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Risk assessment is a very important step toward managing risks in various organizations and industries. One of the most extensively applied risk assessment techniques is failure mode and effects analysis (FMEA). In this paper, a novel fuzzy multiple-criteria decision-making (MCDM)-based FMEA model is proposed for assessing the risks of different failure modes more accurately.

In this model, the weight of each failure mode is considered instead of risk priority number (RPN). Additionally, three criteria of time, cost and profit are added to the three previous risk factors of occurrence (O), severity (S) and detection (D). Furthermore, the weights of the mentioned criteria and the priority weights of the decision-makers calculated by modified fuzzy AHP and fuzzy weighted MULTIMOORA methods, respectively, are considered in the proposed model. A new ranking method of fuzzy numbers is also utilized in both proposed fuzzy MCDM methods.

To show the capability and usefulness of the suggested fuzzy MCDM-based FMEA model, Kerman Steel Industries Factory is considered as a case study. Moreover, a sensitivity analysis is conducted for validating the achieved results. Findings indicate that the proposed model is a beneficial and applicable tool for risk assessment.

To the best of authors’ knowledge, no research has considered the weights of failure modes, the weights of risk factors and the priority weights of decision-makers simultaneously in the FMEA method.

The application of the traditional failure mode and effects analysis (FMEA) technique has been widely questioned in evaluation information, risk factor weights and robustness of results. This paper develops a novel FMEA framework with extended MULTIMOORA method under interval-valued Pythagorean fuzzy environment to solve these problems.

This paper introduces innovatively interval-value Pythagorean fuzzy weighted averaging (IVPFWA) operator, Tchebycheff metric distance and interval-value Pythagorean fuzzy weighted geometric (IVPFWG) operator into the MULTIMOORA submethods to obtain the risk ranking order for emergencies. Finally, an illustrative case is provided to demonstrate the practicality and feasibility of the novel fuzzy FMEA framework.

The feasibility and validity of the proposed method are verified by comparing with the existing methods. The calculation results indicate that the proposed method is more consistent with the actual situation of project and has more reference value.

The research results can provide supporting information for risk management decisions and offer decision-making basis for formulation of the follow-up emergency control and disposal scheme, which has certain guiding significance for the practical popularization and application of risk management strategies in the infrastructure projects.

A novel approach using FMEA with extended MULTIMOORA method is developed under IVPF environment, which considers weights of risk factors and experts. The method proposed has significantly improved the integrity of information in expert evaluation and the robustness of results.

Nowadays, the applications of metal matrix composites are tremendously increasing in engineering fields. Consequently, the demand for precise machining of composites has also grown enormously. The purpose of this paper is to reduce production cost and simultaneously improve desired product quality through optimal parameter setting using WASPAS and MOORA.

Metal matrix composites were fabricated using stir casting process, with aluminum 6063 as matrix and titanium carbide as reinforcement. Fabricated composite samples were machined on medium duty lathe using cemented carbide tool. All the experiments were carried out based on Box–Behnken design. Comparison of multi objective optimization based on ratio analysis and weighted aggregated sum product assessment in optimizing four parameters, namely, “cutting speed,” “feed rate,” “depth of cut” and “reinforcement weight percent of composite samples”; evaluating their influence on material removal rate, cutting force and surface roughness were carried out.

The output achieved by both MOORA and WASPAS are in similar MCDM) techniques in the selection of machining parameters.

The results obtained in the present paper will be helpful for decision makers in manufacturing industries, who work in metal cutting area, to select the suitable levels for the parameters by implementing the MCDM techniques.

The novelty of this paper is making an attempt to select better MCDM technique based on the comparison of results obtained for the individual technique.

The healthcare system is regarded as one of the most critical service industries. The surgical unit is the heart of hospitals in that any failures directly affect the safety of patients, so they should be managed thoroughly. It is an intricate multi-attributes decision-making problem with uncertainty. Uncertain information in the form of fuzzy sets theory has been applied widely to describe the different aspects of system uncertainty. This study aims to present a new methodology to manage the healthcare system failures due to the multi-attributes decision-making process.

