The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 has had significant detrimental effects on human well-being, psychologically, socially, economically, and operationally. As the fight against the pandemic continues, the design of efficient policies for the transitional phase remains fraught with complexity and uncertainty. Like many countries around the globe, the Italian government needs to repair the damage done to its socio-economic system by COVID-19 and the response to it. In this regard, policy makers require reliable decision-making supports that improve and validate their decisions and policies. As part of this effort, they must effectively measure and mitigate the impact of the pandemic, including determining which sectors have been most impacted. Due to the high level of uncertainty surrounding this health crisis, in this study, we first develop a new technique for dealing with decision-making problems under uncertainty using exclusive-or-logic, called the XOR-Best Worst Method. Then, the proposed technique is adopted to assess the impact of COVID-19 on seven relevant sectors (tourism, transport, industrial, financial, agriculture, education, healthcare) by considering social, operational, and economic dimensions. The principal findings show that Italy’s tourism, industrial, and healthcare sectors have been most impacted by COVID-19, by 20.29%, 18.86%, and 15.10% respectively from social-economic and operational point of view. These results indicate that most of sustainable development goals of the United Nations agenda for 2030, “No poverty,” “Zero hunger,” and “Decent work and economic growth,” have been strongly impacted in Italy due to the pandemic and that there is an urgent need for support and recovery.

(2023). XOR-best worst method and its assessment to COVID-19 sectorial impact [journal article - articolo]. In ANNALS OF OPERATIONS RESEARCH. Retrieved from https://hdl.handle.net/10446/260779

XOR-best worst method and its assessment to COVID-19 sectorial impact

Hocine, Amin
2023-09-06

Abstract

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 has had significant detrimental effects on human well-being, psychologically, socially, economically, and operationally. As the fight against the pandemic continues, the design of efficient policies for the transitional phase remains fraught with complexity and uncertainty. Like many countries around the globe, the Italian government needs to repair the damage done to its socio-economic system by COVID-19 and the response to it. In this regard, policy makers require reliable decision-making supports that improve and validate their decisions and policies. As part of this effort, they must effectively measure and mitigate the impact of the pandemic, including determining which sectors have been most impacted. Due to the high level of uncertainty surrounding this health crisis, in this study, we first develop a new technique for dealing with decision-making problems under uncertainty using exclusive-or-logic, called the XOR-Best Worst Method. Then, the proposed technique is adopted to assess the impact of COVID-19 on seven relevant sectors (tourism, transport, industrial, financial, agriculture, education, healthcare) by considering social, operational, and economic dimensions. The principal findings show that Italy’s tourism, industrial, and healthcare sectors have been most impacted by COVID-19, by 20.29%, 18.86%, and 15.10% respectively from social-economic and operational point of view. These results indicate that most of sustainable development goals of the United Nations agenda for 2030, “No poverty,” “Zero hunger,” and “Decent work and economic growth,” have been strongly impacted in Italy due to the pandemic and that there is an urgent need for support and recovery.
articolo
6-set-2023
Kouaissah, Noureddine; Hocine, Amin
(2023). XOR-best worst method and its assessment to COVID-19 sectorial impact [journal article - articolo]. In ANNALS OF OPERATIONS RESEARCH. Retrieved from https://hdl.handle.net/10446/260779
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