Fuzzy DEMATEL Method Research Articles

AN INTEGRATED MODEL APPROACH WITH FUZZY MULTI CRITERIA DECISION MAKING METHODS FOR THE SELECTION OF THIRD PARTY LOGISTICS FIRM IN THE FOOD INDUSTRY

The purpose of this study was to determine third party logistics company selection and evaluation criteria and to help make the most suitable selection among the alternatives in the food sector. Another purpose was to present a mixed model by integrating fuzzy multi criteria decision making methods in third-party logistics company selection process. The combination of fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS methods were used in this study. A decision network was created by evaluating the interactions between the criteria determined depending on the decision goal. This study was conducted in a large scale company producing milk and dairy products in food sector. As a result of the analyses made and the findings obtained, technology, delivery performance and quality were found as the criteria having the highest scores in terms of effectiveness. In addition, it was also determined that the most affected criterion among the criteria was the company image. The S2 Company was selected as the best third-party logistics company as a result of the evaluation of alternatives. The integrated fuzzy methods used in this study were used for the first time in the selection and evaluation of third-party logistics companies. And three new criteria; namely, portage price, hygiene and vehicle were added to the related literature which did not exist before.

Analysis of quality control criteria in an business with the fuzzy DEMATEL method: Glass business example

Quality is at the forefront of the issues to which the production and service sectors attach importance. Increasing customer satisfaction, gaining competitive advantage in the industry, increase in sales vb. for many reasons, companies have increased the importance given to quality control. Before sending the products to the customer, taking into account the necessary quality control criteria, the control of the products will contribute to the solution of any problems that may arise in advance. Especially in sectors where energy and capital are intense, and the capacity is very high, it is one of the fundamental processes that should be done in the company, inspection of products taking into account all quality control criteria. Therefore, it is essential to consider the glass industry in this sense. This study determines the critical value of the quality control criteria on the glass, which a company that produces tempered glass pays attention to before putting the product used as a contract into production. Control criteria were determined by interviewing a team of experts in the company, and then the criteria were evaluated by experts. Then, fuzzy DEMATEL method, which is one of the multi-criteria decision-making techniques, was used and the relations of the criteria with each other were determined. As a result of the calculations made with fuzzy DEMATEL, the criteria are listed as K1 > K2 > K4 > K7 > K6 > K5 > K3 and the aspect measurement with a criterion weight of 0,150 was found to have the most significant effect on the glass.

An Integrated Fuzzy DEMATEL and Fuzzy TOPSIS Method for Analyzing Smart Manufacturing Technologies

I4.0 promotes a future in which highly individualized goods are mass produced at a competitive price through autonomous, responsive manufacturing. In order to attain market competitiveness, organizations require proper integration of I4.0 technologies and manufacturing strategy outputs (MSOs). Implementing such a comprehensive integration relies on carefully selecting I4.0 technologies to meet industrial requirements. There is little clarity on the impact of I4.0 technologies on MSOs, and the literature provides little attention to this topic. This research investigates the influence of I4.0 technologies on MSOs by combining reliable MCDM methods. This research uses a combination of fuzzy DEMATEL and fuzzy TOPSIS to evaluate the impact of I4.0 technologies on MSOs. The fuzzy theory is implemented in DEMATEL and TOPSIS to deal with the uncertainty and vagueness of human judgment. The FDEMATEL was utilized to identify interrelationships and determine criterion a’s weights, while the fuzzy TOPSIS approach was employed to rank the I4.0 technologies. According to the study’s findings, cost is the most critical factor determining MSOs’ market competitiveness, followed by flexibility and performance. On the other hand, additive manufacturing (AM) is the best I4.0 technology for competing in the global market. The results present an evaluation model for analyzing the relative important weight of multiple factors on MSOs. They can also assist managers in concentrating on the most influential factors and selecting the proper I4.0 Technology to preserve competitiveness.

