PMID- 35677841
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20221221
IS  - 0957-4174 (Print)
IS  - 0957-4174 (Electronic)
IS  - 0957-4174 (Linking)
VI  - 205
DP  - 2022 Nov 1
TI  - Intelligent model for contemporary supply chain barriers in manufacturing sectors 
      under the impact of the COVID-19 pandemic.
PG  - 117711
LID - 10.1016/j.eswa.2022.117711 [doi]
AB  - 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.
CI  - (c) 2022 Elsevier Ltd. All rights reserved.
FAU - Gamal, Abduallah
AU  - Gamal A
AD  - Faculty of Computers and Informatics, Zagazig University, Zagazig, Sharqiyah 
      44519, Egypt.
FAU - Abdel-Basset, Mohamed
AU  - Abdel-Basset M
AD  - Faculty of Computers and Informatics, Zagazig University, Zagazig, Sharqiyah 
      44519, Egypt.
FAU - Chakrabortty, Ripon K
AU  - Chakrabortty RK
AD  - Capability Systems Centre, School of Engineering and IT, UNSW Canberra, Egypt.
LA  - eng
PT  - Journal Article
DEP - 20220603
PL  - United States
TA  - Expert Syst Appl
JT  - Expert systems with applications
JID - 9884333
PMC - PMC9162985
OTO - NOTNLM
OT  - ANP
OT  - COVID-19
OT  - MARCOS
OT  - Multi-Criteria Decision-Making
OT  - Supply chain
OT  - Uncertainty
COIS- The authors declare that they have no known competing financial interests or 
      personal relationships that could have appeared to influence the work reported in 
      this paper.
EDAT- 2022/06/10 06:00
MHDA- 2022/06/10 06:01
PMCR- 2022/06/03
CRDT- 2022/06/09 02:23
PHST- 2022/03/02 00:00 [received]
PHST- 2022/05/22 00:00 [revised]
PHST- 2022/05/29 00:00 [accepted]
PHST- 2022/06/10 06:00 [pubmed]
PHST- 2022/06/10 06:01 [medline]
PHST- 2022/06/09 02:23 [entrez]
PHST- 2022/06/03 00:00 [pmc-release]
AID - S0957-4174(22)00998-8 [pii]
AID - 117711 [pii]
AID - 10.1016/j.eswa.2022.117711 [doi]
PST - ppublish
SO  - Expert Syst Appl. 2022 Nov 1;205:117711. doi: 10.1016/j.eswa.2022.117711. Epub 
      2022 Jun 3.