Search Results (52)

Facing the global competitive market and ever-changing customer demands, manufacturers must navigate intense competition and uncertain demand while striving to enhance customer satisfaction. As a result, the demand for customized products has become a crucial design consideration. To respond accurately and swiftly in a competitive market, manufacturers must focus on customer needs, analyze market trends and competitor information, and leverage data analysis as a reference for new product development and design. This study presents a new product development model by integrating quality function deployment (QFD), decision-making trial and evaluation laboratory (DEMATEL), analytic network process (ANP), and fuzzy set theory. It first uses a 2-tuple fuzzy DEMATEL to identify significant interrelationships among factors. A revised house of quality (HOQ) is then constructed to map relationships among customer requirements (CRs), engineering requirements (ERs), and the influences of CRs on ERs. To address uncertainty in human judgment, fuzzy set theory is incorporated into the ANP. The integrated model can determine the relative importance of the ERs. The proposed model is applied to touch panel development, and the results are recommended to the R&D team for new product development. Full article

A reasonable water price for interbasin water transfer projects (IWTPs) is vital for solving the problem of unequal water use among different water users caused by different water source supply prices, promoting external water transfer consumption, and ensuring the stable and equitable project operation. However, the formulation of the water price is influenced by many factors, and it is necessary to identify the key factors and their interactions in the water prices formulation for IWTPs. In this study, we identified 15 factors that affect it. This paper used the fuzzy decision-making trial and evaluation laboratory (DEMATEL) to analyze the causal relationships and importance levels among the influencing factors. A four-level hierarchical structural model was established using an interpretive structural model (ISM), which intuitively displayed the hierarchical structure and pathways of each factor. The role of each influencing factor was determined by using MICMAC. Finally, the grey relational analysis method was used to identify the top five key factors: the socioeconomic development level, diversification of water resources, water demand of water users, cost of the project’s water supply, and national policies and regulations. Strategies to improve the formulation of water prices have also been proposed. The results show that the top five factors influencing the water price for IWTPs are the socio-economic development level, diversification of water resources, water demand of water users, cost of the project’s water supply, and national policies and regulations. The water price should be formulated based on the water resource cost, supply–demand relationships of water resources, and policy objectives to ensure scientific and reasonable cost allocation and differentiated pricing. For water-transfer projects with strong public welfare, the government may lower water prices through financial subsidies to alleviate the burden on water users. Full article

Recently, the development of the Metaverse has emerged as a pivotal concern within both industrial and academic realms. The future development of the Metaverse industry is shrouded in uncertainty, complexity, and a dearth of technical and economic information. To address these challenges, this paper integrates the fuzzy Delphi method and fuzzy DEMATEL based on linguistic variables to explore the critical factors of the Metaverse industry. In accordance with the proposed methodology, a case study is presented to explore the critical factors of the Metaverse industry in Taiwan. The results of the empirical analysis demonstrated that the order of importance for the three principal dimensions is as follows: “infrastructure”, “consumer behavior”, and “user experience”. From the perspective of causality, “infrastructure” can be considered a driving dimension, whereas “user experience” can be regarded as a passive dimension. Regarding the critical factors, it can be observed that “virtual and real integration”, “equipment lightweight”, and “network communication” act as driving factors, exhibiting a high degree of correlation with the advancement of the Metaverse industry. Therefore, the proposed method not only possesses a robust theoretical foundation but also offers tangible practical value in the real world. Full article

As human-driven vehicles (HDVs) and autonomous vehicles (AVs) coexist on the road, the asymmetry between their driving behaviors, decision-making processes, and responses to traffic scenarios introduces new safety challenges, especially in complex merging areas where frequent interactions occur. The existing traffic safety analysis of mixed traffic is mainly to analyze each safety index separately, lacking comprehensive evaluation. To investigate the safety risk more broadly, this study proposes a comprehensive safety evaluation framework for mixed traffic flows in merging areas from the perspective of traffic conflicts, emphasizing the asymmetry between HDVs and AVs. Firstly, an indicator of Emergency Lane Change Risk Frequency is introduced, considering the interaction characteristics of the merging area. A safety evaluation index system is established from lateral, longitudinal, temporal, and spatial dimensions. Then, indicator weights are determined using a modified game theory approach that combines the entropy weight method with the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, ensuring a balanced integration of objective data and expert judgment. Subsequently, a cloud model enhanced with the fuzzy mean value method is then developed to evaluate comprehensive safety. Finally, a simulation experiment is designed to simulate traffic operation of different traffic scenarios under various traffic flow rates, AV penetration rates, and ramp flow ratios, and the traffic safety of each scenario is estimated. Moreover, the evaluation results are compared against those derived from the fuzzy comprehensive evaluation (FCE) method to verify the reliability of the comprehensive evaluation model. The findings indicate that safety levels deteriorate with increasing total flow rates and ramp flow ratios. Notably, as AV penetration rises from 20% to 100%, safety conditions improve significantly, especially under high-flow scenarios. However, at AV penetration rates below 20%, an increase of the AV penetration rate may worsen safety. Overall, the proposed integrated approach provides a more robust and accurate assessment of safety risks than single-factor evaluations, providing deeper insights into the asymmetries in traffic interactions and offering valuable insights for traffic management and AV deployment strategies. Full article

