Building cyber-resilience in maritime transport: A stakeholders’ perspective on mitigation measures

Occupational health and safety (OHS) management is a cycle of decision-making processes, many of which are in fact multi-criterion processes in nature. Therefore, it is important to look for and develop tools to support decision-makers in their actions aimed at improving work safety levels. The objective of this paper is to propose and verify the fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method applied to compare and assess the ways OHS management systems function in different companies. The fuzzy TOPSIS method has already been used for a number of years in assessments of alternative solutions in many different areas, but the application that uses ordered fuzzy numbers is quite original in nature. It is especially beneficial to use the fuzzy approach in OHS management systems, as it makes it possible for experts to assess different criteria using most frequently used linguistic variables. The adopted approach was verified in the study of OHS management systems in four furniture manufacturing companies. Assessment criteria were requirements of the PN-N 18001: 2004 Standard. Thanks to the ordered fuzzy TOPSIS method, the analysed OHS management systems were streamlined from the point of view of 24 assessment criteria, and the best and the worst functioning system was identified. The approach presented here may constitute a significant tool for improving OHS management systems.

Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods

Streamlining apartment provider evaluation: A spherical fuzzy multi-criteria decision-making model

This paper presents fuzzy TOPSIS (technique for order preference by similarity to ideal solution) method for academic member selection. In academic member selection problem the ratings of various alternatives versus various subjective criteria and the weights of all criteria are assessed in linguistic variables represented by fuzzy numbers. Fuzzy numbers try to resolve the ambiguity of concepts that are associated with human being’s judgments. To determine the order of the alternatives, closeness coefficient is defined by calculating the distances to the fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS). Universities can select the appropriate academic member by using fuzzy TOPSIS method. By this way the quality of education will be increased in universities.

Evaluation of flexibility components for improving housing quality using fuzzy TOPSIS method

In this paper, we propose Multi Criteria Decision Making (MCDM) problem is one of the famous different kind of decision making problem. In more cases in real situations, determining the exact values for MCDM problems is difficult or impossible. So, the value of alternatives with respect to the criteria or / and the values of weights, are considered as fuzzy values (fuzzy numbers). In such conditions, the conventional crisp approaches for solving MCDM problems tend to be less effective for dealing with the imprecise or vagueness nature of the linguistic assessment. In this situation, the fuzzy MCDM method are applied for solving MCDM problems. Here, fuzzy TOPSIS (Technique for order preference by similarity to ideal solution) method based on a fuzzy distance measure is used in which the distance from the Fuzzy Positive Ideal Solution (FPIS) and Fuzzy Negative Ideal Solution (FNIS) are calculated. The resulted distances were used to calculate the similarity to ideal solution. Later an optimal membership degree (Closeness co-efficient) of each alternative is computed to estimate to which extent an alternative belongs to both FPIS and FNIS. The closer the degree of membership of FPIS and the farther from FNIS the more preferred the alternative. The membership degree is obtained by the optimization of a defined objective function that measures the degree of which an alternative is similar / dissimilar to the ideal solutions. A numerical example is also demonstrate the procedure of the proposed fuzzy TOPSIS method in the decision making processes.

