Prioritization of healthcare systems during pandemics using Cronbach’s measure based fuzzy WASPAS approach
Muhammet Deveci (),
Raghunathan Krishankumar,
Ilgin Gokasar and
Rumeysa Tuna Deveci
Additional contact information
Muhammet Deveci: National Defence University
Raghunathan Krishankumar: Amrita School of Engineering
Ilgin Gokasar: Bogazici University
Rumeysa Tuna Deveci: Istanbul University
Annals of Operations Research, 2023, vol. 328, issue 1, No 9, 279-307
Abstract:
Abstract Pandemics are well-known as epidemics that spread globally and cause many illnesses and mortality. Because of globalization, the accelerated occurrence and circulation of new microbes, the infection has emerged and the incidence and movement of new microbes have sped up. Using technological devices to minimize the visit durations, specifying days for handling chronic diseases, subsidy for the staff are the alternatives that can help prevent healthcare systems from collapsing during pandemics. The study aims to define the efficient usage of optimization tools during pandemics to prevent healthcare systems from collapsing. In this study, a new integrated framework with fuzzy information is developed, which attempts to prioritize these alternatives for policymakers. First, rating data are assigned respective fuzzy values using the standard singleton grades. Later, criteria weights are determined by extending Cronbach´s measure to fuzzy context. The measure not only understands data consistency comprehensively, but also takes into consideration the attitudinal characteristics of experts. By this approach, a rational weight vector is obtained for decision-making. Further, an improved Weighted Aggregated Sum Product Assessment (WASPAS) algorithm is put forward for ranking alternatives, which is flexibly considering criteria along with personalized ordering and holistic ordering alternatives. The usefulness of the developed framework is tested with the help of a real case study. Rank values of alternatives when unbiased weights are used is given by 0.741, 0.582, 0.640 with ordering as $$R_{1} \succ R_{3} \succ R_{2}$$ R 1 ≻ R 3 ≻ R 2 . The sensitivity/comparative analysis reveals the impact of the proposed model as useful in selecting the best alternative for the healthcare systems during pandemics.
Keywords: Healthcare systems; Pandemics; Fuzzy sets; Multi-criteria decision making (MCDM); WASPAS; Cronbach’s measure (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10479-022-04714-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:328:y:2023:i:1:d:10.1007_s10479-022-04714-3
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479
DOI: 10.1007/s10479-022-04714-3
Access Statistics for this article
Annals of Operations Research is currently edited by Endre Boros
More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().