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Cited by 640

The DOI matches its Crossref record; 131 of the 131 references it cites were found in a registry or an index.

Governance and Complexity—Emerging Issues for Governance Theory

DUIT, ANDREAS, GALAZ, VICTOR·2008·Governance

Abstract

Unexpected epidemics, abrupt catastrophic shifts in biophysical systems, and economic crises that cascade across national borders and regions are events that challenge the steering capacity of governance at all political levels. This article seeks to extend the applicability of governance theory by developing hypotheses about how different governance types can be expected to handle processes of change characterized by nonlinear dynamics, threshold effects, cascades, and limited predictability. The first part of the article argues the relevance of a complex adaptive system approach and goes on to review how well governance theory acknowledges the intriguing behavior of complex adaptive systems. In the second part, we develop a typology of governance systems based on their adaptive capacities. Finally, we investigate how combinations of governance systems on different levels buffer or weaken the capacity to govern complex adaptive systems.

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Crossref · 10.1111/j.1468-0491.2008.00402.x

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Metadata

Authors
DUIT, A., & GALAZ, V.
Venue
Governance
Publisher
Wiley
Published
2008-07
Volume
21
Issue
3
Pages
311-335
ISSN
  • 0952-1895 (ISSN-L)
  • 1468-0491
OpenAlex
W2161714261
Cited by
640
References
131
FWCI
126.07
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Governance and Complexity—Emerging Issues for Governance Theory. https://app.cochat.ai/papers/10.1111/j.1468-0491.2008.00402.x
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DUIT, A., & GALAZ, V. (2008). Governance and Complexity—Emerging Issues for Governance Theory. Governance. https://doi.org/10.1111/j.1468-0491.2008.00402.x

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.