A Comprehensive MCDM-Based Approach for Object-Oriented Metrics Selection Problems

Object-oriented programming (OOP) is prone to defects that negatively impact software quality. Detecting defects early in the development process is crucial for ensuring high-quality software, reducing maintenance costs, and increasing customer satisfaction. Several studies use the object-oriented metrics to identify design flaws both at the model level and at the code level. Metrics provide a quantitative measure of code quality by analyzing specific aspects of the software, such as complexity, cohesion, coupling, and inheritance. By examining these metrics, developers can identify potential defects in OOP, such as design defects and code smells. Unfortunately, we cannot assess the quality of an object-oriented program by using a single metric. Identifying design-defect-metric-based rules in an object-oriented program can be challenging due to the number of metrics. In fact, it is difficult to determine which metrics are the most relevant for identifying design defects. Additionally, multiple thresholds for each metric indicates different levels of quality and increases the difficulty to set clear and consistent rules. Hence, the problem of object-oriented metrics selection can be ascribed to a multi-criteria decision-making (MCDM) problem. Based on the experts’ judgement, we can identify the most appropriate metric for the detection of a specific defect. This paper presents our approach to reduce the number of metrics using one of the MCDM methods. Therefore, to identify the most important detection rules, we apply the fuzzy decision-making trial and evaluation laboratory (Fuzzy DEMATEL) method. We also classify the metrics into cause-and-effect groups. The results of our proposed approach, applied on four open-source projects, compared to our previous published results, confirm the efficiency of the MCDM and especially the Fuzzy DEMATEL method in selecting the best rules to identify design flaws. We increased the defect detection accuracy by the selection of rules containing important and interrelated metrics.

A Fuzzy DEMATEL framework for maintenance performance improvement: A case of Moroccan Chemical Industry

Maintenance performance has vital importance for enterprises to continue their operations without any interruption. The satisfaction of stakeholders and the achievement of strategic goals in a manufacturing organization are highly dependent on effective maintenance performance. A good management system is essential to achieve the desired level of performance. A good management system could be divided into two main parts. The first part consists of identifying and determining the most relevant indicators for maintenance. The determined indicators have to be measured to offer a comprehensive examination of their performance. The second part consists of improving the maintenance performance; however, from the multi-criteria aspect, system performance improvement requires simultaneously various limited sources such as time, resources, and skills. Therefore, improving maintenance performance needs to assign priority to the most critical indicators to use limited resources effectively; however, this is not easy to achieve. Furthermore, the benefit of such efforts may be less than the expected level. In this context, this paper proposes an approach to improve maintenance performance based on the Fuzzy DEMATEL method. The proposed method identifies and priorities the most sufficient indicators to improve overall maintenance performance of an enterprise. Consequently, DMs can put in place the most appropriate action plan, which allows an effective and efficient enhancement of the maintenance performance. Then, the proposed method is implemented in the case of Moroccan Company which is one of the leaders in the chemical industry. The results of this research allow DMs to develop the most advantageous action plan for effective and efficient improvement of both local and global maintenance performance in the company.

Analyzing Interdependencies among Influencing Factors in Smart Manufacturing

The manufacturing industry has grown increasingly computerized and complex. Such changes are brought about mainly by adopting Industry 4.0 (I4) technologies. I4.0 promises a future of mass-producing highly individualized goods via responsive, autonomous, and cost-effective manufacturing operations. Adopting I4.0 technologies significantly improves a company’s productivity, efficiency, effectiveness, innovation, sustainable management, and sustainability. As is well known, implementing I4.0 technologies results in smart and sustainable manufacturing outputs. Despite their significance, I4.0 technologies have received less attention in the literature, and their influence on MSOs is unknown. This study analyzes the factors influencing manufacturing strategy outputs (MSOs), adopting I4.0 technologies using the fuzzy DEMATEL method. This research utilizes the fuzzy DEMATEL method to address the vagueness and uncertainties inherent in human judgments. Furthermore, this method is utilized to determine the cause-and-effect relationship and analyze the interdependence of factors. It explores the interrelationships among MSO factors from the perspectives of academic and industry experts. Identifying cause-and-effect aspects boosts the market’s competitiveness and prioritizes them. The results demonstrated that cost, quality, and performance are the most influential factors on MSOs.

