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20231226013045.0 |
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231226s2022 xx |||||o 00| ||eng c |
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|a 10.1016/j.eswa.2022.117711
|2 doi
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|a pubmed24n1139.xml
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|a (DE-627)NLM341996025
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|a (NLM)35677841
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|a DE-627
|b ger
|c DE-627
|e rakwb
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| 041 |
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|a eng
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| 100 |
1 |
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|a Gamal, Abduallah
|e verfasserin
|4 aut
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| 245 |
1 |
0 |
|a Intelligent model for contemporary supply chain barriers in manufacturing sectors under the impact of the COVID-19 pandemic
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| 264 |
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|c 2022
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| 336 |
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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| 338 |
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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| 500 |
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|a Date Revised 21.12.2022
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a © 2022 Elsevier Ltd. All rights reserved.
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|a The COVID-19 pandemic has cast a shadow on the global economy. Since the beginning of 2020, the pandemic has contributed significantly to the global recession. In addition to the health damages of the pandemic, the economic impacts are also severe. The consequences of such effects have pushed global supply chains toward their breaking point. Industries have faced multiple obstacles, threatening the fragile flow of raw materials, spare parts, and consumer goods. Previous studies showed that supply chain barriers have multi-faceted impacts on industries and supply chains, which demand appropriate measures. In this regard, seven major barriers that directly impact industries have been identified to determine which industry is most affected by the COVID-19 pandemic. This paper utilized a hybrid multi-criteria decision-making (MCDM) approach under a neutrosophic environment using trapezoidal neutrosophic numbers to rank those barriers. The Analytical Network Process (ANP) quantifies the effects and considers the interrelationships between the determined barriers (criteria) involved in decision-making. Subsequently, the Measurement Alternatives and Ranking according to the COmpromise Solution (MARCOS) method was adopted to rank six industries according to the impact of those barriers. Results show that the lack of inventory is the largest barrier to influencing industries, followed by the lack of manpower. Sensitivity analysis is performed to detect the change in the rank of industries according to the change in the relative importance of the barriers
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| 650 |
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4 |
|a Journal Article
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| 650 |
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4 |
|a ANP
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| 650 |
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4 |
|a COVID-19
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| 650 |
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4 |
|a MARCOS
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| 650 |
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4 |
|a Multi-Criteria Decision-Making
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| 650 |
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4 |
|a Supply chain
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| 650 |
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4 |
|a Uncertainty
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| 700 |
1 |
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|a Abdel-Basset, Mohamed
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Chakrabortty, Ripon K
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t Expert systems with applications
|d 1999
|g 205(2022) vom: 01. Nov., Seite 117711
|w (DE-627)NLM098196782
|x 0957-4174
|7 nnns
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| 773 |
1 |
8 |
|g volume:205
|g year:2022
|g day:01
|g month:11
|g pages:117711
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| 856 |
4 |
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|u http://dx.doi.org/10.1016/j.eswa.2022.117711
|3 Volltext
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