MARCOS technique under intuitionistic fuzzy environment for determining the COVID-19 pandemic performance of insurance companies in terms of healthcare services

Ecer, Fatih; Pamučar, Dragan

doi:10.1016/j.asoc.2021.107199

Cited by 147 publications

(73 citation statements)

References 64 publications

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“…The authors determined the priority of financial ratios and the ranking of construction companies with the proposed techniques. The next work 92 discussed that the medical sector has been affected by COVID‐19‐related decisions and issues that were also reflected in business and the economy. They discussed the insurance business and elaborated that assessing and ranking private health insurance companies provide insurance agencies, insurance customers, and authorities with a reliable instrument for the insurance decision‐making process.…”

Section: Literature Review Analysismentioning

confidence: 99%

“…The result of this review revealed 13 extensions of existing methods, namely, LBWA–MACBETH–RAFSI, 49 PmF‐TOPSIS, 67 WASPAS, 95 AHP‐Entropy‐TOPSIS‐GRA, 78 distance measure for IFSs, 59 LHF‐BWM‐TODIM, 96 BBWM with improved matter‐element extension model (BBWM‐IMEEM), 90 cross‐entropy of UPLZs‐MULTIMOORA, 74 Entropy‐F‐VIKOR, 89 FAHP‐HFS‐TOPSIS, 80 HF‐divergence measure‐HF‐ARAS, 76 TrIT2F‐BWM‐VIKOR, 72 and IF‐MARCOS. 92 These methods mainly focus on handling the inaccuracies and uncertainties (vagueness issue) mentioned in Table 1 . Among the six new proposed MADM methods that were developed to overcome the limitation of the existing methods, five were under the medical category, namely, SODOSM, 10 FFNs, 63 spherical normal fuzzy weighted Bonferroni mean (SpNoFWBM), 58 FA, 65 and CQROULWPBM, 64 whereas FLQOWA 83 was under the economic category.…”

Section: Literature Review Analysismentioning

confidence: 99%

“…Figure 6 shows the 16 countries in which the studies included in this review were conducted. The selected articles' geographical distribution in terms of numbers and percentages shows that the most prolific contributors were from India 59 , 63 , 65 , 73 , 75 , 76 , 79 , 80 , 82 , 83 , 88 , 93 with 12 studies; China 56 , 58 , 72 , 74 , 86 , 90 , 96 with seven studies; Turkey, 51 , 60 , 71 , 91 , 92 Pakistan, 54 , 57 , 67 , 78 , 85 and Malaysia 10 , 37 , 52 , 68 , 89 with five studies each; Saudi Arabia 69 , 77 , 94 with three studies; Iraq, 61 , 66 Egypt, 44 , 62 Iran, 50 , 81 and Italy 70 , 87 with two studies each; and Serbia, 49 Philippines, 53 Brazil, 55 ...…”

Section: Literature Review Analysismentioning

confidence: 99%

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

Alsalem

Mohammed²,

Albahri

et al. 2021

Int J of Intelligent Sys

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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.

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Section: Literature Review Analysismentioning

confidence: 99%

Section: Literature Review Analysismentioning

confidence: 99%

Section: Literature Review Analysismentioning

confidence: 99%

See 1 more Smart Citation

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

Alsalem

Mohammed²,

Albahri

et al. 2021

Int J of Intelligent Sys

View full text Add to dashboard Cite

show abstract

“…This method determines ideal and anti-ideal alternatives as reference values and then defines the relationshiprepresented as a utility function in the MARCOS method -between them and other alternatives. Though it has been introduced very recently, it attracted considerable attention from researcher communities [27], [36][37][38][39][40][41]. The following are the steps of the MARCOS method [42].…”

Section: Measurement Alternatives and Ranking According To Compromise Solution (Marcos)mentioning

confidence: 99%

Combining the Suitability-Feasibility-Acceptability (Sfa) Strategy With the McDm Approach

Zolfani¹,

Bazrafshan

Akaberi

et al. 2021

FU Mech Eng

Self Cite

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Suitability-Feasibility-Acceptability (SFA) is a fundamental tool for the development and selection of strategy. Any type of decision-making problem can be resolved by Multiple Criteria Decision Making (MCDM) methods. In this research, we explore the complexity of determining the proper goal market for the Chilean fish market. This study proposed a combined approach of SFA with MCDM methods in a real case study. The proposed structure helps to assign the best market for Chilean export fish to West Asia. Three countries (Saudi Arabia, the United Arab Emirates, and Oman) are selected as a target market in this region, and then related criteria are obtained from various sources. In order to develop a new market for the Chilean fishery industry, five major criteria, including the potential of a target market, region's economic attractiveness, consumption of the seafood, location, cost of transportation, and country risks, were selected based on the SFA framework. Calculating the criteria weights is performed by the Best-Worst (BWM) method, and ordering the alternatives is operated by Measurement Alternatives and Ranking according to compromise Solution (MARCOS) methods. The results showed that Oman is the best destination (importer) for the Chilean fish market (Salmon fish as the case).

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“…For example, Ecer and Pamucar [4] have used fuzzy BWM (best worst method) to find the relative weights and fuzzy CoCoSo (combined compromise solution) with Bonferroni (CoCoSo'B) to rank alternatives in sustainable supplier selection problem. Ecer and Pamucar [5] assessed insurance companies according to their service quality in Covid-19 by using intuitionistic fuzzy MARCOS (measurement of alternatives and ranking according to compromise solution). Shojaei and Bolvardizadeh [6] has used rough AHP (analytic hierarchy process) and rough TOPSIS (technique for order performance by similarity to ideal solution) for assessing suppliers in terms of sustainability in construction industry.…”

Section: Introductionmentioning

confidence: 99%

A New Integrated Grey McDm Model: Case of Warehouse Location Selection

Ulutaş

Balo²,

Sua³

et al. 2021

FU Mech Eng

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Warehouses link suppliers and customers throughout the entire supply chain. The location of the warehouse has a significant impact on the logistics process. Even though all other warehouse activities are successful, if the product dispatched from the warehouse fails to meet the customer needs in time, the company may face with the risk of losing customers. This affects the performance of the whole supply chain therefore the choice of warehouse location is an important decision problem. This problem is a multi-criteria decision-making (MCDM) problem since it involves many criteria and alternatives in the selection process. This study proposes an integrated grey MCDM model including grey preference selection index (GPSI) and grey proximity indexed value (GPIV) to determine the most appropriate warehouse location for a supermarket. This study aims to make three contributions to the literature. PSI and PIV methods combined with grey theory will be introduced for the first time in the literature. In addition, GPSI and GPIV methods will be combined and used to select the best warehouse location. In this study, the performances of five warehouse location alternatives were assessed with twelve criteria. Location 4 is found as the best alternative in GPIV. The GPIV results were compared with other grey MCDM methods, and it was found that GPIV method is reliable. It has been determined from the sensitivity analysis that the change in criteria weights causes a change in the ranking of the locations therefore GPIV method was found to be sensitive to the change in criteria weights.

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MARCOS technique under intuitionistic fuzzy environment for determining the COVID-19 pandemic performance of insurance companies in terms of healthcare services

Cited by 147 publications

References 64 publications

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

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

Combining the Suitability-Feasibility-Acceptability (Sfa) Strategy With the McDm Approach

A New Integrated Grey McDm Model: Case of Warehouse Location Selection

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