Investigating changes of total quality management principles in the context of Industry 4.0: Viewpoint from an emerging economy

Industry 4.0 will radically affect Total Quality Management (TQM) practices and principles, which are still widely used in businesses and one of the management practices. Some TQM principles, with the developed technology and systems, have become “natural management principles” whose application in the organization is fully guaranteed and the system is made to exist on its own. While some principles become easier to implement, some TQM principles and practices may need to be repositioned in terms of business management. For this reason, in this study, after a comprehensive TQM and Industry 4.0 literature research and analysis, the situation and interaction of TQM principles in enterprises that implement Industry 4.0 (I4.0), both a modeling and a survey study were made within the framework of ISO 9001:2015 TQM Principles to determine the changes in TQM principles in the I4.0 environment. Statistical analyses were performed determining relationship among TQM principles and direction of these relationships. In addition, the fuzzy DEMATEL method was applied to determine the interactions of TQM principles in the I4.0 environment. As a result, evidence-based decision making, continuous improvement and process management principles are applied much more easily with I4.0, the principles of leadership and employee participation continue to develop.

The influencing factors and mechanisms for urban flood resilience in China: From the perspective of social-economic-natural complex ecosystem

Urban flood is one of the most frequent and deadly natural disasters in the world, seriously affecting urban sustainability and people's well-being in China. As the largest developing country in the world, China urgently needs to improve its urban flood resilience. Previous studies related to urban flood resilience are mostly focused on its assessment method and simulation. However, few studies directly aim to reveal the influencing factors of urban flood resilience and their inner relationships. In order to make a significant contribution to the long-term improvement of urban flood resilience in the context of global climate change and urbanization, it is crucial to explore the influencing mechanisms of urban flood resilience. This study aims to identify key influencing factors and their interactions on urban flood resilience in China. To this end, a conceptual framework based on Pressure-State-Response model and Social-Economic-Natural Complex Ecosystem theory (PSR-SENCE model) are established and 24 factors are identified within three dimensions. The relationships between the factors are tested using a fuzzy-DEMATEL method. The results reveal that factors in pressure and response dimensions have a greater impact on the whole system, while the factors in the state dimension are more influenced by the other two dimensions. The results identify 14 critical factors, with four detailed influence paths discussed among the different dimensions. Accordingly, the implications for improving urban flood resilience are discussed within the context of the key influencing paths. The study provides a theoretical basis and approach to directly explore how the factors influencing urban flood resilience and proposes specific impact paths and improvement implications.

A Comparative Analysis of Applied FMADM in a Serious Games Evaluation Model

In recent years, Serious Games are being used as an innovative pedagogical strategy to achieve more effective learning in various fields of knowledge, but in order to use them effectively, it is essential to evaluate them systematically to obtain solid evidence of their impact. To this end, the integration of fuzzy multi-attribute decision making (FMADM) methods will be beneficial for the evaluation of Serious Games in order to weight their evaluation criteria according to the desired context, as these FMADMs have the capacity to take into account the imprecision and uncertainty of human judgements. In this paper, we will present a comparative analysis of various fuzzy multi-attribute decision making (FMADM) techniques, namely the fuzzy DEMATEL and fuzzy SWARA methods applied in the Serious Games evaluation model in which the fuzzy AHP method has been used. In order to find the ranking of various dimensions responsible for better decision making and the ability to accurately reflect human judgment for the evaluation of Serious Games in a given context. According to the results obtained, we find that the fuzzy AHP method was the best suited to our decision problem, despite the identical ranking of the criteria obtained.

Determination of critical catalyst preparation factors (cCPF) influencing hydrogen evolution

In recent years, the energy crisis has gotten worse as a result of global challenges like the pandemic and the Ukraine crisis. To solve this problem, researchers have focused on development of sustainable resources and renewable energy infrastructure for its potential as a promising and effective strategy. Hydrogen is a significant energy carrier that will fulfill global energy demand while also significantly reducing greenhouse gas (GHG) emissions in the future decades. The catalysts used in hydrogen generation have a substantial effect on hydrogen efficiency, however unknown parameters affecting catalyst activity throughout the catalyst preparation process are a major source of concern. The most essential components are to accurate determination the development conditions of the catalysts used in the hydrogen generation. The main objective is to produce hydrogen energy with high efficiency thereby reducing the currently usage of fossil fuels, which are currently used in transportation, industry, home, and commercial applications. This study's aim is to examine critical catalyst preparation factors (cCPF) that have an effect on the efficiency of the catalyst using the fuzzy DEMATEL method. In this regard, twelve cCPF were identified based on literature review and in consultation with experts and the causal relationships among critical factors were visualized with the proposed method. The results highlighted that the most critical CPF that should be tackled to improve hydrogen generation efficiency are: appropriate reduction temperature (F), and the appropriate reduction agent concentration (G), drying conditions (L), drying time (M) and calibration of instruments and equipment (N). The findings of this study can be used to researchers and decision-makers for improving the overall performance of catalysts.

