Search Results (123)

Distance learning has become essential to higher education, yet its application in military officer training presents unique academic, operational, and security challenges. For Lithuania’s future officers, remote education must foster not only knowledge acquisition but also decision-making, leadership, and operational readiness—competencies traditionally developed in immersive, in-person environments. This study addresses these challenges by integrating System Dynamics Modelling, Contemporary Risk Management Standards (ISO 31000:2022; Dynamic Risk Management Framework), and Learning Analytics to evaluate the interdependencies among twelve critical factors influencing the system resilience and effectiveness of distance military education. Data were collected from fifteen domain experts through structured pairwise influence assessments, applying the fuzzy DEMATEL method to map causal relationships between criteria. Results identified key causal drivers such as Feedback Loop Effectiveness, Scenario Simulation Capability, and Predictive Intervention Effectiveness, which most strongly influence downstream outcomes like learner engagement, risk identification, and instructional adaptability. These findings emphasize the strategic importance of upstream feedback, proactive risk planning, and advanced analytics in enhancing operational readiness. By bridging theoretical modelling, contemporary risk governance, and advanced learning analytics, this study offers a scalable framework for decision-making in complex, high-stakes education systems. The causal relationships revealed here provide a blueprint not only for optimizing military distance education but also for enhancing overall system resilience and adaptability in other critical domains. Full article

The complexities of megaprojects, particularly major transportation infrastructure projects (MTIs), require technological innovation that advances economic, social, and ecological objectives. Traditional engineering innovation emphasizes economic gains while neglecting sustainability. Therefore, implementing green innovation (GI) in MTIs is essential. This research examines key factors and correlations influencing MTI-GI to strengthen theoretical understanding and guide effective implementation. First, literature and interviews are used to identify MTI-GI influencing factors through the technology–organization–environment (TOE) framework. Second, an intuitive fuzzy number approach reduces subjectivity in expert scoring and, combined with the DEMATEL method, constructs a fuzzy DEMATEL model to quantify factor importance and identify critical drivers. Critical factors are then analyzed to formulate GI promotion strategies. Results reveal that MTI-GI influencing factors span technology, organization, and environment dimensions. Prioritizing green technological innovation and feedback mechanisms, optimizing organizational structures, and aligning with regional environmental characteristics are crucial for successful MTI-GI implementation. These findings support GI expansion in MTIs and offer targeted strategies for managing complex systems. Full article

To enhance the safety risk management and control capabilities for TBM (Tunnel Boring Machine) construction in hydraulic tunnels, this study conducts a correlation analysis and dynamic evolution study of safety risks. Data were collected through multiple channels, including a literature review, on-site records, and expert interviews. Grounded theory was employed for three-level coding to initially identify risk factors, and gray relational analysis was used for indicator optimization, ultimately establishing a safety risk system comprising 5 categories and 21 indicators. A multi-level hierarchical structure of risk correlation was established using fuzzy DEMATEL and ISM, which was then mapped into a Bayesian network (BN). The degree of correlation was quantified based on probabilistic information, leading to the construction of a risk correlation analysis model based on fuzzy DEMATEL–ISM–BN. Furthermore, considering the risk correlations, a safety risk evolution model for TBM construction in hydraulic tunnels was developed based on system dynamics. The validity of the model was verified using the AY project as a case study. The results indicate that the safety risk correlation structure for TBM construction in hydraulic tunnels consists of 7 levels, with the closest correlation found between “inadequate management systems” and “failure to implement safety training and technical disclosure”. As the number of interacting risk factors increases, the trend of risk level evolution also rises, with the interrelations within the management subsystem being the key targets for prevention and control. The most sensitive factors within each subsystem were further identified as adverse geological conditions, improper construction parameter settings, inappropriate equipment selection and configuration, weak safety awareness, and inadequate management systems. The control measures proposed based on these findings can provide a basis for project risk prevention and control. The main limitations of this study are that some probability parameters rely on expert experience, which could be optimized in the future by incorporating more actual monitoring data. Additionally, the applicability of the established model under extreme geological conditions requires further verification. Full article

Seismic retrofitting of reinforced concrete (RC) structures is essential for improving resilience and extending service life, particularly in regions with outdated building codes. However, selecting the optimal retrofitting strategy requires balancing multiple interdependent sustainability criteria—economic, environmental, and social—under expert-based uncertainty. This study presents a fuzzy hybrid multi-criteria decision-making (MCDM) approach that combines DEMATEL, DANP, and TOPSIS to represent causal interdependencies, derive interlinked priority weights, and rank retrofit alternatives. The assessment applies three complementary life cycle-based tools—cost-based, environmental, and social sustainability analyses following LCCA, LCA, and S-LCA frameworks, respectively—to evaluate three commonly used retrofitting strategies: RC jacketing, steel jacketing, and carbon fiber-reinforced polymer (CFRP) wrapping. The fuzzy-DANP methodology enables accurate modeling of feedback among sustainability dimensions and improves expert consensus through causal mapping. The findings identify CFRP as the top-ranked alternative, primarily attributed to its enhanced performance in both environmental and social aspects. The model’s robustness is confirmed via sensitivity analysis and cross-method validation. This mathematically grounded framework offers a reproducible and interpretable tool for decision-makers in civil infrastructure, enabling sustainability-oriented retrofitting under uncertainty. Full article

