Sorting radiology departments in a disaster management assessment with G-ARASsort

Arash Moheimani, Alessio Ishizaka, Seyed Mohammad Hassan Hosseini and Sachin Kumar Mangla

International Journal of Production Research, 2025, vol. 63, issue 2, 459-482

Abstract: This study presents a new multiple criteria group decision making (MCGDM) sorting method, named G-ARASsort – a new variant of the ARAS ranking method, to address a disaster management assessment problem through a group consensus. MCGDM sorting methods improve a decision-making problem by providing useful and unparalleled insights. Disaster management is one of the most critical areas of decision-making, where decisions are made under tremendous pressure. Radiology units play a central role in disaster management and the present study establishes a new disaster management assessment framework to assess their disaster readiness. The proposed method is applied to sort 37 radiology units into four ordered classes, defined through a Delphi panel. The results show that approximately 11% and 14% of the departments placed in the first (best) and the last (worst) classes, respectively. The findings can help the lower-class units improve their performance by using the upper-class units’ performance as a yardstick. Additionally, healthcare directors can identify more reliable radiology units to turn to during disasters and prevent patient misallocation. A comparative analysis is also conducted to confirm the method’s competency.

Date: 2025
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DOI: 10.1080/00207543.2023.2232477

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