Modeling factors affecting the interests of the container terminal using fuzzy cognitive map and fuzzy DEMATEL

PurposeBecause container terminals (CTs) are broker organizations, their interest has complex, various internal and external factors, the purpose of this study is to scrutiny and structure the factors affecting the interests of the CT.Design/methodology/approachIn terms of purpose, this study is a developmental study that, are identified the factors related to the interests of the CT through studying the library and interviewing experts and then the degree of influence of each factor on each other by using the interview with experts of CT in Bushehr province are determined. Then, the fuzzy DEMATEL method is used to calculate the feedback loop of the indicators, and then the matrix obtained Fcmapper software and the fuzzy cognitive map (FCM) is drawn.FindingsAccording to the FCM analysis, three important factors are centrality identified in terms of attracting capital, quality of service and efficiency. In addition, there are three factors, attracting capital, operator performance and law have high outdegree.Originality/valueThis research has identified 34 effective indicators of CT interests and evaluated their relationship with FCM. In the available researches, all these indicators measurement has not been evaluated together. Furthermore, fuzzy DEMATEL has been used to evaluate self-loops. Another contribution of this research is the introduction of a strategic route as a roadmap for CT managers in Bushehr province to decide on the interests of a CT.

Causations Analysis of a High-Speed Railway Accident Using Extended 24Model with Interval Type-2 Fuzzy DEMATEL Method

One of the most significant goals that must be guaranteed for high-speed railway systems is safety. A new model is constructed for high-speed railway accident analysis with interval type-2 fuzzy DEMATEL method based on the 24Model. Specifically, the 24Model is introduced to identify the accident factors from four stages at the individual and organizational levels. The DEMATEL method is combined with interval type-2 fuzzy sets to analyze the key causations of the accident considering the interrelationships between factors under an uncertain environment. A specific case of the “7.23” Yong-Tai-Wen railway accident is employed to validate the proposed model. The analysis results show that poor management of the ministry of railways, imperfect rules and standards and little supervision or inspection are core organizational factors that lead to accidents. Besides, unsafe material conditions and unsafe human conditions are the direct causes of the accident which are easily influenced by other accident factors. The relevant managers need to strengthen the inspection to ensure the safe operation of the high-speed railway.

How to Identify Barriers to the Adoption of Sustainable Agriculture? A Study Based on a Multi-Criteria Model

The world’s population grows yearly, so increasing food production is necessary, to meet consumer demands. This production must be clean; thus, sustainable agriculture seems to represent a solution. However, social, economic, and environmental barriers impede the adoption of this practice. Therefore, this research identified these barriers, according to the sustainability triple-bottom line through a literature review, and analyzed which barriers are more influential and vulnerable to influences, using the Fuzzy DEMATEL method, as well as by considering the opinions of 30 mixed crop producers. As a result, eleven barriers were identified; and “technical knowledge and qualified workforce” was the most influential on not adopting sustainable agriculture. A multi-criteria model was provided and could be replicated in further research. Thus, sustainable practices are provided, to minimize the barriers’ negative impacts and assist producers; highlighting investment and policies for training farmers to have the technical knowledge to practice sustainable agriculture. Theoretical implications were reviewed, such as an analysis of the barriers found in the literature and the lack of studies reporting on the difficulty of producers in adopting sustainable agriculture, as well as the practical implications of providing assistance and transferring knowledge, to eliminate these barriers, so that sustainable practices can be efficiently implemented.

