A Hybrid Spherical Fuzzy MCDM Approach to Prioritize Governmental Intervention Strategies against the COVID-19 Pandemic: A Case Study from Vietnam

Phi-Hung Nguyen, Jung-Fa Tsai, Thanh-Tuan Dang, Ming-Hua Lin, Hong-Anh Pham and Kim-Anh Nguyen
Additional contact information
Phi-Hung Nguyen: Department of Business Management, National Taipei University of Technology, Taipei 10608, Taiwan
Jung-Fa Tsai: Department of Business Management, National Taipei University of Technology, Taipei 10608, Taiwan
Thanh-Tuan Dang: Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan
Ming-Hua Lin: Department of Urban Industrial Management and Marketing, University of Taipei, Taipei 11153, Taiwan
Hong-Anh Pham: Faculty of Business, FPT University, Hanoi 100000, Vietnam
Kim-Anh Nguyen: Faculty of Business, FPT University, Hanoi 100000, Vietnam

Mathematics, 2021, vol. 9, issue 20, 1-26

Abstract: The unprecedented coronavirus pandemic (COVID-19) is fluctuating worldwide. Since the COVID-19 epidemic has a negative impact on all countries and has become a significant threat, it is necessary to determine the most effective strategy for governments by considering a variety of criteria; however, few studies in the literature can assist governments in this topic. Selective governmental intervention during the COVID-19 outbreak is considered a Multi-Criteria Decision-Making (MCDM) problem under a vague and uncertain environment when governments and medical communities adjust their priorities in response to rising issues and the efficacy of interventions applied in various nations. In this study, a novel hybrid Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Fuzzy Weighted Aggregated Sum Product Assessment (WASPAS-F) model is proposed to help stakeholders such as governors and policymakers to prioritize governmental interventions for dealing with the COVID-19 outbreak. The SF-AHP is implemented to measure the significance of the criteria, while the WASPAS-F approach is deployed to rank intervention alternatives. An empirical case study is conducted in Vietnam. From the SF-AHP findings, the criteria of “effectiveness in preventing the spread of COVID-19”, “ease of implementation”, and “high acceptability to citizens” were recognized as the most important criteria. As for the ranking of strategies, “vaccinations”, “enhanced control of the country’s health resources”, “common health testing”, “formation of an emergency response team”, and “quarantining patients and those suspected of infection” are the top five strategies. Aside from that, the robustness of the approach was tested by performing a comparative analysis. The results illustrate that the applied methods reach the general best strategy rankings. The applied methodology and its analysis will provide insight to authorities for fighting against the severe pandemic in the long run. It may aid in solving many complicated challenges in government strategy selection and assessment. It is also a flexible design model for considering the evaluation criteria. Finally, this research provides valuable guidance for policymakers in other nations.

Keywords: MCDM; COVID-19; governmental intervention strategies; spherical fuzzy analytic hierarchy process (SF-AHP); fuzzy weighted aggregated sum product assessment (WASPAS-F); Vietnam (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://www.mdpi.com/2227-7390/9/20/2626/pdf (application/pdf)
https://www.mdpi.com/2227-7390/9/20/2626/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:9:y:2021:i:20:p:2626-:d:659118

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().