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Cited by 505

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Capitalizing on Paradox: The Role of Language in Transforming Organizational Identities

Fiol, C. Marlene·2002·Organization Science

Abstract

A strongly identified workforce presents a paradox during times of radical organizational change. Though it may bind people together behind the change initiative, strong organizationwide identification often blinds and potentially blocks the view of new possibilities. Prior research on identity change has tended to either ignore the paradox or resolve it by advocating some middle ground such as hybrid organizational identities or group-level identifications. This paper presents an identity transformation model that capitalizes on the paradoxical tensions over time by unpacking the processes by which individual and organizational levels of identity interact. It operationalizes the model by suggesting linguistic markers that describe the different stages of the process and rhetorical techniques that leaders can use to guide people through the process. To illustrate the model and its application, the paper highlights moments across a 10-year period at Tech-Co, a high-technology company undergoing a significant identity transformation.

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Metadata

Authors
Fiol, C. M.
Venue
Organization Science
Published
2002-12
Volume
13
Issue
6
Pages
653-666
ISSN
  • 1047-7039 (ISSN-L)
  • 1526-5455
OpenAlex
W2022919863
Cited by
505
References
4
FWCI
21.14
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Capitalizing on Paradox: The Role of Language in Transforming Organizational Identities. https://app.cochat.ai/papers/10.1287/orsc.13.6.653.502
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Fiol, C. M. (2002). Capitalizing on Paradox: The Role of Language in Transforming Organizational Identities. Organization Science. https://doi.org/10.1287/orsc.13.6.653.502

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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.