An interaction and feedback mechanism-based group decision-making for emergency medical supplies supplier selection using T-spherical fuzzy information

Abstract

Selecting a supplier for emergency medical supplies during disasters can be considered a typical multiple attribute group decision-making (MAGDM) problem. MAGDM is an intriguing common problem that is rife with ambiguity and uncertainty. It becomes much more challenging when governments and medical care enterprises adjust their priorities in response to the escalating problems and the effectiveness of the actions taken in different countries. As decision-making problems become increasingly complicated nowadays, a growing number of experts are likely to use T-spherical fuzzy sets (T-SFSs) rather than exact numbers. T-SFS is a novel extension of fuzzy sets that can fully convey ambiguous and complicated information in MAGDM. The objective of this paper is to propose a MAGDM methodology based on interaction and feedback mechanism (IFM) and T-SFS theory. In it, we first introduce T-SF partitioned Bonferroni mean (T-SFPBM) and T-SF weighted partitioned Bonferroni mean (T-SFWPBM) operators to fuse the evaluation information provided by experts. Then, an IFM is designed to achieve a consensus between multiple experts. In the meantime, we also find the weights of experts by using T-SF information. Furthermore, in light of the combination of IFM and T-SFWPBM operator, an MAGDM algorithm is designed. Finally, an example of supplier selection for emergency medical supplies is provided to demonstrate the viability of the suggested approach. The influence of parameters on decision results and comparative analysis with the existing methods confirmed the reliability and accuracy of the suggested approach.

An integrated G-MACONT approach for healthcare supplier selection

“…As most of the evaluation criteria in healthcare supplier selection problems, like quality, performance, responsiveness, service etc. are qualitative in nature, the past researchers also preferred to deploy various uncertainty models, like fuzzy set theory (Manivel and Ranganathan, 2019;Sumrita, 2020;Boz et al, 2022), plithogenic fuzzy set (Abdel-Basset et al, 2021), fuzzy rough numbers (Pamucar et al, 2022), interval-valued intuitionistic fuzzy set (IVIFS) (Salimian et al, 2022), neutrosophic fuzzy set (Gonzalez et al, 2023) and T-spherical fuzzy set (Gurmani et al (2023) to evaluate importance of the criteria and performance of the alternative healthcare suppliers using linguistic variables. It is interestingly GS 14,2 noted that till date, no endeavour has been put forward to integrate grey system theory with any of the MCDM techniques to solve healthcare supplier selection problems.…”

“…To demonstrate application of G-MACONT method in solving a supplier selection problem in the healthcare sector, six major suppliers providing pharmaceutical items to a healthcare unit, S ¼ fS 1 ; S 2 ; S 3 ; S 4 ; S 5 ; S 6 g are considered and evaluated based on six most-commonly studied criteria in the existing literature. These criteria are cost (C 1 ) (Forghani et al, 2018;Akcan and G€ uldes, 2019;Sumrita, 2020;Abdel-Basset et al, 2021;G€ onc€ u and Çetin, 2022;Gurmani et al, 2023), quality (C 2 ) (Forghani et al, 2018;Akcan and G€ uldes, 2019;Abdel-Basset et al, 2021;G€ onc€ u and Çetin, 2022;Gonzalez et al, 2023;Gurmani et al, 2023), delivery performance (C 3 ) (Forghani et al, 2018;Manivel and Ranganathan, 2019), reliability (C 4 ) (Akcan and G€ uldes, 2019), responsiveness (C 5 ) (Abdel-Basset et al, 2021) and flexibility (C 6 ) (Manivel and Ranganathan, 2019;Akcan and G€ uldes, 2019;Gonzalez et al, 2023). For solving GS 14,2 this healthcare supplier selection problem using G-MACONT approach, the opinions of three decision makers (experts) are sought with respect to relative importance assigned to the considered evaluation criteria and performance of the alternative suppliers against each criterion.…”

“…, 2022), neutrosophic fuzzy set (Gonzalez et al. , 2023) and T-spherical fuzzy set (Gurmani et al. (2023) to evaluate importance of the criteria and performance of the alternative healthcare suppliers using linguistic variables.…”

“…, 2018; Akcan and Güldes, 2019; Abdel-Basset et al. , 2021; Göncü and Çetin, 2022; Gonzalez et al ., 2023; Gurmani et al. , 2023), delivery performance (C 3 ) (Forghani et al.…”

Group decision making in the analytic hierarchy process by hesitant fuzzy numbers

“…For example Foroozesh et al studied a new soft computing approach based on multi-attributes decision analysis, group decision making and fuzzy possibilistic statistical modeling for sustainable supplier selection problem 27 . Gurmani et al presented an interaction and feedback mechanism-based group decision-making for emergency medical supplies supplier selection using T-spherical fuzzy information 28 . AlAita et al introduced a new approach is proposed using neutrosophic statistics to analyze split-plot and split-block designs.…”