A new fuzzy FUCOM-QFD approach for evaluating strategies to enhance the resilience of the healthcare sector to combat the COVID-19 pandemic

Khan, Feroz Hassan; Ali, Yousaf; Pamučar, Dragan

doi:10.1108/k-02-2021-0130

Cited by 34 publications

(15 citation statements)

References 92 publications

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“…For example, a recommendation is to deal with the issue of uncertainty in HC setting prioritization using fuzzy, intuitionistic fuzzy, hesitant fuzzy, neutrosophic fuzzy, or probabilistic information [71]. Moreover, a study for evaluating strategies on enhancing HC resilience to combat COVID-19 recommended to be extended to other MCDM methods (e.g., AHP, TOPSIS and VIKOR) [39,72]. The FDOSM and FWZIC approaches are recommended to be employed in the different COVID-19 cases owing to their promising results in terms of accuracy and consistency of their weighting and ranking [66].…”

Section: Environments and Methods Recommendationsmentioning

confidence: 99%

“…This situation became increasingly evident during the COVID-19 pandemic [ 71 ]. The COVID-19 pandemic has placed a significant burden on global HC systems, with developing countries bearing the brunt of the damage owing to their underdeveloped HC infrastructure and limited financial resources [ 72 ]. Hospitals’ emergency reaction to HC management lacks sufficient systems for providing HC to COVID-19 patients [ 53 ].…”

Section: Challengesmentioning

confidence: 99%

“…MCDM approaches have been proven effective in numerous HC data-focused applications [ 36 ]. A resilient HC sector can address any type of emergencies in a country [ 70 , 72 ]. It is capable of identifying priority locations, comparing populations, and providing alternatives for government agencies to respond.…”

Section: Motivationsmentioning

confidence: 99%

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Systematic review of MCDM approach applied to the medical case studies of COVID-19: trends, bibliographic analysis, challenges, motivations, recommendations, and future directions

Alamoodi

Zaidan

Albahri

et al. 2023

Complex Intell. Syst.

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When COVID-19 spread in China in December 2019, thousands of studies have focused on this pandemic. Each presents a unique perspective that reflects the pandemic’s main scientific disciplines. For example, social scientists are concerned with reducing the psychological impact on the human mental state especially during lockdown periods. Computer scientists focus on establishing fast and accurate computerized tools to assist in diagnosing, preventing, and recovering from the disease. Medical scientists and doctors, or the frontliners, are the main heroes who received, treated, and worked with the millions of cases at the expense of their own health. Some of them have continued to work even at the expense of their lives. All these studies enforce the multidisciplinary work where scientists from different academic disciplines (social, environmental, technological, etc.) join forces to produce research for beneficial outcomes during the crisis. One of the many branches is computer science along with its various technologies, including artificial intelligence, Internet of Things, big data, decision support systems (DSS), and many more. Among the most notable DSS utilization is those related to multicriterion decision making (MCDM), which is applied in various applications and across many contexts, including business, social, technological and medical. Owing to its importance in developing proper decision regimens and prevention strategies with precise judgment, it is deemed a noteworthy topic of extensive exploration, especially in the context of COVID-19-related medical applications. The present study is a comprehensive review of COVID-19-related medical case studies with MCDM using a systematic review protocol. PRISMA methodology is utilized to obtain a final set of (n = 35) articles from four major scientific databases (ScienceDirect, IEEE Xplore, Scopus, and Web of Science). The final set of articles is categorized into taxonomy comprising five groups: (1) diagnosis (n = 6), (2) safety (n = 11), (3) hospital (n = 8), (4) treatment (n = 4), and (5) review (n = 3). A bibliographic analysis is also presented on the basis of annual scientific production, country scientific production, co-occurrence, and co-authorship. A comprehensive discussion is also presented to discuss the main challenges, motivations, and recommendations in using MCDM research in COVID‐19-related medial case studies. Lastly, we identify critical research gaps with their corresponding solutions and detailed methodologies to serve as a guide for future directions. In conclusion, MCDM can be utilized in the medical field effectively to optimize the resources and make the best choices particularly during pandemics and natural disasters.

