Elsevier

Applied Soft Computing

Volume 132, January 2023, 109891
Applied Soft Computing

Risk assessment approach for analyzing risk factors to overcome pandemic using interval-valued q-rung orthopair fuzzy decision making method

https://doi.org/10.1016/j.asoc.2022.109891Get rights and content

Highlights

  • Interval-valued q-rung orthopair fuzzy-COmplex PRoportional ASsessment (IVq-ROFCOPRAS) method is proposed.

  • A risk analysis model is proposed to identify the obstacles for overcoming the COVID-19 pandemic.

  • The most important obstacles are determined and highlighted for managers and decision makers.

  • Developed framework may used to determine measures for different types of disasters.

Abstract

The process of developing and implementing sustainable strategies to prevent spread of COVID-19 for society typically requires integrating all social, technological, economic, governmental aspects in a systematic way. Since the clear understanding of risk factors contribute to the success of the strategies applied against COVID-19, a risk assessment procedure is applied in this study to properly evaluate risk factors cause to spread of pandemic as a multi-complex decision problem. Therefore, due to the evaluation of risk factors, which often involves uncertain information, the model is constructed based on interval-valued q-rung orthopair fuzzy-COmplex PRoportional ASsessment (IVq-ROF-COPRAS) method. While the developed framework is efficient to enhance the quality of decisions by implementing more realistic, precise, and effective application procedure under uncertain environment, it has capability to help governments for developing comprehensive strategies and responses. According to the results of the proposed risk analysis model, the top three risk factors are “The Approach that Prioritizes the Economy in Policies”, “Insufficient Process Control in Normalization” and “Lack of Epidemic Management Culture in Individuals and Businesses”. Lastly, to show applicability and efficiency of the model sensitivity and comparative analysis were conducted at the end of the study.

Keywords

Risk assessment
Fuzzy sets
Interval valued
q-ROFSs
COPRAS

Data availability

No data was used for the research described in the article.

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