This study introduces a new risk evaluation methodology by failure mode and effect analysis (FMEA) and MULTIMOORA method. Group decision-making process in this methodology is presented under uncertain information in the form of interval-valued hesitant fuzzy linguistic sets (IVHFLSs). IVHFLSs encompass both qualitative and quantitative interpretation of experts to reflect their preferences, as well the ability and flexibility of derivation of linguistic information by several linguistic terms increase. To avoid the different ranking order of MULTIMOORA approaches, a new interval multi-approaches multi-attribute methodology, namely, technique of precise order preference (TPOP), is extended to provide precise ranking order.

The application and precision of proposed integrated IVHFL-MULTIMOORA methodology with TPOP is examined in a case study of healthcare systems. The results indicate the superiority of proposed methodology to prioritize and assess the failures as well as handling system uncertainty.

This study addresses the challenges of an organization to prioritize potential failures by implementing FMEA method. Moreover, this paper contributes to making the manager's ability in decision-making. The value of this study can be discussed in two aspects. First and foremost, this study provides a new FMEA-based methodology to rank failures precisely. The results prove that the proposed methodology is more robust to changes of different ranking order methods, applied by FMEA. On the other hand, using the capability of IVHFLSs allows collecting accurate information in an ambiguous and uncertain environment.

Low cost carriers (LCCs) have become one of the most significantly growing parts of the airline servicing market. This new player has redesigned the whole airline industry, which was previously led by the national/international full-service airline companies. Considering such advancements, the hub locations of LCCs became an important issue than ever before. Within this concept, a guiding framework is developed for an LCC company, which is in search of a new hub airport location within Turkey to satisfy the demand and attract new passengers.

An interval-valued intuitionistic fuzzy (IVIF) sets based weighted aggregated sum product assessment (WASPAS) and multi-objective optimization by ratio analysis (MULTIMOORA) methods are developed for decision-making processes.

Five airport locations are evaluated using the developed method. Results showed that in determining hub locations for LCCs, potential number of passengers of the city, airport quality and the number of hotels within the city are obtained as the three most important criteria among 12 evaluation criteria. The best location for the LCC company is determined as Antalya Airport.

To apply the proposed method to a different set of alternatives, data gathered on comparing location of alternatives from experts should be updated.

Proposed hybrid framework is presented as the first time in the literature as a decision-making tool. In order to validate framework's applicability, efficiency and effectiveness, a comparison and a sensitivity analysis are conducted at the end of the study.

There have been numerous efforts to tackle the problem of accumulated construction and demolition wastes worldwide. In this regard, this study develops a model for identifying the optimum fleet required for waste transportation. The proposed model is validated through a case study from the construction sector in New Cairo, Egypt.

Various fleet combinations are assessed against the time, cost, energy and emissions generated from waste transportation. Genetic algorithm optimization is performed to select the near-optimum solutions. Complex proportional assessment and operational competitiveness rating analysis decision-making techniques are applied to rank Pareto frontier solutions. These rankings are aggregated using an ensemble approach based on the half-quadratic theory. Finally, a sensitivity analysis is implemented to determine the most sensitive attribute.

The results reveal that the optimum fleet required for construction and demolition wastes (CDW) transportation consists of one wheel loader of bucket capacity 2.5 cubic meters and nine trucks of capacity 22 cubic meters. Furthermore, consensus index and trust level of 0.999 are obtained for the final ranking. This indicates that there is a high level of agreement between the rankings. Moreover, the most sensitive criterion (i.e. energy) is identified using a sensitivity analysis.

This study proposes an efficient and effective construction and demolition waste transportation strategy that will lead to economic gains and protect the environment. It aims to select the optimum fleet required for waste transportation based on economic, social and environmental aspects. The usefulness of this study is establishing a consensual decision through the aggregation of conflicting decision makers' preferences in waste transportation and management.

The purpose of this paper is to present the augmented reality (AR) eyeglass selection problem based on Neutrosophic MULTIMOORA method which is a very new multi-objective method.

The author evaluates five AR goggles according to six different criteria. Criteria have different weights and determined by analytic hierarchy process. The author used neutrosophic MULTIMOORA method in order to evaluate AR eyeglasses.

Five different AR eyeglasses were evaluated and the best one was selected according to six different criteria (benefit and non-benefit). According to Neutrosophic MULTIMOORA method, Sony AR eyeglass is selected as the best one. Neutrosophic MULTIMOORA method uses simple computational equations and it handles multi-objective decision making problems effectively.