Modeling cause-and-effect relationships among variables affecting work stress based on fuzzy DEMATEL method

Purpose Several variables can affect work stress. This study aims to model the cause-and-effect relationships among different variables that can predict work stress based on one of the most important fuzzy multicriteria decision-making methods used to investigate the cause-and-effect relationships among variables. Design/methodology/approach This study was conducted in 2020, including 17 experts in safety management, occupational health and work psychology, based on the fuzzy decision-making trial and evaluation laboratory method as a robust approach to identify the cause-and-effect relationships among different variables. Findings Shift work, lack of job satisfaction, mental health, mental overload, fatigue, job security, sleep disorders, environmental discomfort, work pressure, job knowledge (this could mean expertise/level of qualifications/familiarity with the job), work complexity and role conflict were found to be the most significant variables affecting work stress. Moreover, the cause-and-effect model of relationships among variables showed that shift work and lack of job satisfaction are root causes, and mental health, fatigue, mental workload, sleep disorder and environmental discomfort are direct causes. Originality/value Although the results of this study demonstrate that work stress can be influenced by 12 different variables, the modeling results show that some variables, such as shift work and lack of job satisfaction, can directly or indirectly impact other variables and thus result in work stress.

A hybrid framework to model resilience in the generic medicine supply chain of MSMEs

PurposeOne of the most important components of healthcare is the timely delivery of pharmaceutical products, such as life-saving medicines. However, disruptions like COVID-19 bring new challenges and risks to the pharmaceutical supply chain (PSC) and healthcare organizations that impact their operational performance. This study focuses on mitigating risks in India's generic medicine supply chain (GMSC) as a result of various disruptions, which can assist policymakers develop appropriate plans and strategies to build resilience in the Jan Aushadhi Scheme (JAS) of micro, small and medium enterprises (MSMEs) in order to improve their overall performance.Design/methodology/approachRisk-causing vulnerabilities and resilience capabilities are identified from the literature review and expert's opinions. Following that, the vulnerabilities are classified into cause-and-effect vulnerabilities, and supply chain resilient capabilities (SCRCs) are measured using a hybrid fuzzy DEMATEL and best worst method (FDEMATEL-BMW) framework.FindingsThe outcome of the study reveals that transportation breakdown, loss of human resources and loss of suppliers are the potential risk-causing vulnerabilities that lead to vulnerabilities like shortages of medicines, loss of in-hand stock qualities and loss of sales/revenue. In addition, the analysis suggests that the sustainability of an organization with maximum weightage is the critical factor for building resilience in GMSC followed by flexibility, agility and visibility.Practical implicationsThe integration of resilience into Jan Aushadhi GMSC can help in managing disruptions efficiently and effectively to mitigate risk and optimize MSMEs overall performance.Originality/valueTo the best of the authors’ knowledge, this work will be the first of its kind to model resilience in GMSC of MSMEs using a hybrid framework.

Drivers Affecting Bitcoin Adoption as a Payment Mechanism in the Tourism Industry

While travelers' desire to visit the world's most remote places has grown, the inefficiency of global payments indicates a significant barrier to tourism growth. As an emerging, decentralized, and borderless digital innovation, Bitcoin technology seems to have the ability to serve as a payment alternative and address such fundamental inefficiencies. On the other hand, bitcoin adoption can only happen when tourists and business owners choose to operate bitcoin simultaneously. The study has developed a novel Bitcoin Collaborative Network and Tourism Collaborative Network model to examine Bitcoin adoption factors. Then a fuzzy DEMATEL method was applied to the factors influencing the adoption domain, as identified based on an extensive literature review, in-depth interviews, and an international Delphi process. The study offered a model for the heterogeneous collaborative network of Bitcoin and Tourism (BCN and TCN), revealing that Perceived Usefulness is the most influencing criterion and the most prominent variable in Bitcoin Adoption. Bitcoin Technological Complexity, Government Regulatory, and Bitcoin Awareness are the factors that give the highest impacts. Also, Bitcoin's Technological Complexity is the most significant factor in bitcoin adoption. The findings might assist businesses in adopting a new market expansion strategy and benefiting from technological spillover, while government officials can explore new supporting legislation.