Due to inequality, millions of people in sub-Saharan Africa lack access to reliable and affordable energy. Attempts to address this challenge have led to the application of different approaches to energy management, such as non-linear modeling techniques. While these approaches have been used to generate information about technical requirements for solving energy inequality, limited information existscresocio-economic information about energy inequality. This research, therefore, uses a multi-criteria decision-making (MCDM) framework to address energy inequality in sub-Saharan Africa. The framework contains a fuzzy analytical hierarchical process (FAHP) for determining criteria importance and VIKOR (VIseKriterijumska Optimizacija i Kompromisno Resenje) for emerging socio-economic criteria and mitigation strategies for energy inequality. Also, the framework contains nine socio-economic criteria and ten mitigation strategies. A sub-urban community was used to evaluate the framework performance. This study compared the VIKOR method performance with a fuzzy PROMETHEE (reference Ranking Organization METHod for Enrichment Evaluation) and a fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. The results from the FAHP method showed that environmental sustainability was the fundamental criterion for evaluating mitigation strategies for energy inequality. On the other hand, the results from the VIKOR method indicated that decentralized renewable energy solutions were the most suitable strategy for addressing energy inequality. According to the TOPSIS method results, cross-subsidization models was the best strategy for addressing energy inequality. Based on Spareman's correlation results for VIKOR and TOPSIS methods, it was observed that a significant association between these methods. On the other hand, there was no significant correlation between the VIKOR and PROMETHEEE results. The aggregation of the VIKOR, PROMETHEE, and TOPSIS results show that decentralized renewable energy solution was the best strategy for addressing energy inequality for the case study. The research findings will guide stakeholders, especially investors, on the best action for investment initiatives in sub-Saharan Africa.

Purpose Selection of target market entry strategy in the international market significantly affects the success of the company in international markets. The purpose of this study is to analyze international market entry strategy of a Turkish home textile company that has its own brand with hybrid fuzzy Multi-Criteria Decision-Making (MCDM) methods. Design/methodology/approach In the first stage, 5 criteria and 30 sub-criteria were selected with the help of the literature review and the experts working in the company. In the second stage, criteria weights were determined with Fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) method and in the third stage, the best international market entry strategy was selected using Fuzzy CODAS (Combinative Distance-Based Assessment) method. Findings The top three most important criteria for entering the Gulf countries target market were obtained as Return on investment (C36), Market size (C11) and Financial resources of company (C34). Franchise (A2) was chosen as the most appropriate international target market entry strategy. The same results were obtained using Fuzzy CODAS, Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and Fuzzy EDAS (Evaluation based on Distance from Average Solution) methods. Research limitations/implications Results depend on the experience and observations of the expert group limited to single textile company. Hybrid model formed with Fuzzy PIPRECIA, Fuzzy CODAS, Fuzzy TOPSIS and Fuzzy EDAS methods provides convenience in deciding international market entry strategy with uncertain and complex information. Practical implications The proposed fuzzy hybrid model is expected to assist managers in selecting international market entry strategy by providing different perspective. Also, policymakers can extend this study to different countries for analyzing differences in international market entry strategies among countries. Social implications To facilitate companies for the selection of international market entry strategy. Originality/value The originality of this study is the application of hybrid approach based on Fuzzy PIPRECIA and Fuzzy CODAS methods in international market entry strategy selection problem of a textile company which includes a large number of criteria and sub-criteria. According to comparative analysis, the same result is obtained with three Fuzzy MCDM methods and sensitivity analysis is applied according to the changes in criteria weights.

During the COVID-19, colleges organized online education on a massive scale. To make better use of online education in the post-epidemic era, this paper conducts an online education satisfaction survey with four types of colleges and 129,325 students propose a fuzzy TOPSIS (technique for order preference by similarity to ideal solution) method based on the cloud model to rank the satisfaction of different colleges. Firstly, based on the characteristics of online education during the COVID-19, we build an evaluation indicator system from four dimensions: technology, instructor, learner and environment including, 10 indicators and 94 sub-indicators. Secondly, the cloud model is used to quantitatively describe the natural language and uncertainty in a large amount of assessment information. The cloud model generator is used for sub-indicators and achieves an effective and flexible conversion between linguistic information and quantitative values. The cloud model of indicators are presented by integrating the corresponding sub-indicators. The weights of indicators are determined by the entropy method based on the cloud model and possibility degree matrix, which eliminates the judgment of decision-makers and has great power for handling practical problems with unknown weight information. Finally, a fuzzy TOPSIS method based on the cloud model is proposed to rank the satisfaction of online education of different colleges. The proposed method is compared with other existing methods to shown its merits. The experimental result is consistent with the proportion of students who accept online education in the post-epidemic era. According to the second questionnaire, as the qualitative evaluation of the cloud model of indicators increases, the qualitative evaluation of satisfaction of different types of colleges will also increase. It indicates that the method proposed in this paper is practical.

