PMID- 34226821
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20221221
IS  - 1568-4946 (Print)
IS  - 1872-9681 (Electronic)
IS  - 1568-4946 (Linking)
VI  - 110
DP  - 2021 Oct
TI  - Evaluation of government strategies against COVID-19 pandemic using q-rung 
      orthopair fuzzy TOPSIS method.
PG  - 107653
LID - 10.1016/j.asoc.2021.107653 [doi]
AB  - The COVID-19 outbreak, which emerged in China and continues to spread rapidly all 
      over the world, has brought with it increasing numbers of cases and deaths. 
      Governments have suffered serious damage and losses not only in the field of 
      health but also in many other fields. This has directed governments to adopt and 
      implement various strategies in their communities. However, only a few countries 
      succeed partially from the strategies implemented while other countries have 
      failed. In this context, it is necessary to identify the most important strategy 
      that should be implemented by governments. A decision problem based on the 
      decisions of many experts, with some contradictory and multiple criteria, should 
      be taken into account in order to evaluate the multiple strategies implemented by 
      various governments. In this study, this decision process is considered as a 
      multi-criteria decision making (MCDM) problem that also takes into account 
      uncertainty. For this purpose, q-rung orthopair fuzzy sets (q-ROFSs) are used to 
      allow decision-makers to their assessments in a wider space and to better deal 
      with ambiguous information. Accordingly, two different Technique for Order of 
      Preference by Similarity to Ideal Solution (TOPSIS) approaches are recommended 
      under the q-ROFS environment and applied to determine the most appropriate 
      strategy. The results of the proposed approaches determine the A1 - Mandatory 
      quarantine and strict isolation strategy as the best strategy. Comparisons with 
      other q-rung orthopair fuzzy MCDM methods and intuitionistic fuzzy TOPSIS method 
      are also presented for the validation of the proposed methods. Besides, 
      sensitivity analyses are conducted to check the robustness of the proposed 
      approaches and to observe the effect of the change in the q parameter.
CI  - (c) 2021 Elsevier B.V. All rights reserved.
FAU - Alkan, Nursah
AU  - Alkan N
AD  - Istanbul Technical University, Industrial Engineering Department, 34367 Macka, 
      Istanbul, Turkey.
FAU - Kahraman, Cengiz
AU  - Kahraman C
AD  - Istanbul Technical University, Industrial Engineering Department, 34367 Macka, 
      Istanbul, Turkey.
LA  - eng
PT  - Journal Article
DEP - 20210630
PL  - United States
TA  - Appl Soft Comput
JT  - Applied soft computing
JID - 101536968
PMC - PMC8241659
OTO - NOTNLM
OT  - COVID-19
OT  - MCDM
OT  - Q-rung orthopair fuzzy sets
OT  - Strategy selection
OT  - TOPSIS
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- 2021/07/07 06:00
MHDA- 2021/07/07 06:01
PMCR- 2021/06/30
CRDT- 2021/07/06 06:36
PHST- 2020/11/24 00:00 [received]
PHST- 2021/05/12 00:00 [revised]
PHST- 2021/06/22 00:00 [accepted]
PHST- 2021/07/06 06:36 [entrez]
PHST- 2021/07/07 06:00 [pubmed]
PHST- 2021/07/07 06:01 [medline]
PHST- 2021/06/30 00:00 [pmc-release]
AID - S1568-4946(21)00574-3 [pii]
AID - 107653 [pii]
AID - 10.1016/j.asoc.2021.107653 [doi]
PST - ppublish
SO  - Appl Soft Comput. 2021 Oct;110:107653. doi: 10.1016/j.asoc.2021.107653. Epub 2021 
      Jun 30.