Unrealistic cash flow forecasts negatively affect project stakeholders and are a common issue for construction practitioners. This study proposes a new method for predicting the probabilistic cash flow of a project that can automate the calculation process while considering the impact of risks and their inter-related structure. This research integrates a Bayesian Belief Network (BBN) and 5D-BIM to provide a new probabilistic cash flow analysis approach. Here, 5D-BIM is used to facilitate cash flow calculations and automate the process. The BBN has also been implemented to assess the impact of risk factors on project cash flow, considering their complex inter-related structure. In addition, a hybrid approach combining fuzzy set theory, decision-making trial and evaluation laboratory (DEMATEL), and interpretive structural modeling (ISM) is used to form the BBN. The proposed method provides a robust tool for calculating the probabilistic cash flow of the project. The results showed that the project’s cash flow in the last month was IRR 14.4 billion without considering the impact of risks. The probabilistic cash flow of the project indicates that due to the impact of the risks, the project cash flow will be in the range of IRR −142.2 billion and IRR 1.11 billion at the end of the project. This shows the possibility of experiencing between 11 and 130% deviation in the project cash flow due to existing risks. In conclusion, project cash flow is unreliable without considering the impact of risks. This framework supports better financial decisions and allows for the evaluation of cash flow risk management scenarios. Full article

The construction industry is a major contributor to global carbon emissions, making the decarbonization of its supply chain a critical goal for sustainable development. This study aims to identify key drivers of decarbonization within the construction supply chain and analyze their interrelationships using causal and structural modeling techniques. A bibliometric analysis is conducted to highlight theoretical gaps in the field, followed by the application of the Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL) method to identify key decarbonization factors, and the Adversarial Interpretive Structural Modeling (AISM) method to construct a causal model that reveals their interactions. The results identify 17 key factors, categorized into five levels, with low-carbon policy guidance and consumer preferences emerging as the most influential. Based on these findings, a three-tier strategy is proposed to guide decarbonization efforts within the construction supply chain. This research provides theoretical insights into decarbonization and offers actionable recommendations for future industry practices and policy development. Full article

Proper management of vehicle structural factors related to public transportation safety is vital to formulate maintenance strategies and to enhance transportation safety. Therefore, this work aims to comprehensively identify potential structural factors, assess their impacts as regards causing public transportation vehicle malfunctions, and understand their cause–effect interrelationships. Maintenance management can be improved based on the analysis outcomes. Multi-Criteria Decision-Making (MCDM) techniques are widely applied to decision-making problems. However, due to the advanced and complex structures of modern vehicles, conventional single-used MCDM techniques encounter limitations in their ability to thoroughly account for all potential failure factors and to systematically manage the causal interrelationships, which makes the analysis results less practically applicable. To overcome these challenges, this article proposes an innovative MCDM framework. Specifically, Failure Tree Analysis (FTA) and the Interval-Valued Pythagorean Fuzzy Analytic Hierarchy Process (IVPF-AHP) are integrated to construct the logical relationships between the failure structural factors from real-world maintenance records. The factors are ranked and selected based on their severity influence and occurrence likelihood influence. Subsequently, the Interval-Valued Pythagorean Fuzzy Decision-Making Trial and Evaluation Laboratory (IVPF-DEMATEL) takes causal diagrams to identify interdependencies between the factors based on the mitigated ambiguity of human assessments. A case study in the public transportation bus domain is conducted to demonstrate the effectiveness of the proposed MCDM framework. The results offer insightful maintenance suggestions for public transportation operators and engineers to save human labor and material resources. Full article

