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Cited by 414

The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.

Supply-Chain Management for Recoverable Manufacturing Systems

Guide, V. Daniel R., Jayaraman, Vaidyanathan, Srivastava, Rajesh, Benton, W. C.·2000·Interfaces
DOI 10.1287/inte.30.3.125.11656
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Abstract

Recoverable manufacturing systems minimize the environmental impact of industry by reusing materials, reducing energy use, and reducing the need to landfill industrial products. These systems are widespread in the United States and are profitable, in addition to contributing to sustainable development. However, the management of supply-chain activities can differ greatly from management activities in traditional manufacturing supply chains. Seven complicating characteristics increase uncertainty. Managers must take actions to reduce uncertainty in the timing and quantity of returns, balance return rates with demand rates, and make material recovery more predictable. Managers must also plan for the collection of products from end-users. The use of information systems with new production-planning and control techniques makes management of these activities more predictable.

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Metadata

Authors
Guide, V. D. R., Jayaraman, V., Srivastava, R., & Benton, W. C.
Venue
Interfaces
Publisher
Institute for Operations Research and the Management Sciences (INFORMS)
Published
2000-06
Volume
30
Issue
3
Pages
125-142
ISSN
  • 0092-2102 (ISSN-L)
  • 1526-551X
DOI
10.1287/inte.30.3.125.11656
OpenAlex
W2102678803
Cited by
414
References
44
FWCI
22.46
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Supply-Chain Management for Recoverable Manufacturing Systems. https://app.cochat.ai/papers/10.1287/inte.30.3.125.11656
The paper
Guide, V. D. R., Jayaraman, V., Srivastava, R., & Benton, W. C. (2000). Supply-Chain Management for Recoverable Manufacturing Systems. Interfaces. https://doi.org/10.1287/inte.30.3.125.11656

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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.