Aplicação de métodos multicritério ao problema de escolha de modelos de pagamento eletrônico por cartão de crédito

Gomes, Carlos Francısco Sımões; Costa, Helder Gomes

doi:10.1590/s0103-65132013005000068

Cited by 15 publications

(10 citation statements)

References 23 publications

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“…Among its main contributions, we emphasize the application of the THOR multi-criteria system in waste recycling in Brazil 20 and in processes associated with health 22 . Gomes and Costa 18 applied this method, together with the METHODS ELECTRE (I and II) and PROMETHÉE II, to the problem of choosing electronic payment models by credit card, and other authors used it to establish strategies for the purchase of a frigate opportunity for the Brazilian Navy 25 .…”

Section: Methodsmentioning

confidence: 99%

“…The THOR method is based on three axiomatic concepts/theories for simultaneous use: preference modeling (approaching the French school -non-compensatory model), multi-attribute utility theory (bringing it closer to the American school -compensatory model) and theories that deal with inaccurate information. The combination of these theories allows quantifying the attractiveness of each alternative by creating a non-transitive aggregation function 18 . The use of THOR allows a faster and more efficient analysis of alternatives, considering the non-determinism of the weight assignment process, and quantifying this non-determinism, reapplying it in the process of ordering the alternatives 19 .…”

Section: Brazilian Navy Ship Of Hopementioning

confidence: 99%

“…O método THOR baseia-se em três conceitos axiomáticos/teorias para uso simultâneo: modelagem de preferência (aproximando-o da escola francesa – modelo não compensatório), teoria da utilidade multiatributo (aproximando-o da escola americana – modelo compensatório) e teorias que tratam da informação imprecisa. A utilização conjunta destas teorias permite quantificar a atratividade de cada alternativa ao criar uma função de agregação não transitiva 18 . O uso do THOR permite analisar as alternativas mais rápida e eficientemente, considerando o não determinismo do processo de atribuição de pesos, e quantificar esse não determinismo, reaplicando-o no processo de ordenação das alternativas 19 .…”

Section: Métodosunclassified

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Choosing a hospital assistance ship to fight the covid-19 pandemic

Costa

Maêda

Teixeira³

et al. 2020

Rev. saúde pública

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OBJECTIVE: To apply the THOR 2 multi-criteria support system to select the Brazilian navy’s most suitable hospital care vessel (NAsH) to support the fight against the covid-19 pandemic. METHODS: We used the first three stages of the Soft Systems Methodology for structuring and modeling of the problem. For the evaluation and ordering of alternatives, we used the Thor 2 multi-criteria support system, comparing four classes of NAsH in the light of their operational and hospital criteria: “Dr. Montenegro,” “Soares Meirelles,” “Oswaldo Cruz” and “Tenente Maximiano.” The chosen ship would support the amazon hospital system, which has an increasing number of cases of covid-19. RESULTS: After the application of the methods, we analyzed three distinct scenarios of ordering the alternatives, which allowed a robust sensitivity analysis, conferring greater transparency and reliability to the decision-making process. The NAsH “Oswaldo Cruz” was selected to be used in the fight against the pandemic. CONCLUSIONS: This study brings valuable contribution to academia and society, since it represents the application of a multi-criteria decision-aid method in the state of the art to contribute to the solution of a real problem that affects millions of people in Brazil and worldwide.

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Section: Methodsmentioning

confidence: 99%

Section: Brazilian Navy Ship Of Hopementioning

confidence: 99%

Section: Métodosunclassified

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Choosing a hospital assistance ship to fight the covid-19 pandemic

Costa

Maêda

Teixeira³

et al. 2020

Rev. saúde pública

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“…As with the conclusions of Gomes & Costa (2015) it is here pointed out that the decision maker should consider a different method solution to enhance his decision process for greater knowledge of the problem.…”

Section: Ranking Initial Ranking Electre III Saw Topsis Promethee Ii mentioning

confidence: 94%

“…Moshkovich et al (2012) evaluated the stability of the results obtained through the SAW and TODIM methods. Gomes & Costa (2015) used a set of methods, including ELECTRE I, II and PROMETHEE II, in order to evaluate the differences between the rankings generated by these different methods in the choice of an electronic payment system. In turn, Yoon & Hwang (1995, p.68) suggested that MCDM ranking methods should be evaluated in the sense of predicting the initial rankings given by the decision maker, that is "how well a method predicts unaided decisions made independently of the judgments used to fit the model".…”

Section: Introductionmentioning

confidence: 99%

Considerations Regarding the Choice of Ranking Multiple Criteria Decision Making Methods

Leoneti

2016

Pesqui. Oper.

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ABSTRACT.Various methods, known as Multiple Criteria Decision Making Methods (MCDM), have been proposed to assist decision makers in the process of ranking alternatives. Given the variability of available methods, choosing an MCDM ranking method is a difficult task. There are key factors in the process of choosing an MCDM method such as: (i) available time; (ii) effort required by a given approach; (iii) importance of accuracy; (iv) transparency necessity; (v) conflict minimization necessity; and (vi) facilitator's skill with the method. However, the problem is further increased by the knowledge that the solution of MCDM ranking methods may be sensitive to slight variations in entrance data and, in some cases, might replace the best alternative for the worst when the weightings for the criteria are changed. Some researchers have addressed this problem through different approaches, including the evaluation of MCDM ranking methods in the sense of predicting the initial rankings given by the decision maker. The objective of this study is to propose an empirical experiment to evaluate the propensity for initial ranking prediction of the principal MCDM ranking methods, namely: SAW, TOPSIS, ELECTRE III, PROMETHEE II and TODIM. The study also aimed to assess possible common ranking problems in MCDM methods, such as reversibility, found in the literature. It was found that just up to 20% of initial ranking order was predicted entirely correct by some of the methods. It was also found that just a few methods did not present internal ranking inconsistency. The results of this study and those found in the literature give a warning regarding the choice of MCDM ranking methods. It is suggested that special care must be taken in the choice of methods and, besides axiomatic comparisons, ranking comparisons could be a useful way to enhance the decision making process, since MCDM methods are tools for learning about the problem and do not prescribe solutions.

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