Modeling transportation disruptions in the supply chain of automotive parts manufacturing company

Fartaj, SR; Kabir, G; Eghujovbo, V; Ali, SM; Paul, SK

Modeling transportation disruptions in the supply chain of automotive parts manufacturing company

Fartaj, SR Kabir, G Eghujovbo, V Ali, SM Paul, SK

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Publisher:: ELSEVIER
Publication Type:: Journal Article
Citation:: International Journal of Production Economics, 2020, 222
Issue Date:: 2020-04

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Field	Value	Language
dc.contributor.author	Fartaj, SR
dc.contributor.author	Kabir, G
dc.contributor.author	Eghujovbo, V
dc.contributor.author	Ali, SM
dc.contributor.author	Paul, SK
dc.date.accessioned	2020-10-03T23:59:37Z
dc.date.available	2020-10-03T23:59:37Z
dc.date.issued	2020-04
dc.identifier.citation	International Journal of Production Economics, 2020, 222
dc.identifier.issn	0925-5273
dc.identifier.issn	1873-7579
dc.identifier.uri	http://hdl.handle.net/10453/143063
dc.description.abstract	© 2019 Elsevier B.V. The transportation network plays a vital role in the strategic imperative of automotive parts manufacturing companies. There is a lack of academic and practical studies, which focus solely on transportation disruption analysis in the supply chain of automotive parts manufacturing company. Moreover, very few studies have taken into account the cause and effect relationship between transportation disruption factors. The objective of this study is to analyze the critical transportation disruption factors of the supply chain of automotive parts manufacturing company and to represent the interrelationships using the best-worst (BWM) and rough strength-relation (RSR) analysis methods. The newly integrated BWM-RSR framework considers the vagueness and ambiguity in disruption factor analysis. The applicability and effectiveness of the newly developed BWM-RSR framework are demonstrated at an automotive parts manufacturing company in Oldcastle, Ontario, Canada. The results show that infrastructural bottlenecks/congestion and inadequate skilled labor are the most critical factors to the disruption of the transportation network in the automotive industry. The developed new framework can be used as an effective tool to analyze critical transportation disruption factors and examine the associated interrelationships.
dc.language	English
dc.publisher	ELSEVIER
dc.relation.ispartof	International Journal of Production Economics
dc.relation.isbasedon	10.1016/j.ijpe.2019.09.032
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Operations Research
dc.title	Modeling transportation disruptions in the supply chain of automotive parts manufacturing company
dc.type	Journal Article
utslib.citation.volume	222
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Management Discipline
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
pubs.consider-herdc	true
dc.date.updated	2020-10-03T23:59:34Z
pubs.publication-status	Published
pubs.volume	222

Abstract:

© 2019 Elsevier B.V. The transportation network plays a vital role in the strategic imperative of automotive parts manufacturing companies. There is a lack of academic and practical studies, which focus solely on transportation disruption analysis in the supply chain of automotive parts manufacturing company. Moreover, very few studies have taken into account the cause and effect relationship between transportation disruption factors. The objective of this study is to analyze the critical transportation disruption factors of the supply chain of automotive parts manufacturing company and to represent the interrelationships using the best-worst (BWM) and rough strength-relation (RSR) analysis methods. The newly integrated BWM-RSR framework considers the vagueness and ambiguity in disruption factor analysis. The applicability and effectiveness of the newly developed BWM-RSR framework are demonstrated at an automotive parts manufacturing company in Oldcastle, Ontario, Canada. The results show that infrastructural bottlenecks/congestion and inadequate skilled labor are the most critical factors to the disruption of the transportation network in the automotive industry. The developed new framework can be used as an effective tool to analyze critical transportation disruption factors and examine the associated interrelationships.

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http://hdl.handle.net/10453/143063