Rise of multiattribute decision-making in combating COVID-19: A systematic review of the state-of-the-art literature

Mohammed Assim Alsalem; Rawia Mohammed; Osamah Shihab Albahri; Aws Alaa Zaidan; Abdullah Hussein Alamoodi; Kareem Dawood; Alhamzah Alnoor; Ahmed Shihab Albahri; Bilal Bahaa Zaidan; Uwe Aickelin; Hassan Alsattar; Mamoun Alazab; Fawaz Jumaah

doi:10.1002/int.22699

Rise of multiattribute decision-making in combating COVID-19: A systematic review of the state-of-the-art literature

Int J Intell Syst. 2022 Jun;37(6):3514-3624. doi: 10.1002/int.22699. Epub 2021 Oct 4.

Affiliations

¹ Department of Computing, Faculty of Arts, Computing and Creative Industry Universiti Pendidikan Sultan Idris Tanjung Malim Malaysia.
² Faculty of Computing and Innovative Technology Geomatika University College Kuala Lumpur Malaysia.
³ Computer Science Department Komar University of Science and Technology (KUST) Sulaymaniyah Iraq.
⁴ School of Management Universiti Sains Malaysia Pulau Pinang Malaysia.
⁵ Informatics Institute for Postgraduate Studies (IIPS) Iraqi Commission for Computers and Informatics (ICCI) Baghdad Iraq.
⁶ Future Technology Research Center National Yunlin University of Science and Technology Douliou Taiwan R.O.C.
⁷ School of Computing and Information Systems The University of Melbourne Australia.
⁸ College of Engineering, IT and Environment Charles Darwin University Casuarina Northern Territory Australia.
⁹ Department of Advanced Applications and Embedded Systems Intel Corporation Pulau Pinang Malaysia.

Abstract

Considering the coronavirus disease 2019 (COVID-19) pandemic, the government and health sectors are incapable of making fast and reliable decisions, particularly given the various effects of decisions on different contexts or countries across multiple sectors. Therefore, leaders often seek decision support approaches to assist them in such scenarios. The most common decision support approach used in this regard is multiattribute decision-making (MADM). MADM can assist in enforcing the most ideal decision in the best way possible when fed with the appropriate evaluation criteria and aspects. MADM also has been of great aid to practitioners during the COVID-19 pandemic. Moreover, MADM shows resilience in mitigating consequences in health sectors and other fields. Therefore, this study aims to analyse the rise of MADM techniques in combating COVID-19 by presenting a systematic literature review of the state-of-the-art COVID-19 applications. Articles on related topics were searched in four major databases, namely, Web of Science, IEEE Xplore, ScienceDirect, and Scopus, from the beginning of the pandemic in 2019 to April 2021. Articles were selected on the basis of the inclusion and exclusion criteria for the identified systematic review protocol, and a total of 51 articles were obtained after screening and filtering. All these articles were formed into a coherent taxonomy to describe the corresponding current standpoints in the literature. This taxonomy was drawn on the basis of four major categories, namely, medical (n = 30), social (n = 4), economic (n = 13) and technological (n = 4). Deep analysis for each category was performed in terms of several aspects, including issues and challenges encountered, contributions, data set, evaluation criteria, MADM techniques, evaluation and validation and bibliography analysis. This study emphasised the current standpoint and opportunities for MADM in the midst of the COVID-19 pandemic and promoted additional efforts towards understanding and providing new potential future directions to fulfil the needs of this study field.

Keywords: COVID‐19; SARS‐CoV‐2; decision support; multiattribute decision‐making; multicriteria decision‐making.