Evaluating AR goggles by using the Neutrosophic MULTIMOORA method for the first time is the originality of this paper.

This study aims to determine the ranking of the 81 provinces at the NUTS-3 level in Turkey with respect to the personal satisfaction and public services satisfaction by applying Fuzzy Multi-Criteria Decision-Making methods to the Life Satisfaction Survey Results.

Fuzzy TOPSIS, Fuzzy MULTIMOORA and Fuzzy ARAS are implemented to assess life satisfaction of the individuals who lived in provinces, based on Life Satisfaction Survey 2013 for Turkey’s national comparison. In the solution process, 14 indicators for personal satisfaction and 38 indicators for public services satisfaction were considered.

The results showed that personal health satisfaction, earnings from work satisfaction and monthly income satisfaction are the most important criteria in terms of personal satisfaction. Also, healthcare services satisfaction, judicial services satisfaction and education services satisfaction have the highest importance in terms of public services satisfaction. The final ranking of the 81 provinces is obtained by considered methods. According to the ranking results, there is no significant difference between the east and the west part of Turkey in terms of personal satisfaction, whereas there is a distinct difference between them in terms of satisfaction with public services.

This study is the first research for evaluating the ranking of the provinces at the NUTS-3 level in Turkey according to the Life Satisfaction Survey 2013 results considering 14 indicators for personal satisfaction and 38 indicators for public services satisfaction by using FMCDM approaches that have not been applied before.

This study aims to identify and accurately assess the risk factors of competitors’ cooperation in the NPD project.

New product development (NPD) is essential to the survival of companies and surpassing other competitors. A key prerequisite for the success of an NPD project is the timing of new product delivery to the market. The main challenge faced by many project managers is the delay in execution and completion phases due to the complex nature and uncertainty of these projects. Rival companies' cooperation reduces the time spent on an NPD project which is an excellent way to reduce the risk of losing the market, but it increases other risk factors.

Based on the results, the security and confidentiality of innovation, the competitors attracting human resources and the company’s brand credibility factors were ranked higher than other factors and should be predicted and managed before cooperating with competitors.

This paper proposed a new model to assess risk factors in cooperation with rival companies in NPD projects. This model takes into account new parameters, for example, negative and positive risks, negative and positive passable risks and risk-based multi-objective optimization by ratio analysis plus full multiplicative form methodology for the rival companies cooperation in NPD projects. To evaluate the efficiency of the proposed model, a real case of the R&D unit of Iran Khodro Company was studied.

Existing studies have found that most merger and acquisition (M&A) activities do not create the intended synergy. These studies have mainly investigated how firms' internal factors contribute to M&A successes or failures. The current study differs from the earlier ones by exploring how governments' activities can contribute to the creation of acquisition synergy.

A novel technique based on multi-objective optimization by ratio analysis and complex proportional assessment method under an interval-valued intuitionistic fuzzy (IVIF) environment is proposed to prioritize these government roles needed during the M&A process focusing on the Chinese M&A market.

Enactments of regulations and loan guarantees are the most important strategies to help Chinese acquirers overcome acquisition failures. While tax relief ranks third, government training support ranks fourth. Finally, the result shows that government institutional support is the least to help acquirers overcome acquisition failures.

The government has a role to play in the acquisition success. Although this study has prioritized governments' role in relative importance order, the authors recommend that governments capable of providing all these strategies should do so without any specific order. However, if otherwise, governments should not neglect the strategies with less weight completely but rather consider reducing capital allocations to such strategies. Moreover, this study shows how firms with stronger business ties with government officials may enjoy success during acquisition activities. The authors recommend that firms intending to make acquisitions develop stronger ties with governments in order to benefits from governments.

This is the first study to develop a theoretical framework showing how government can contribute to M&A success. The study achieves this by extending Keynesian's arguments and identifies five (5) ways in which governments can ensure acquisition success. Second, within fuzzy multi-criteria decision-making (F-MCDM) research, this study is the first to show the applicability of integrated multi-objective optimization by ratio analysis (MULTIMOORA) and complex proportional assessment (COPRAS) techniques in an IVIF environment. The novel methodology proposed in this study offers an insightful research method to future studies focusing on group decision problems.