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Cited by 729

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Social Movements as Extra-Institutional Entrepreneurs: The Effect of Protests on Stock Price Returns

King, Brayden G, Soule, Sarah A.·2007·Administrative Science Quarterly

Abstract

This paper uses social movement theory to examine one way in which secondary stakeholders outside the corporation may influence organizational processes, even if they are excluded from participating in legitimate channels of organizational change. Using data on activist protests of U.S. corporations during 1962–1990, we examine the effect of protests on abnormal stock price returns, an indicator of investors' reactions to a focal event. Empirical analysis demonstrates that protests are more influential when they target issues dealing with critical stakeholder groups, such as labor or consumers, and when generating greater media coverage. Corporate targets are less vulnerable to protest when the media has given substantial coverage to the firm prior to the protest event. Past media attention provides alternative information to investors that may contradict the messages broadcast by protestors.

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Metadata

Authors
King, B. G., & Soule, S. A.
Venue
Administrative Science Quarterly
Published
2007-09
Volume
52
Issue
3
Pages
413-442
ISSN
  • 0001-8392 (ISSN-L)
  • 1930-3815
OpenAlex
W2151817029
Cited by
729
References
9
FWCI
43.97
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Social Movements as Extra-Institutional Entrepreneurs: The Effect of Protests on Stock Price Returns. https://app.cochat.ai/papers/10.2189/asqu.52.3.413
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King, B. G., & Soule, S. A. (2007). Social Movements as Extra-Institutional Entrepreneurs: The Effect of Protests on Stock Price Returns. Administrative Science Quarterly. https://doi.org/10.2189/asqu.52.3.413

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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.