theoretical model, scale development, and cross‐cultural validation. https://app.cochat.ai/papers/10.1002/job.1990
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Zheng, X., Zhu, W., Zhao, H., & Zhang, C. (2015). Employee well‐being in organizations: Theoretical model, scale development, and cross‐cultural validation. Journal of Organizational Behavior. https://doi.org/10.1002/job.1990

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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.