The increasing generation of solid waste poses significant environmental, resource, and public health challenges. Design for Recycling (DfR) is a key strategy to enhance end-of-life product recycling during the design stage. Evaluating product recyclability is central to DfR and essential for its successful implementation. However, existing methods often suffer from limited accuracy or high complexity, hindering their practical application in design. To address these issues, this study proposes a novel hybrid approach that integrates qualitative and quantitative analysis, improving evaluation accuracy while simplifying the process through a single recyclability indicator. The method combines the Analytic Hierarchy Process (AHP) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) with fuzzy comprehensive evaluation to estimate the probability of different recycling options. It further assesses recycling value based on economic viability, environmental impact, and disassembly difficulty, ultimately generating a comprehensive recyclability score to support design decisions. Case study results show that Design Alternative 2, with a recycling value of −3.26 Chinese yuan (CNY), is preferable to Design Alternative 1 (−16.58 CNY), demonstrating the practical feasibility of the proposed method. Furthermore, a controlled-variable comparative analysis highlights the method’s advantages in enhancing evaluation reliability and supporting design decisions.

Purpose This study aims to support waste reduction in hospital operating rooms by identifying performance indicators and waste categories that should be prioritized for intervention, based on their criticality and interrelationships. The goal is to enhance efficiency and effectiveness in healthcare operations by aligning with lean thinking principles. Design/methodology/approach A multi-criteria decision-making model is developed by integrating Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Class and Fuzzy decision-making trial and evaluation laboratory (DEMATEL) methods. Fuzzy TOPSIS Class is applied to evaluate and classify 32 operating room (OR) performance indicators and 21 waste types according to expert-assessed criticality levels. Subsequently, Fuzzy DEMATEL is used to analyse causal relationships among the most critical indicators and wastes. A real-world case study based on expert judgement is used to validate the approach. Findings The model enables the identification of high-priority OR performance indicators and waste types and maps their interdependencies through a visual cause-and-effect matrix. This matrix provides insights into the influence structure between performance indicators and waste categories, supporting informed and targeted decision-making in OR management. Originality/value This study contributes to healthcare operations management by combining Fuzzy TOPSIS Class and Fuzzy DEMATEL in a novel way to address waste reduction in ORs. The integrated model offers a systematic, expert-informed approach for prioritizing indicators and wastes, as well as understanding their interrelations, providing actionable guidance for the development of targeted action plans to enhance OR performance through lean thinking.

Background: Indonesia’s logistics industry boosts economic growth but harms the environment via plastic waste and carbon emissions – single-use plastics and fossil fuel transport cause persistent pollution. Green procurement (GP) is essential to reduce these impacts by prioritising sustainable suppliers and products despite cost and regulatory challenges. Objectives: The objective of this study is to explore the interconnections and significance of barriers affecting the implementation of GP in Indonesia’s logistics sector. Method: The study employs content validity analysis, decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modelling (ISM) approaches for data processing. These methods are used to identify, analyse and structure the relationships and hierarchical positioning of the barriers. Results: The study identifies 14 key barriers to the successful implementation of GP in Indonesia’s logistics industry. Key barriers include the lack of eco-friendly materials, insufficient supplier readiness, the absence of regulatory frameworks and inadequate government incentives. These foundational barriers trigger cascading effects that impact both operational and strategic procurement levels. Conclusion: The findings suggest overcoming barriers through targeted supplier training, increasing eco-friendly materials, adopting effective GP regulations and enhancing government incentives, which will reduce environmental impact, promote sustainable logistics practices and support broader environmental sustainability goals. Contribution: This study helps Indonesia’s logistics by providing practical solutions that enable the industry to adopt sustainable practices, reduce environmental impacts and support national sustainability goals.

Purpose To analyse the overall performance index score of an automotive component manufacturing organisation that has implemented Lean Six Sigma 4.0 (LSS4.0) using neutrosophic DEMATEL (Decision-Making Trial and Evaluation Laboratory). Design/methodology/approach Performance measurement is a complex process as it relies upon many quantifiable and non-quantifiable factors. In this study, the overall performance index score of (LSS4.0) is analysed using neutrosophic DEMATEL. Five main criteria and 62 sub-criteria are identified from existing studies using a structured literature review method, sub-criteria are grouped with appropriate main criteria based on expert panel decisions. Organisational performance was evaluated based on data collected using questionnaires and real-time data of few metrics. People, process, organisational, technical and operational criteria are the main criteria considered for evaluation of the organisation’s performance. Findings Results of the study indicated that technological and infrastructural development has a vital role in improving the overall performance of an organisation. Practical implications The study is being done with reference to automotive component manufacturing industry. Hence, the resulting inference has practical validity. On academic front, the study confirms an increase in organisation’s overall performance through the adoption of integrated LSS4.0 manufacturing method, and proposed performance management system model facilitates real-time reviewing of performance metrics. Originality/value Comprehensive performance analysis of LSS 4.0 using neutrosophic MCDM method is the original contribution of the authors.

