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Cited by 331

The DOI matches its Crossref record; 134 of the 134 references it cites were found in a registry or an index.

The Grateful Workplace: A Multilevel Model of Gratitude in Organizations

Fehr, Ryan, Fulmer, Ashley, Awtrey, Eli, Miller, Jared A.·2017·Academy of Management Review

Abstract

Gratitude is a valuable emotion with an array of functional outcomes. Nonetheless, research on gratitude in organizations is limited. In this article we develop a multilevel model of gratitude composed of episodic gratitude at the event level, persistent gratitude at the individual level, and collective gratitude at the organizational level. We then consider the types of human resource initiatives that organizations can develop to cultivate employee gratitude and the contingencies of gratitude’s emergence at the individual and organizational levels of analysis. Finally, we elucidate the benefits of gratitude for organizations and their employees. The result is a deeper understanding of how gratitude unfolds in organizations and the role that organizations themselves can play in influencing emotions at multiple levels in the workplace.

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Crossref · 10.5465/amr.2014.0374

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Metadata

Authors
Fehr, R., Fulmer, A., Awtrey, E., & Miller, J. A.
Venue
Academy of Management Review
Published
2017-04
Volume
42
Issue
2
Pages
361-381
ISSN
  • 0363-7425 (ISSN-L)
  • 1930-3807
OpenAlex
W2337926682
Cited by
331
References
134
FWCI
26.97
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Grateful Workplace: A Multilevel Model of Gratitude in Organizations. https://app.cochat.ai/papers/10.5465/amr.2014.0374
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Fehr, R., Fulmer, A., Awtrey, E., & Miller, J. A. (2017). The Grateful Workplace: A Multilevel Model of Gratitude in Organizations. Academy of Management Review. https://doi.org/10.5465/amr.2014.0374

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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.