How, When, & Where temporary hospitals fit in turbulent times: A hybrid MADM optimization in the middle east

Yazdi, Amir Karbassi; Muneeb, Farhan Muhammad; Wanke, Peter; Hanne, Thomas; Ali, Adnan

Abstract

Governments have been challenged to provide temporary hospitals and other types of facilities to face the COVID-19 pandemic. This research proposes a novel multi-attribute decision-making (MADM) model to help determine how, when, and where these temporary facilities should be installed based on a set of critical success factors (CSFs) mapped in an uncertain environment. We portray the available facilities for temporary hospitals based on the CSFs that must be considered to make critical decisions regarding the optimal position based on the government's strategic decision-making process, thus indirectly providing better services and maximizing resources. In relation to earlier work, this research builds upon hybrid Pythagorean fuzzy numbers to find weights in Best-Worst Methods and rank temporary facilities based on evaluation by an area-based method for ranking. Policy implications and future directions are derived.

Más información

Título según WOS: How, When, & Where temporary hospitals fit in turbulent times: A hybrid MADM optimization in the middle east
Título según SCOPUS: ID SCOPUS_ID:85144014496 Not found in local SCOPUS DB
Título de la Revista: COMPUTERS & INDUSTRIAL ENGINEERING
Volumen: 175
Editorial: PERGAMON-ELSEVIER SCIENCE LTD
Fecha de publicación: 2023
DOI:

10.1016/J.CIE.2022.108761

Notas: ISI, SCOPUS