Identifying critical success factors in Heart Failure Self-Care using fuzzy DEMATEL method

Mahmoudi, Saeed; Jalali, Amir; Ahmadi, Maryam; Abasi, Parvin; Salari, Nader

doi:10.1016/j.asoc.2019.105729

Cited by 52 publications

(34 citation statements)

References 60 publications

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“…Fuzzy DEMATEL method is currently applied in many areas such as management [28,29], emergency planning [30], health care systems [31,32], and safety management [11,33]. The overview of the literature show that for integrating the experts' opinions and preferences in DEAMTEL, arithmetic mean has been usually used [34,35]. Since arithmetic mean is sensitive to outliers, the integration of experts' opinions using this method has high error.…”

Section: Fuzzy Dematelmentioning

confidence: 99%

A fuzzy DEMATEL approach for evaluating the risk factors

2021

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Many risk factors are dependent on each other and taking this into account can help manage appropriate decisions. The poor evaluation of these factors will impose high costs in many real applications, especially for a supply chain. There are different methods for risk evaluating and their effects for ranking them. For instant, in the fuzzy DEMATEL method, the experts’ linguistic opinions and preferences on the agent effects are used as the input. The important point is how these opinions are aggregated to produce the less computational error. In this regard, this paper proposes a new method based on statistical inferences for a fuzzy DEMATEL approach for evaluating the factors of a supply chain. This method was applied to a case study and the results showed that the proposed method was better than other methods for integrating the experts’ opinions in a supply chain. However, this method was proposed for the evaluation of supply chain factors, it can be applied to other systems as well.

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Section: Fuzzy Dematelmentioning

confidence: 99%

A fuzzy DEMATEL approach for evaluating the risk factors

2021

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“…Each decision maker will be asked to fill in a non-negative matrix X, showing linguistic evaluations of influence for each couple of elements according to the scale presented in Table 6 (similar to the one used by Mahmoudi et al [64]). Each evaluation of influence corresponds to a triangular fuzzy number (TFN) x ij = a ij , b ij , c ij , where a ij ≤ b ij ≤ c ij .…”

Section: Fuzzy Dematel To Evaluate the Factor Of Dependence For Each mentioning

confidence: 99%

Assessing Supply Chain Risks in the Automotive Industry through a Modified MCDM-Based FMECA

et al. 2020

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Supply chains are complex networks that receive assiduous attention in the literature. Like any complex network, a supply chain is subject to a wide variety of risks that can result in significant economic losses and negative impacts in terms of image and prestige for companies. In circumstances of aggressive competition among companies, effective management of supply chain risks (SCRs) is crucial, and is currently a very active field of research. Failure Mode, Effects and Criticality Analysis (FMECA) has been recently extended to SCR identification and prioritization, aiming at reducing potential losses caused by lack of risk control. This article has a twofold objective. First, SCR assessment is investigated, and a comprehensive list of specific risks related to the automotive industry is compiled to extend the set of most commonly considered risks. Second, an alternative way of calculating the Risk Priority Number (RPN) is proposed within the FMECA framework by means of an integrated Multi-Criteria Decision-Making (MCDM) approach. We give a new calculation procedure by making use of the Analytic Hierarchy Process (AHP) to derive factors weights, and then the fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) to evaluate the new factor of “dependence” among the risks. The developed joint analysis constitutes a risk analysis support tool for criticality in systems engineering. The approach also deals with uncertainty and vagueness associated with input data through the use of fuzzy numbers. The results obtained from a relevant case study in the automotive industry showcase the effectiveness of this approach, which brings important value to those companies: When planning interventions of prevention/mitigation, primary importance should be given to (1) supply chain disruptions due to natural disasters; (2) manufacturing facilities, human resources, policies and breakdown processes; and (3) inefficient transport.

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“…In this process, the average values of these evaluations were considered, and the details are shown in Equation (2) [57]:…”

Section: It2 Fuzzy Dematelmentioning

confidence: 99%

Multi-Faceted Analysis of Systematic Risk-Based Wind Energy Investment Decisions in E7 Economies Using Modified Hybrid Modeling with IT2 Fuzzy Sets

Qiu¹,

et al. 2020

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This study aimed to analyze the systematic risks of wind energy investments. Within this framework, E7 countries are included in the scope of the examination. A large literature review was carried out and 12 different systematic risk factors that could exist in wind energy investments were identified. The analysis process of the study consisted of two different stages. First, the specified risk criteria were weighted with the help of the interval type 2 (IT2) fuzzy decision-making trial and evaluation laboratory (DEMATEL) method. Second, E7 countries were ranked according to the risk management effectiveness in wind energy investments. In this process, the IT2 fuzzy Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) approach was taken into consideration. The findings show that volatility in exchange rates and interest rates were the most important risks in wind energy investments. In addition, it was determined that China and Indonesia were the most successful countries in managing risks in wind energy investments. In contrast, India, Russia, and Turkey were determined to be the least successful. Additionally, the IT2 fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method was applied as a robustness check of the extended VIKOR method. It was concluded that the ranking results of the IT2 fuzzy TOPSIS method were similar to the results of the IT2 fuzzy VIKOR. It can be understood that the proposed ranking method was consistent with the comparative analysis results. From this point of view, it was observed that countries should take measures regarding their exchange rate and interest rate risks in order to increase the efficiency in wind energy investments. In this context, companies should first ensure that they do not have a foreign exchange short position in their balance sheets by conducting an effective financial analysis. In addition, it is important to use financial derivatives to minimize the exchange rate and interest rate risks. Using these results, it will be possible to manage this risk by taking the reverse position for the existing foreign currency and interest risk. In this way, it will be possible to increase the efficiency of wind energy investments, which will contribute to the social and economic development of each respective country.Energies 2020, 13, 1423 2 of 25 their own energy resources can benefit from these resources [1]. This situation gives these countries a serious cost advantage. On the other hand, countries that do not have sufficient energy resources have to supply the energy they need from outside, which makes these countries dependent on energy. Because of this problem, countries are developing several strategies to produce their own energy [2].Renewable energy sources are an important alternative that allows countries to produce their own energy. The most important feature of these energy alternatives, which come in different forms, such as wind, solar, biomass, geothermal, and hydroelectricity, is that they obtain their resources from natur...

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Identifying critical success factors in Heart Failure Self-Care using fuzzy DEMATEL method

Cited by 52 publications

References 60 publications

A fuzzy DEMATEL approach for evaluating the risk factors

A fuzzy DEMATEL approach for evaluating the risk factors

Assessing Supply Chain Risks in the Automotive Industry through a Modified MCDM-Based FMECA

Multi-Faceted Analysis of Systematic Risk-Based Wind Energy Investment Decisions in E7 Economies Using Modified Hybrid Modeling with IT2 Fuzzy Sets

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