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Cited by 978

The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.

Event System Theory: An Event-Oriented Approach to the Organizational Sciences

Morgeson, Frederick P., Mitchell, Terence R., Liu, Dong·2015·Academy of Management Review

Abstract

Organizations are dynamic, hierarchically structured entities. Such dynamism is reflected in the emergence of significant events at every organizational level. Despite this fact, there has been relatively little discussion about how events become meaningful and come to impact organizations across space and time. We address this gap by developing event system theory, which suggests that events become salient when they are novel, disruptive, and critical (reflecting an event’s strength). Importantly, events can originate at any hierarchical level and their effects can remain within that level or travel up or down throughout the organization, changing or creating new behaviors, features, and events. This impact can extend over time as events vary in duration and timing or as event strength evolves. Event system theory provides a needed shift in focus for organizational theory and research by developing specific propositions articulating the interplay among event strength and the spatial and temporal processes through which events come to influence organizations.

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Metadata

Authors
Morgeson, F. P., Mitchell, T. R., & Liu, D.
Venue
Academy of Management Review
Published
2015-10
Volume
40
Issue
4
Pages
515-537
ISSN
  • 0363-7425 (ISSN-L)
  • 1930-3807
OpenAlex
W2036096531
Cited by
978
References
17
FWCI
74.21
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Event System Theory: An Event-Oriented Approach to the Organizational Sciences. https://app.cochat.ai/papers/10.5465/amr.2012.0099
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Morgeson, F. P., Mitchell, T. R., & Liu, D. (2015). Event System Theory: An Event-Oriented Approach to the Organizational Sciences. Academy of Management Review. https://doi.org/10.5465/amr.2012.0099

Data sources

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.