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Section: Environments and Methods Recommendationsmentioning

confidence: 99%

Section: Challengesmentioning

confidence: 99%

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Systematic review of MCDM approach applied to the medical case studies of COVID-19: trends, bibliographic analysis, challenges, motivations, recommendations, and future directions

Alamoodi

Zaidan

Albahri

et al. 2023

Complex Intell. Syst.

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“…The study developed a comprehensive framework that can be used by policy makers and health practitioners in determining the best strategies to combat pandemics in the healthcare sector. A hybrid Fuzzy FUCOM-VIKOR-QFD has also been utilized in developing a risk assessment framework for electric power sector of Pakistan [ 115 , 116 ]. The criteria weight coefficients were determined by Fuzzy FUCOM whereas Fuzzy VIKOR ranked the risks according to the weight coefficients obtained from FUCOM.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of critical risk factors in the implementation of modular construction

et al. 2022

Self Cite

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Modular construction is considered as a preferred construction method over conventional construction due to a number of benefits including reduction in project completion time, improved environmental performance, better quality, enhanced workers’ safety and flexibility. However, successful implementation of modular construction is hindered by various risk factors and uncertainties. Therefore, it is imperative to perform a comprehensive risk assessment of critical risk factors that pose a negative impact on the implementation of modular construction. Moreover, there is also a relatively less rate of modular construction adoption in developing countries, highlighting the need to focus more on underdeveloped regions. This study aims to propose a risk assessment framework for identification, evaluation and prioritization of critical risk factors affecting the implementation of modular construction in Pakistan. 20 risk factors were identified from previous literature which were then evaluated to shortlist the most significant risks using Fuzzy Delphi. The most significant risk factors were then prioritized using a novel Full-Consistency Method (FUCOM). The results specified ‘Inadequate skills and experience in modular construction’, ‘Inadequate capacity of modular manufacturers’ and ‘Inability to make changes in design during the construction stage’ as top three critical risks in the implementation of modular construction. This is the first study to propose a risk assessment framework for modular construction in Pakistan. The results of the study are useful to provide insights to construction industry practitioners in highlighting and eliminating risks involved in modular construction planning and execution.

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“…The results of this study indicate that developing countries are more vulnerable to the Covid-19 pandemic than their developed counterparts in terms of their sustainable development levels. Khan, Ali, and Pamucar (2021) offer a new fuzzy FUCOM-QFD approach for the assessment of healthcare systems during the Covid-19 pandemic that can be applied to the systems in different countries.…”

Section: Literature Reviewmentioning

confidence: 99%

How vulnerable are high-income countries to the covid-19 pandemic? An MCDM approach

Tuzcu¹,

Türkoğlu

2022

Decis. Mak. Appl. Manag. Eng.

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This paper tries to determine the most vulnerable points of highincome countries during the Covid-19 pandemic in an MCDM setting. For this aim, we use the entropy method to obtain criteria weights and the PIV method for the comparisons. We employ a wide range of criteria that account for political, demographic, capacity, and Covid-19 indicators including vaccination. Our sample consists of 40 HICs. The results reveal that countries with less equitable healthcare systems and with more vaccine hesitancy are more vulnerable to Covid-19. Hospital bed capacity, a strict government policy, and a lower percentage of the population who smoke add to the success of countries in this combat. We compare our findings with SAW and MAUT techniques as well and obtain very similar rankings. Therefore, we conclude that the PIV method can be used for national performance evaluations with a reduced rank reversal problem and computational simplicity.

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A new fuzzy FUCOM-QFD approach for evaluating strategies to enhance the resilience of the healthcare sector to combat the COVID-19 pandemic

Cited by 34 publications

References 92 publications

Systematic review of MCDM approach applied to the medical case studies of COVID-19: trends, bibliographic analysis, challenges, motivations, recommendations, and future directions

Systematic review of MCDM approach applied to the medical case studies of COVID-19: trends, bibliographic analysis, challenges, motivations, recommendations, and future directions

Evaluation of critical risk factors in the implementation of modular construction

How vulnerable are high-income countries to the covid-19 pandemic? An MCDM approach

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