A novel alpha-level sets based fuzzy DEMATEL method considering experts’ hesitant information

Fuzzy DEMATEL method is diffusely employed to analyze the interrelationship among factors in various fields under uncertain and fuzzy environment. In the extant fuzzy DEMATEL studies, fuzzy assessments are converted into related crisp values by means of different defuzzification ways. Such conversion may result in not only the loss of information, but also the discount of consideration of fuzzy information. Therefore, it seems reasonable and necessary to keep as much information as possible during the analysis process, instead of converting it into crisp values at the very beginning. An appropriate way to keep as much information as possible is to employ alpha level sets to handle fuzzy information instead of simple defuzzification. In addition, it is quite common that experts may hesitate under uncertain and fuzzy environment in the real-world situation, when providing their assessments on the interrelationship among factors. However, such practical issue is neglected in the extant fuzzy DEMATEL methods. With respect to aforementioned limitations, this study proposes a novel alpha level sets based fuzzy DEMATEL method to handle the fuzzy information, together with considering experts’ hesitation from qualitative context under uncertain and fuzzy environment. Additionally, two different options are provided to analyze the interrelationship among factors in the proposed method. The proposed method not only improves the extant fuzzy DEMATEL studies, but also enriches the theoretical studies of fuzzy DEMATEL, its novelty and superiority is demonstrated through illustrative example and related comparisons.

Performance measurement of lean supply chain management: a balanced scorecard proposal

The purpose of this paper is to propose a performance measurement framework to evaluate Lean Supply Chain Management (LSCM) performance. A literature review was performed to identify the main goals and performance indicators in LSCM. A questionnaire was designed that included the identified goals and measures. Next, based on data collected from international academics and practitioners with expertise in LSCM, a two-stage Delphi study using Fuzzy Delphi and Fuzzy DEMATEL methods was carried out to refine the most relevant goals and metrics and their interrelationships and establish benchmark values that are useful for managers to evaluate the performance achieved through the deployment of lean principles, practices, and techniques throughout the supply chain. Finally, an integrated performance measurement framework based on the balanced scorecard approach is proposed with a discussion of the academic and practical implications of the proposed framework.

Modeling the Sustainable Supply Chain Network Design for Food-Agricultural Industries considering Social and Environmental Impacts.

The food supply chain is one of the most sensitive supply chains as it is directly related to the health of humans and society. Therefore, this study aims to evaluate the components of the sustainable supply chain in the food industry. For this purpose, in the first step, several studies and research backgrounds have been conducted by researchers to identify the effective index on sustainability in the food and agricultural supply chain. After reviewing the literature, general indicators of sustainability that affect the agricultural supply chain are specified. Next, by using the fuzzy DEMATEL method, the effectiveness and efficiency of these criteria in three economic, environmental, and social dimensions have been assessed. The results show that in the economic dimension, the use of high technology in the production and the presentation of various citrus forms by using intermediate and conversion industries is the most effective. Criteria for purchasing and using livestock manure instead of using chemical fertilizers have a very high level of effectiveness. In the environmental dimension, reducing or eliminating waste production using recyclable and environmentally friendly materials has the most significant impact. In the social dimension, the positive mental image of customers has a more positive approach to manufacturers who use a sustainable supply chain and has the most impact. The main achievement of this study is that the most important factor in sustainability is the citrus quality control of the agricultural supply chain.

Evaluation of Ski Centers’ Performance Using Multiple-Criteria Decision-Making Methods

Abstract Introduction. This study aimed to determine the criteria for the choice of nine different leading ski centers that serve actively in the ski tourism sector of Turkey, to calculate the criteria weights, and to measure the performance of these centers. Material and methods. In this context, the data were defuzzified using the CFCS method, and the fuzzy DEMATEL method was used to determine the criteria affecting the choice of ski centers. Then, the TOPSIS method was applied to measure the performance of ski centers by using the criteria weights obtained with the fuzzy DEMATEL method. Results. As a result of the analysis, the weights of the main criteria were found as follows: facility amenities, price, accessibility, accommodation, alternative tourism, and visitors’ rating scores. Consequently, the top three ski resorts according to their scores are SC4, SC1, and SC9, respectively. The ski center which is coded SC9 is ranked at the bottom. Conclusions. The study examined the ski centers that actively operate in Turkey. This could be considered as a spatial decision-making problem. This study could be a road map for the performance evaluation in ski tourism. Moreover, the results will be beneficial for the ski centers to identify their deficiencies and carry out improvement works in attracting the increasing demand for skiing to their centers.