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Cited by 543

The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.

Organizing Self‐Organizing Systems: Toward a Theory of Industrial Symbiosis

Chertow, Marian, Ehrenfeld, John·2012·Journal of Industrial Ecology

Abstract

Summary: Industrial symbiosis examines cooperative management of resource flows through networks of businesses known in the literature as industrial ecosystems. These industrial ecosystems have previously been portrayed as having characteristics of complex adaptive systems, but with insufficient attention to the internal and external phenomena describing their genesis. Drawing on biological, ecological, organizational, and systems theory, a discontinuous three‐stage model of industrial symbiosis is presented. The model proceeds from a random formative stage involving numerous actors engaging in material and energy exchanges, to conscious recognition and intentional pursuit of network benefits, to institutionalization of beliefs and norms enabling successful collaborative behavior. While there is much variation, with no single path to this outcome, the recognition of benefits is seen as an emergent property characteristic of these self‐organized systems that move beyond the initial stage.

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Crossref · 10.1111/j.1530-9290.2011.00450.x

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Metadata

Authors
Chertow, M., & Ehrenfeld, J.
Venue
Journal of Industrial Ecology
Published
2012-02
Volume
16
Issue
1
Pages
13-27
ISSN
  • 1088-1980 (ISSN-L)
  • 1530-9290
OpenAlex
W1545660695
Cited by
543
References
61
FWCI
66.12
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Organizing Self‐Organizing Systems: Toward a Theory of Industrial Symbiosis. https://app.cochat.ai/papers/10.1111/j.1530-9290.2011.00450.x
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Chertow, M., & Ehrenfeld, J. (2012). Organizing Self‐Organizing Systems: Toward a Theory of Industrial Symbiosis. Journal of Industrial Ecology. https://doi.org/10.1111/j.1530-9290.2011.00450.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.