In recent years, Failure Mode and Effects Analysis (FMEA) has become an essential preventive tool widely applied across various fields. As a structured system analysis method, FMEA aids in identifying potential failure modes in product or process design, allowing for preventive measures to be taken in advance. However, traditional FMEA has certain limitations, as it does not comprehensively consider all potential failure factors. This study proposes an improved FMEA method that addresses these shortcomings by integrating it with a Multiple-Criteria Decision Making (MCDM) model, thereby enhancing the comprehensiveness of the assessment framework. Notably, this research introduces an economic risk factor—Expected Cost (EC)—to make the analysis results more aligned with real-world conditions. Additionally, to manage the uncertainty in expert opinions, this study applies Interval Type-2 Trapezoidal Fuzzy Numbers (IT2TFNs) and combines them with the Best-Worst Method (BWM) to calculate the weights of risk factors. Furthermore, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is employed to explore the interrelationships between failure modes. Finally, the Multi-Attribute Ideal-Real Comparative Analysis (MAIRCA) method is used to rank risk factors, determining the priorities for improvement. This paper uses an air purifier as a case study to validate the effectiveness of the improved FMEA method, successfully addressing the shortcomings of traditional FMEA regarding uncertainty in expert opinions and the calculation of Risk Priority Numbers (RPNs). It provides a more practical and accurate risk assessment framework. Full article

Ports are the main arteries of global trade, handling goods circulation and serving as hubs for information, capital, and technology. Integrating digital technology has become the key for green port development to achieve resource efficiency and ecological balance. The current literature overlooks how digital technology can facilitate greener port operations. This study integrates sustainable supply chain management and system dynamics theories based on an in-depth analysis of existing research results and expert interviews. The analysis focuses on three key dimensions: integrating digital technologies with infrastructure, optimizing digital management and operations, and improving environmental and safety management in a digitally driven setting. Using the fuzzy Decision Making Trial and Evaluation Laboratory (Fuzzy Dematel) methodology, we collaborated with domain experts in port logistics to identify and confirm 12 pivotal factors that support the green digital transformation of ports. The research shows that the most critical success factors for using digital technology to drive ports’ green transformation are green supply chain information platforms, intelligent vessel scheduling, traffic optimization, and digital carbon emission monitoring. This study significantly contributes to the literature on green port transformation, offering indispensable practical insights for port operators, government entities, and shipping firms in identifying and deploying these key success factors. The findings will help maritime supply chain stakeholders develop actionable digital strategies, improving port efficiency and ecological resilience. Full article

Interdependent criteria play a crucial role in complex decision-making across various domains. Traditional methods often struggle to evaluate and prioritize criteria with intricate dependencies. This paper introduces a generalized method integrating the analytic network process (ANP), the decision-making trial and evaluation laboratory (DEMATEL), and the consistent fuzzy analytic hierarchy process (CFAHP) in a fuzzy environment. The Drazin inverse technique is applied to derive a fuzzy total priority matrix, and we normalize the row sum to achieve the steady-state fuzzy priorities. A numerical example in the information systems (IS) industry demonstrates the approach’s real-world applications. The proposed method derives narrower fuzzy spreads compared to the past fuzzy analytic network process (FANP) approaches, minimizing objective uncertainty. Total priority interdependent maps provide insights into complex technical and usability criteria relationships. Comparative analysis highlights innovations, including non-iterative convergence of the total priority matrix and the ability to understand interdependencies between criteria. The integration of the FANP’s network structure with the fuzzy DEMATEL’s influence analysis transcends the capabilities of either method in isolation, marking a significant methodological advancement. By addressing challenges such as parameter selection and mathematical complexity, this research offers new perspectives for future research and application in multi-attribute decision-making (MADM). Full article

As environmental awareness grows, society emphasizes green business. Thus, semiconductor companies encompass energy-saving processes and innovative product development. This study employs the fuzzy decision-making trial and evaluation laboratory (DEMATEL) analysis method to assess the impact of four key dimensions, externalities, market orientation, green technology, and corporate social responsibility, on semiconductor companies’ green production decisions. This study uses the DEMATEL-based analytic network process (DANP) approach to rank the criteria order in green production decision-making. The results from the DEMATEL causality diagram highlight externalities as the most critical dimension influencing other dimensions of green production decisions. This study suggests that regulatory pollution punishment and subsidies emerge as the primary drivers for green production decisions. Companies adopt environmentally friendly production practices to prevent regulatory pollution penalties or reduce carbon trading costs. Additionally, the DANP results reveal that corporate image criteria in the corporate social responsibility dimension hold the utmost priority in semiconductor firms’ green production decision-making. This implies that considerations for improving a company’s image should take precedence as semiconductor companies seek shareholder support and governmental subsidies to ensure sustainable operations. Externalities arise as the secondary priority dimension in green production decision-making, aligning with the impact of externalities identified in DEMATEL findings. Full article

