Modelling supply chain risk events by considering their contributing events: a systematic literature review

Shahsavari, M; Hussain, OK; Sharma, P; Saberi, M

Modelling supply chain risk events by considering their contributing events: a systematic literature review

Shahsavari, M Hussain, OK Sharma, P Saberi, M

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Publisher:: TAYLOR & FRANCIS LTD
Publication Type:: Journal Article
Citation:: Enterprise Information Systems, 2025, 19, (5-6)
Issue Date:: 2025-01-01

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Field	Value	Language
dc.contributor.author	Shahsavari, M
dc.contributor.author	Hussain, OK
dc.contributor.author	Sharma, P
dc.contributor.author	Saberi, M https://orcid.org/0000-0002-5168-2078
dc.date.accessioned	2025-08-06T04:18:45Z
dc.date.available	2025-08-06T04:18:45Z
dc.date.issued	2025-01-01
dc.identifier.citation	Enterprise Information Systems, 2025, 19, (5-6)
dc.identifier.issn	1751-7575
dc.identifier.issn	1751-7583
dc.identifier.uri	http://hdl.handle.net/10453/189214
dc.description.abstract	Proactive Supply Chain Risk Management (SCRM) helps organisations anticipate and mitigate risks, ensuring business continuity and resilience in a violet market. Existing research proposes various techniques to quantify risk occurrence, but none account for the causal relationships between contributing events and risk events. This paper addresses this gap through a systematic literature review of SCRM techniques and outlines future research directions to enhance proactive SCRM by incorporating causal dependencies in risk quantification.
dc.language	English
dc.publisher	TAYLOR & FRANCIS LTD
dc.relation.ispartof	Enterprise Information Systems
dc.relation.isbasedon	10.1080/17517575.2025.2472303
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0806 Information Systems, 1503 Business and Management
dc.subject.classification	Business & Management
dc.subject.classification	3503 Business systems in context
dc.subject.classification	3507 Strategy, management and organisational behaviour
dc.subject.classification	4609 Information systems
dc.title	Modelling supply chain risk events by considering their contributing events: a systematic literature review
dc.type	Journal Article
utslib.citation.volume	19
utslib.for	0806 Information Systems
utslib.for	1503 Business and Management
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	University of Technology Sydney/UTS Groups
pubs.organisational-group	University of Technology Sydney/UTS Groups/Data Science Institute (DSI)
pubs.organisational-group	University of Technology Sydney/UTS Groups/The Trustworthy Digital Society
utslib.copyright.status	open_access	*
dc.rights.license	This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/
dc.date.updated	2025-08-06T04:18:42Z
pubs.issue	5-6
pubs.publication-status	Published
pubs.volume	19
utslib.citation.issue	5-6

Abstract:

Proactive Supply Chain Risk Management (SCRM) helps organisations anticipate and mitigate risks, ensuring business continuity and resilience in a violet market. Existing research proposes various techniques to quantify risk occurrence, but none account for the causal relationships between contributing events and risk events. This paper addresses this gap through a systematic literature review of SCRM techniques and outlines future research directions to enhance proactive SCRM by incorporating causal dependencies in risk quantification.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/189214