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

In today’s fast-moving digital economy, service start-ups are reshaping industries; however, they face intense uncertainty, limited resources, and fierce competition. This study introduces an Artificial Intelligence (AI)-powered process modeling framework designed to give these ventures a competitive edge by combining big data analytics, machine learning, and Business Process Model and Notation (BPMN). While past models often overlook the dynamic, human-centered nature of service businesses, this research fills that gap by integrating AI-Driven Ideation, AI-Augmented Content, and AI-Enabled Personalization to fuel innovation, agility, and customer-centricity. Expert insights, gathered through a two-stage fuzzy Delphi method and validated using DEMATEL, reveal how AI can transform start-up processes by offering real-time feedback, predictive risk management, and smart customization. This model does more than optimize operations; it empowers start-ups to thrive in volatile, data-rich environments, improving strategic decision-making and even health and safety governance. By blending cutting-edge AI tools with process innovation, this research contributes a fresh, scalable framework for digital-age entrepreneurship. It opens exciting new pathways for start-up founders, investors, and policymakers looking to harness AI’s full potential in transforming how new ventures operate, compete, and grow. Full article

The exponential growth of lithium-ion battery consumption has amplified the urgency of identifying sustainable and economically viable recycling solutions. This study proposes an integrated decision-making framework based on the T-Spherical Fuzzy Einstein Interaction Aggregator DEMATEL-CoCoSo approach to comprehensively evaluate and rank battery recycling technologies under uncertainty. Ten key evaluation criteria—encompassing environmental, economic, and technological dimensions—were identified through expert consultation and literature synthesis. The T-Spherical Fuzzy DEMATEL method was first applied to analyze the causal interdependencies among criteria and determine their relative weights, revealing that environmental drivers such as energy consumption, greenhouse gas emissions, and waste generation exert the most systemic influence. Subsequently, six recycling alternatives were assessed and ranked using the CoCoSo method enhanced by Einstein-based aggregation, which captured the complex interactions present in the experts’ evaluations and assessments. Results indicate that Direct Recycling is the most favorable option, followed by the Hydrometallurgical and Bioleaching methods, while Pyrometallurgical Recycling ranked lowest due to its high energy demands and environmental burden. The proposed hybrid model effectively handles linguistic uncertainty, expert variability, and interdependent evaluation structures, offering a robust decision-support tool for sustainable technology selection in the circular battery economy. The framework is adaptable to other domains requiring structured expert-based evaluations under fuzzy environments. Full article

In light of the persistent environmental degradation driven by fossil fuels, developing new energy sources is essential for achieving sustainability. The recent surge in electric vehicle adoption has underscored the significance of new energy batteries. However, the supply chains of new energy battery manufacturers face multiple sustainability risks, which impede sustainable practice adoption. To tackle these challenges, leanness philosophy is an effective tool, and Industry 5.0 enhances its efficacy significantly, further mitigating sustainability risks. This study integrates the supply chain, leanness philosophy, and Industry 5.0 by applying quality function deployment. A novel four-phase hybrid MCDM model integrating the fuzzy Delphi method, DEMATEL, AHP, and fuzzy VIKOR, identified five key sustainability risks five core leanness principles, and eight critical Industry 5.0 enablers. By examining a Chinese new energy battery manufacturer as a case study, the findings aim to assist managers and decision-makers in mitigating sustainability risks within their supply chains. Full article

Amid the increasing complexity of urban risks, urban parks not only serve ecological and recreational functions but are increasingly becoming a critical spatial foundation supporting public psychological resilience and social recovery. This study aims to systematically evaluate the daily adaptability of urban parks in the context of micro-risks. The research integrates the theories of “restorative environments,” environmental safety perception, urban resilience, and social ecology to construct a five-dimensional framework for perceived resilience, encompassing resilience, safety, sociability, controllability, and adaptability. Additionally, a dynamic feedback mechanism of perception–behavior–reperception is introduced. Methodologically, the study utilizes the Fuzzy Delphi Method (FDM) to identify 17 core indicators, constructs a causal structure and weighting system using DEMATEL-based ANP (DANP), and further employs the VIKOR model to simulate public preferences in a multi-criteria decision-making process. Taking three representative urban parks in Guangzhou as empirical case studies, the research identifies resilience and adaptability as key driving dimensions of the system. Factors such as environmental psychological resilience, functional diversity, and visual permeability show a significant path influence and priority intervention value. The empirical results further reveal significant spatial heterogeneity and group differences in the perceived resilience across ecological, neighborhood, and central park types, highlighting the importance of context-specific and user-adaptive strategies. The study finally proposes four optimization pathways, emphasizing the role of feedback mechanisms in enhancing urban park resilience and shaping “cognitive-friendly” spaces, providing a systematic modeling foundation and strategic reference for perception-driven urban public space optimization. Full article

