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Cited by 1,607

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Supply networks and complex adaptive systems: control versus emergence

Choi, Thomas Y, Dooley, Kevin J, Rungtusanatham, Manus·2001·Journal of Operations Management

Abstract

In much of the current literature on supply chain management, supply networks are recognized as a system. In this paper, we take this observation to the next level by arguing the need to recognize supply networks as a complex adaptive system(CAS). We propose that many supply networks emerge rather than result from purposeful design by a singular entity. Most supply chain management literature emphasizes negative feedback for purposes of control; however, the emergent patterns in a supply network can much better be managed through positive feedback, which allows for autonomous action. Imposing too much control detracts from innovation and flexibility; conversely, allowing too much emergence can undermine managerial predictability and work routines. Therefore, when managing supply networks, managers must appropriately balance how much to control and how much to let emerge.

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Metadata

Authors
Choi, T. Y., Dooley, K. J., & Rungtusanatham, M.
Venue
Journal of Operations Management
Publisher
Wiley
Published
2001-03-19
Volume
19
Issue
3
Pages
351-366
ISSN
  • 0272-6963 (ISSN-L)
  • 1873-1317
OpenAlex
W2169589185
Cited by
1,607
References
2
FWCI
29.61
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Supply networks and complex adaptive systems: control versus emergence. https://app.cochat.ai/papers/10.1016/s0272-6963(00)00068-1
The paper
Choi, T. Y., Dooley, K. J., & Rungtusanatham, M. (2001). Supply networks and complex adaptive systems: control versus emergence. Journal of Operations Management. https://doi.org/10.1016/s0272-6963(00)00068-1

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.