Purpose This study explores how AI can support sustainable and efficient textile design, identify AI-based factors, analyse their interdependencies, and categorize them into cause-and-effect groups using a structured decision-making approach. Design/methodology/approach The study adopted a three-step process: (1) conducting a systematic literature review to identify AI applications in textile design, (2) applying the Fuzzy Delphi Method (FDM) to screen and cross-validate key factors based on expert opinions, and (3) using the Decision Making Trail and Evaluation Laboratory (DEMATEL) approach to analyse the cause-and-effect relationships between the screened factors. Findings The study found that AI-enabled generative Design for Material Efficiency and Predictive Colour and Trend Forecasting for Design Planning are primary causal factors influencing other AI-driven innovations, while AI-Powered Fit Prediction and Customization Algorithms and AI-Based Circular Design Recommendations are ranked as effect factors (i.e., they are more dependent on the impact of other factors). The results demonstrate the interdependent role of AI technologies in textile design and their influence on sustainability and efficiency in operations. Originality and implications The study provides new insight by mapping the influence of textile design AI technologies in a systematic way using an integrated FDM-DEMATEL framework, and the findings offer useful guidelines for designers, producers, and policymakers to set priorities for AI-based innovations and to make strategic investments into AI applications for increasing efficiency, circularity, and sustainability in the textile sector.

Potentially complex structures underlie the barriers to digital health transformation. This study aimed to identify the elements of barriers to digital health transformation and clarify the relationships among them using Interpretive Structural Modeling and Cross Impact Matrix-Multiplication Applied to Classification. We identified 11 barriers through a brainstorming session conducted by 3 nursing researchers in Japan. These elements were analyzed via mathematical processing, and a hierarchical structural diagram was constructed. The characteristics of each element were classified using the Cross Impact Matrix-Multiplication Applied to Classification analysis. The results demonstrated consistency with those of previous studies, thus indicating content validity. Furthermore, this study succeeded in systematically organizing the multilayered barriers and visualizing a comprehensive model that even individuals unfamiliar with the cultural context of health care could easily understand. These findings suggest that the organizational culture of nursing plays a fundamental role in the promotion of digital health transformation and emphasize the importance of collaboration among stakeholders at the clinical, developmental, and policy levels. Future strategies for digital health transformation should incorporate more flexible approaches using SWOT analysis and the Decision-Making Trial and Evaluation Laboratory technique.

Purpose This study aims to examine how the Committee of Sponsoring Organizations (COSO) framework can be adapted to a public-sector context (customs administration) to strengthen internal controls in bonded warehouse operations and bridge the gap between accounting theory and public-sector practice. The contributions translate COSO principles into measurable, causally ordered control criteria and ranked interventions. Design/methodology/approach This research integrated the decision-making trial and evaluation laboratory (DEMATEL) and analytic network process (ANP) approaches to construct a multi-criteria decision-making model for identifying the factors and strategies that influence the success of internal control in bonded warehouses. Findings The results that DEMATEL identifies control environment and operations as the system cause with the highest net influence, driving risk assessment, information and communication and monitoring. ANP ranks smuggling risk and cargo movement safety as the two most critical criteria, followed by audit/control mechanisms. The integrated ANP prioritizes an intelligent bonded management system, full-spectrum internet of things monitoring and rolling regulatory review. Practical implications The main practical implication of this study is the proposal of implementation strategies for customs to enhance internal controls in bonded warehouses and identify the critical success factors. Originality/value This study examines the integration of the five interconnect components of COSO (control environment, risk assessment, control activities, information and communication and monitoring) into public sector governance, thereby contributing to academic research in accounting and organizational change.

Purpose This paper aims to investigate the underlying factors contributing to the high attrition rates among women gig workers, with a focus on understanding the complexities of these factors and their interrelations. Design/methodology/approach The study uses a literature review and expert consultations to identify potential challenges leading to attrition. It then uses the Decision-Making Trial and Evaluation Laboratory method to analyse cause-and-effect relationships among these challenges. Findings The research identifies the lack of organizational support, inadequate psychological safety, poor person-job fit and work-family conflict as primary factors contributing to the high turnover rate among female gig workers. It also explores the interconnections between these challenges, providing a nuanced understanding of the attrition dynamics in the gig economy. The findings provide valuable insights for policymakers and stakeholders in the gig economy, highlighting the need for targeted strategies to address the identified challenges and reduce turnover rates among female gig workers. Originality/value This study contributes to the gig economy literature by using a structured decision-making approach to model and understand the complex factors influencing women’s attrition rates in gig work, thereby offering a novel perspective on workforce management in a rapidly evolving economic sector.

