Skip to main content

Research Repository

Advanced Search

A decision framework to mitigate supply chain risks: an application in the offshore-wind industry

Mogre, R.; Talluri, S.; D’Amico, F.

A decision framework to mitigate supply chain risks: an application in the offshore-wind industry Thumbnail


Authors

S. Talluri

F. D’Amico



Abstract

Decision support systems (DSSs) for supply chain risk management benefit from a holistic approach for mitigating risks, which include identification and assessment of risks and evaluation and selection of measures to appease risks. However, previous studies in this area overlooked probability estimation, measure selection, and assessment of interdependence of risks and measures. We aim to fill these gaps in the literature by proposing a two-stage DSSs that will assist managers in not only select mitigation strategies for supply chain risks, but also mitigation tactics when risks occur. Our DSS employs a novel matrix formulation for decision-tree analysis, which integrates expert judgments. We applied our models to the supply chain of a fast-expanding offshore-wind industry, which faces high levels of exposure to risks because of the associated complexities in this domain. The results demonstrate how to select mitigation strategies and mitigation tactics for managing supply chain risks within the offshore-wind industry.

Citation

Mogre, R., Talluri, S., & D’Amico, F. (2016). A decision framework to mitigate supply chain risks: an application in the offshore-wind industry. IEEE Transactions on Engineering Management, 63(3), 316-325. https://doi.org/10.1109/tem.2016.2567539

Journal Article Type Article
Acceptance Date May 6, 2016
Online Publication Date Jun 15, 2016
Publication Date Aug 1, 2016
Deposit Date May 11, 2016
Publicly Available Date May 13, 2016
Journal IEEE Transactions on Engineering Management
Print ISSN 0018-9391
Electronic ISSN 1558-0040
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 63
Issue 3
Pages 316-325
DOI https://doi.org/10.1109/tem.2016.2567539
Public URL https://durham-repository.worktribe.com/output/1384800

Files

Accepted Journal Article (634 Kb)
PDF

Copyright Statement
© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.






You might also like



Downloadable Citations