Production involves processes such as raw material extraction, energy consumption, and waste management, which can lead to significant environmental consequences. Therefore, supplier selection based not only on technical performance but also on environmental sustainability criteria has become a fundamental component of eco-friendly manufacturing strategies. Moreover, in the selection of electric vehicle batteries, it is essential to consider customer demands alongside environmental factors. Accordingly, selected suppliers should fulfill company expectations while also reflecting the “voice” of the customer. The objective of this study is to propose an integrated approach for green supplier selection by taking into account various environmental performance requirements and criteria. The proposed approach evaluates battery suppliers with respect to both customer requirements and green criteria. To construct the relational structure, the DEMATEL method was employed to analyze the interrelationships among customer requirements (CRs). Subsequently, the Quality Function Deployment (QFD) model was used to establish a central relational matrix that captures the degree of correlation between each pair of supplier selection criteria and CRs. Finally, to evaluate and rank alternative suppliers, the Interval Type-2 Fuzzy VIKOR (IT2 F-VIKOR) method was applied. The hybrid approach proposed by us, integrating DEMATEL, QFD, and IT2 F-VIKOR, offers significant improvements over traditional methods. Unlike previous approaches that focus independently on customer preferences or supplier criteria, our model provides a unified evaluation by considering both dimensions simultaneously. Furthermore, the use of Interval Type-2 Fuzzy Logic enables the model to better manage uncertainty and ambiguity in expert judgments, yielding more reliable results compared to conventional fuzzy approaches. Additionally, the applicability of the model has been demonstrated through a real-world case study, confirming its practical relevance and robustness in the selection of green suppliers for electric vehicle battery procurement. 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

Background: Effective decision-making in supply chain contexts requires understanding how criteria interact to shape rational and transparent decision structures. This study investigates how behavioral aspects influence the structuring of decision-making logic and the interdependencies between key criteria in supply chain contexts. Methods: Using Fuzzy DEMATEL, the research models the interactions between five core criteria —classification, definition, specification, decision, and action feedback—based on inputs from experienced professionals in a global chemical company. The approach enables mapping of causal influences while accounting for subjectivity and uncertainty in expert judgments. Results: The analysis identified specification, definition, and action feedback as causal criteria, with classification and decision being primarily influenced by them. The modeling process supported clearer prioritization and revealed how expert-based interactions can reduce decision biases. Conclusions: This study demonstrates how structuring decision-making logic through causal modeling enhances clarity and reduces subjectivity. The findings contribute to the development of decision support tools applicable across strategic supply chain contexts, offering practical implications for professionals seeking to improve decision transparency and effectiveness. Full article

Serving as critical sustainable transportation infrastructure, inland waterways provide dual socioeconomic and ecological value by (1) facilitating high-efficiency freight logistics through cost-effective bulk cargo transport while stimulating regional economic growth, and (2) delivering essential ecosystem services including flood regulation, water resource preservation, and biodiversity conservation. This study establishes a stakeholder-centered risk assessment framework to enhance decision-making of waterway engineering projects and promote the sustainable development of Inland Waterway Transport. We propose a three-layer approach: (1) identifying key stakeholders in the decision-making stage of waterway engineering projects through multi-dimensional criteria; (2) listing and classifying decision-making risks from the perspectives of managers, users, and other stakeholders; (3) applying the Decision-Making Trial and Evaluation Laboratory (DEMATEL) to prioritize key risks and proposing a risk assessment model based on fuzzy reasoning theory to evaluate decision-making risks under uncertain conditions. This framework was applied to the Yangtze River Trunk Line Wuhan–Anqing Waterway Regulation Project. The results show that the risk ranking is managers, users, and other stakeholders, among which the risk of engineering freight demand is particularly prominent. This suggests that we need to pay attention to optimizing material transportation and operational organization, promote the development of large-scale ships, and realize the diversification of ship types and transportation organizations. This study combines fuzzy reasoning with stakeholder theory, providing a replicable tool for the Waterway Management Authority to address the complex sustainability challenges in global waterway development projects. 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

The maritime transport of liquefied gases poses significant safety and environmental hazards such as fire, explosion, toxic gas emissions, and air pollution. The main objective of this study was to systematically identify, analyze, and prioritise the potential risks associated with the operation of liquefied gas tankers using a hybrid methodological framework. This framework integrates Fuzzy Delphi, Fuzzy DEMATEL, and Fault Tree Analysis (FTA) techniques to provide a comprehensive risk assessment. Initially, 20 key risk factors were identified through expert consensus using the Fuzzy Delphi method. The causal relationships between these factors were then assessed using Fuzzy DEMATEL to understand their interdependencies. Based on these results, accident probabilities were further analyzed using FTA modelling. The results show that fires, explosions, and large gas leaks are the most serious threats. Equipment failures—often caused by corrosion and operational errors by crew members—are also significant contributors. In contrast, cyber-related risks were found to be of lower criticality. The study highlights the need for improved crew training, rigorous inspection mechanisms, and the implementation of robust preventive risk controls. It also suggests that the prioritisation of these risks may need to be reevaluated as autonomous ship technologies become more widespread. By mapping the interrelated structure of operational hazards, this research contributes to a more integrated and strategic approach to risk management in the LNG/LPG shipping industry. Full article