Abstract
During the COVID-19 pandemic, masks have become essential items for all people to protect themselves from the virus. Because of considering multiple factors when selecting an antivirus mask, the decision-making process has become more complicated. This paper proposes an integrated approach that uses F-BWM-RAFSI methods for antivirus mask selection process with respect to the COVID-19 pandemic. Finally, sensitivity analysis was demonstrated by evaluating the effects of changing the weight coefficients of the criterion on the ranking results, simulating changes in Heronian operator parameters, and comparing the obtained solution to other MCDM approaches to ensure its robustness.
Highlights
The COVID-19 pandemic, which is the result of the SARS-CoV-2 virus, has spread around the world in a short time since its emergence in Wuhan, China, mobilized international health authorities and its effect continues to be serious
This paper focuses on the selection process of the antivirus masks under the COVID-19 pandemic situation and aims to address the following research questions (RQs): RQ1: Which criterion is more important for selecting an antivirus mask? RQ2: How to effectively evaluate the antivirus masks through the subjective judgment of group experts in medicine sector? RQ3: How to build a decision-making approach that evaluates the antivirus mask alternatives?
The fuzzy logic extension of best-worst method (BWM) method proposed by Rezaei (2015), a newly developed multi criteria decision-making (MCDM) approach for weighting criteria and alternatives based on pairwise comparisons, can handle uncertainties and vagueness of decision-makers’ opinions in the comparison matrix better
Summary
The COVID-19 pandemic, which is the result of the SARS-CoV-2 virus, has spread around the world in a short time since its emergence in Wuhan, China, mobilized international health authorities and its effect continues to be serious. Yang et al (2020) developed the MCDM method based on SpNoF Bonferroni mean operator and the weighted Bonferroni mean operator for selecting an antivirus mask during the COVID-19 pandemic. This paper proposes an integrated approach that uses fuzzy BWM and Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (F-BWM-RAFSI) methods for antivirus mask selection process with respect to the COVID-19 pandemic. It has been demonstrated that the BWM method performs significantly better than other MCDM methods such as AHP in terms of consistency index, minimum violation, total deviation and conformity (Rezaei, 2015) These advantages are indicated below (Stević et al, 2018; Zolfani et al, 2019; Ecer and Pamucar, 2020; Luo et al., 2020):.
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