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Cited by 305

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

Emotional Dynamics and Strategizing Processes: A Study of Strategic Conversations in Top Team Meetings

Liu, Feng, Maitlis, Sally·2014·Journal of Management Studies

Abstract

An important but largely unexplored issue in the study of strategy‐as‐discourse is how emotion affects the discursive processes through which strategy is constructed. To address this question, this paper investigates displayed emotions in strategic conversations and explores how the emotional dynamics generated through these displays shape a top management team's strategizing. Using microethnography, we analyse conversations about ten strategic issues raised across seven top management team meetings and identify five different kinds of emotional dynamic, each associated with a different type of strategizing process. The emotional dynamics vary in the sorts of emotions displayed, their sequencing and overall form. The strategizing processes vary in how issues are proposed, discussed, and evaluated, and whether decisions are taken or postponed. We identify team relationship dynamics as a key mechanism linking emotional dynamics and strategizing processes, and issue urgency as another important influence.

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Metadata

Authors
Liu, F., & Maitlis, S.
Venue
Journal of Management Studies
Publisher
Wiley
Published
2013-01-16
Volume
51
Issue
2
Pages
202-234
ISSN
  • 0022-2380 (ISSN-L)
  • 1467-6486
OpenAlex
W2140211181
Cited by
305
References
13
FWCI
18.29
Type
journal article
Language
en
Open access
closed

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Liu, F., & Maitlis, S. (2014). Emotional Dynamics and Strategizing Processes: A Study of Strategic Conversations in Top Team Meetings. Journal of Management Studies. https://doi.org/10.1111/j.1467-6486.2012.01087.x

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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.