With the growth of the worldwide population and depletion of natural resources, the sustainable development of food systems cannot be ignored. The demand for agri-food waste valorization practices like high-value compounds production has received widespread attention; however, numerous challenges still exist. The present study aims to identify those challenges of agri-food waste valorization and propose effective solutions based on smart technologies. Based on a systematic review of the literature, the study combs existing challenges of agri-food waste valorization and constructs a six-dimension conceptual model of agri-food waste valorization challenges. Moreover, the study integrates a Fermatean fuzzy set (FFS) with multi-criteria decision-making (MCDM) methods including stepwise weight assessment ratio analysis (SWARA), decision-making trial and evaluation laboratory-interpretative structural modeling method (DEMATEL-ISM), and quality function deployment (QFD) to evaluate the weights of each dimension, find causal interrelationships among the challenges and fundamental ones, and rank the potential smart solutions. Finally, the results indicate that the “Government” dimension is the severest challenge and point out five primary challenges in agri-food waste valorization. The most potential smart solution is the “Facilitating connectivity and information sharing between supply chain members (S8)”, which may help government and related practitioners manage agri-food waste efficiently and also facilitate circular economy. Full article

The “green transformation of the express” delivery industry in this study primarily refers to the adoption of green energy and environmentally friendly technologies in express delivery packaging, transportation, and recycling systems. This transformation can significantly enhance energy efficiency and reduce emissions in the express system, promoting the sustainable development of the entire industry. However, the progress of green transformation in China’s express delivery industry has been impeded by various barriers. To address this, we propose a barrier analysis framework based on the Fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) methodology to explore key obstacles to green transformation in the express industry. Our research aims to answer three main questions: (1) What are the key barriers to green transformation in China’s express delivery industry? (2) How do these barriers interact and influence each other? (3) What strategic measures can be implemented to overcome these barriers? We first compile a list of barriers, innovatively proposing two new ones: “inadequate green standards in the express industry” and “suboptimal green packaging technology”. Considering the ambiguity in expert input and the complex interactions among barriers, we employ fuzzy DEMATEL within an Interval Type 2 Fuzzy Sets (IT2FSs) environment to investigate the significance and causality of these barriers. This approach distinguishes our study from previous research by providing a more nuanced understanding of barrier interactions in the specific context of China’s express delivery industry. Based on our analysis, we identify eight critical barriers and propose corresponding strategic measures. Full article

As an important support for power systems with high penetration of sustainable energy, the energy storage system (ESS) has changed the traditional model of simultaneous implementation of electricity production and consumption. Its installed capacity under the source-grid-load scenario is rising year by year, contributing to sustainable development, but it faces the problems of insufficient utilization and benefits. This study analyzes the functional combination of ESS under source-grid-load scenarios. A comprehensive benefit evaluation method of energy storage projects (ESPs), based on a fuzzy decision-making trial and evaluation laboratory (DEMATEL) and super-efficiency data envelopment analysis (DEA), is proposed. Firstly, the functional requirements of energy storage in source-grid-load scenarios are explored, and the characteristics of various functions are analyzed to form eight functional combination schemes. Secondly, index modeling is carried out from three aspects—the whole life cycle cost, functional combination benefits, and social and environmental benefits—and a comprehensive benefit evaluation index system of ESP is proposed. Then, the intuitionistic trapezoidal fuzzy number (ITFN) is combined with DEMATEL to form an effective analysis method for the input–output relationship of the indices, and the comprehensive evaluation is realized based on the SE-DEA model. Compared with other methods, this model can ensure the objectivity and stability of the evaluation results in ESP evaluation. Finally, the effectiveness of the proposed evaluation method and the rationality of the functional combination are verified under source-grid-load scenarios. The calculation results show that in the application scenario of source-grid-load, after adopting the functional combination scheme formulated in this article, the comprehensive investment benefits of ESPs have been improved. Moreover, the source side effect is at its best, with an efficiency value of 2.209. Full article

To enhance the safety management of steel-truss-bridge construction, an evaluation method based on the improved DEMATEL–ISM was proposed to analyze the risk factors involved in such construction. Decision Making Trial and Evaluation Laboratory (DEMATEL) is a method for systematic factor analysis that utilizes graph-theory and -matrix tools, allowing for the assessment of the existence and strength of relationships between elements by analyzing the logical and direct impact relationships among various elements in a system. The distinctive feature of Interpretative Structural Modeling (ISM) is the decomposing of complex systems into several subsystems (elements) and constructing the system into a multi-level hierarchical structural model through algebraic operations. Specifically, triangular fuzzy numbers are introduced initially to improve the direct influence matrix in the DEMATEL method, thereby reducing the subjectivity of expert evaluations. The degree of influence, influenced degree, centrality degree, and causality degree of each influencing factor are determined and ranked based on the above analysis. In response to the characteristics of top-push construction, 20 key factors were selected from four aspects: “human, material, environment, and management”. The top five identified influencing factors are displacement during pushing (X10), safety-management qualification (X18), local buckling (X14), overturning of steel beams (X13), and collision with bridge piers during guide beam installation (X7). Subsequently, corresponding solutions were proposed for different influencing factors. The results of the study offer targeted measures to enhance the safety management of steel truss bridge construction and provide a reference for accident prevention. Full article