Fuzzy Multiple Criteria Decision Making plays an important role in solving problems in decision making under fuzzy environment. Among the popular methods used is the fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) where the solution is based on the shortest distance from its positive ideal solution and the farthest distance from its negative ideal solution. The fuzzy TOPSIS method was first introduced by Chen (2000). At present, there are several variants of fuzzy TOPSIS methods and each of them claimed to have its own advantages. In this paper, a comparative analysis is made between the classical fuzzy TOPSIS method proposed by Chen in 2000 and the simplified fuzzy TOPSIS proposed by Sodhi in 2012. The purpose of this study is to show the similarities and the differences between these two methods and also elaborate on their strengths and limitations as well. A comparison is also made by providing numerical examples of both methods.

The fuzzy TOPSIS applications in the last decade

As foreign trade has become more spread, the country of production and even the origin of the raw material used in the production has become an important factor. Mentioning the country of origin on the label of the product dates back to World War-I when “Good product sells itself” understanding is dominant. In this study, the image of country of origin was evaluated with fuzzy set theory. Fuzzy sets theory lays foundation for the methods used in the solution of relative and uncertain problems. As image evaluation is a relative issue, these methods were used in our study. The first phase in the study model is data collection. Data collected was used to determine image factors, calculate factor loads (weights) and order alternatives. In the determination of image factors Fuzzy Cognitive Mapping (FCM) method was employed. To calculate factor and alternative weights Fuzzy Analytic Hierarchy Process (AHP) method was used. In the phase of ordering of alternatives which are called product group elements both Fuzzy AHP and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method were employed. TOPSIS is based on the main principle of similarity to ideal solution and is employed to solve problem and make decision. In our study FCM, Fuzzy AHP and TOPSIS methods were used in stages, analyses were performed and solutions were developed. In the final part, there are evaluations with regard to which product group will be more effective when which image is minimized.

Among several computing models in Health Insurance, the selection of appropriate health insurance is necessary for gaining higher beneficial profit during critical situations. Sometimes the random selection of Health Insurance leads to bad results. In this paper, we proposed the Multiple Criteria Decision Making (MCDM) theory to make a decision about the best form of health insurance. This MCDM is one of the best ideal solutions to overcome bad results. We implemented TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method for choosing the best Health Insurance. In the TOPSIS method, we have defined the Fuzzy TOPSIS hesitant method for a decision-making scenario for multi-criteria. The advantages of hesitant fuzzy TOPSIS approaches are flexibility, consistency, understandability, strong analytical efficiency and the ability to calculate the relative strength in a simple mathematical form for each alternative. In this, we used linguistic and Intuitionistic decision-makers. Here multiple objectives like 1.beneficial and non-beneficial 2.fuzzy weightage for attributes are used for group decision making. In the Health Insurance scenario we have multi attributes like 1.individual plan 2.family plan 3.entry age 4.premium 5.claim 6.sum assured that are applied to all Health Insurance and by using the above methods.

The selection of an appropriate spillway has a significant effect to the construction of a dam and several procedures and considerations are needed. In the past, this selection of the type of the spillway was arbitrary and sometimes with bad results. Recently the Multiple Criteria Decision Making theory has given the possibility to make a decision about the optimum form of a spillway under complex circumstances. In this paper, the above method is used and especially the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method for the selection of a spillway for a dam in the district of Kilkis in Northern Greece—‘Dam Pigi’. As the criteria were fuzzy and uncertain, the Fuzzy TOPSIS method is introduced together with the AHP (Analytic Hierarchy Process), which is used for the evaluation of criteria and weights. Five types of spillways were selected as alternatives and nine criteria. The criteria are expressed as triangular fuzzy numbers in order to formulate the problem. Finally, using the Fuzzy TOPSIS method, the alternatives were ranked and the optimum type of spillway was obtained.

A fuzzy multi criteria risk assessment based on decision matrix technique: A case study for aluminum industry