JOURNAL ARTICLE

The Power of Specialization: NGO Advocacy in Global Conservation Governance.

  • Published In: International Studies Quarterly, 2023, v. 67, n. 2. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Shibaike, Takumi 3 of 3

Abstract

The article examines how the organizational choice between specialism and generalism among nongovernmental organizations (NGOs) influences issue salience—defined as public attention to an issue—in global governance, with a focus on wildlife conservation. Drawing on organizational ecology, the study finds that specialist NGOs, which concentrate on narrow niches, are more effective at raising issue salience by targeting engaged segments of the public ("issue publics"), whereas generalist NGOs, such as the World Wildlife Fund (WWF), appeal to broader but less attentive audiences. Quantitative analysis of mammalian species conservation issues (2008–2015) shows a strong positive association between specialist NGO density and issue salience, while the priority of leading generalist NGOs has limited explanatory power. A qualitative case study of pangolin conservation further illustrates that specialist NGOs initiated awareness-raising efforts that led generalist NGOs to follow, suggesting a division of labor rather than a hierarchy dominated by a few leading NGOs. The findings challenge prevailing views that NGO influence is monopolized by large organizations and highlight the distinct roles of specialist NGOs in shaping the organizational environment of global governance.

Additional Information

  • Source:International Studies Quarterly. 2023/06, Vol. 67, Issue 2, p1
  • Document Type:Article
  • Subject Area:Environmental Sciences
  • Publication Date:2023
  • ISSN:0020-8833
  • DOI:10.1093/isq/sqad023
  • Accession Number:192460597
  • Copyright Statement:Copyright of International Studies Quarterly is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.