A fuzzy set is a mathematical construct that assigns a membership grade to each element within a universe of discourse, representing the degree to which the element belongs to the set. This approach extends classical binary logic by allowing continuous values between 0 and 1, making it a natural framework for handling uncertainties and vague concepts often expressed in natural language. Fuzzy sets are particularly powerful in modelling real-world scenarios where ambiguity and imprecision are inherent, such as in human decision-making, linguistic expressions, and complex systems. This paper introduces a novel application of fuzzy logic by proposing a fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) method. DEMATEL is a well-established technique used to analyse cause-and-effect relationships within complex systems. Still, its traditional form relies on crisp values, which may not adequately capture the inherent uncertainties in real-world data. Our proposed method integrates triangular fuzzy numbers into the DEMATEL framework, enabling the representation and analysis of data with imprecision and vagueness. Specifically, we apply the fuzzy DEMATEL approach to study the cause-and-effect relationships among factors affecting transgender individuals, a population often marginalized and underrepresented in research. By leveraging triangular fuzzy numbers, our method provides a more nuanced and realistic representation of the uncertainties and complexities in the data. This approach not only enhances the accuracy of the analysis but also offers a meaningful way to interpret vague or subjective information, ultimately contributing to more informed decision-making and policy development for transgender communities.

Integrating fuzzy DEMATEL and Constructal Law for biofouling dynamics in Marine Growth Prevention Systems.

Targeting degraded hotspots in riparian corridors for rehabilitation based on hydrological, ecological, natural and anthropogenic indicators.

Purpose Adopting the metaverse in construction has significant potential for digitalizing this sector, integrating physical and digital reality. However, several complex and interconnected barriers hinder its adoption. This paper aims to examine these interrelationships to promote the metaverse adoption in construction. Design/methodology/approach A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-guided literature review was conducted to identify existing barriers to metaverse adoption, followed by the employment of the fuzzy Decision-Making Trial and Evaluation Laboratory method to analyze the interrelationships among the identified barriers. Findings The analysis revealed a hierarchical structure of barriers, comprising five primary and 17 secondary barriers. Among them, the strongest causal main barriers were political barriers (MB1), particularly the “Lack of standardization policies”, and cultural barriers (MB5), with “Internal cultural conflict” emerging as the most critical sub-barriers. Practical implications The findings provide several practical guidelines for industry practitioners by pinpointing the most causal barriers hindering the adoption of metaverse technologies in construction. Originality/value Unlike previous studies that treated adoption barriers in isolation, this study systematically explores their interdependencies for the first time, providing advanced understandings and supporting strategic decision-making for the integration of the metaverse in construction.

In the medium-sized automotive sector, supplier selection is the most important factor in ensuring constant quality, cost management, and delivery performance. These sectors must deal with tight operational restrictions, interconnected criteria, and ambiguous information. As a result, choosing a supplier is a difficult choice. This article proposes an inventive strategy to address this issue over an integrated framework. 3.2. Fuzzy Analytic Hierarchy Process (FAHP) is used to calculate the criteria weights due to uncertainty, Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL) is used to map cause and effect relationships, and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Evaluation Based on Distance from Average Solution (EDAS) are used to assess supplier performance. Sensitivity analysis evaluates the stability of the results, whereas the Borda and Copeland Count methods combine the rankings. The FAHP score, the important factors are cost 0.128, quality 0.279, and delivery reliability 0.130. According to FDEMATEL, lower-weighted criteria indicate cause, and higher-weighted criteria indicate effect. TOPSIS and EDAS considered S1 and S2 to be the best performers, whereas S4 frequently scored lowest. These opinions were validated by Borda and Copeland aggregation. S1 and S2 maintained their top positions in every scenario, according to a sensitivity study with a weight variation of ±20%. Based on the results of this study, the integrated model offers a robust and clear base for the selection of suppliers.

Understanding the causal relationships between safety factors is essential for successful intervention in industries with intrinsically high-risk environments such as the construction industry. Therefore, the aim of this study is to employ the Interpretive Structural Modeling (ISM) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) techniques to analyze and map the interdependencies among various safety-related elements affecting construction safety. According to the results, resource allocation was shown to be the highest-level, most independent element in the analysis, highlighting its function as the primary facilitator of safety initiatives. This strategic commitment directly drives Management Commitment and Competence, which form the core organizational support structure. Mid-level elements that translate management intent into site-level practice include workers’ training, safety motivation, and communication structure. The frequency of safety observations, workers’ involvement in safety decisions, and subcontractor and procurement management—the immediate procedural controls—are then used to assess operational efficacy. Crucially, the most dependent factor was found to be Workers’ Compliance, indicating that frontline safety behavior is the result of efficient management at all higher levels. Therefore, in order to improve overall safety performance in construction, this research emphasizes the importance of improving resource provision and leadership commitment. The outputs of the current study provide an organized, evidence-based roadmap for selecting interventions.

The Maqasid al-Shariah (objectives of Islamic jurisprudence) emphasizes the preservation of five essential elements of human well-being, known as ad-dharuriyyat al-khams, including the protection of life (Hifz al-Nafs) and property (Hifz al-Mal). These principles align directly with the primary objective of occupational safety and health (OSH) management, which is to safeguard individuals and organizational assets from harm. Ensuring workplace safety is vital where risks are elevated. A strong safety culture requires a holistic strategy encompassing organizational, technological, human, and external factors. However, safety initiatives often face budgetary constraints, leading to underinvestment in OSH. This cross-sectional study investigates how organizations approach OSH investment and the interdependencies among influencing factors. Data were gathered through semi-quantitative surveys with Administrative Officers and Technical Heads of one of the public Higher Learning Institutions (HLIs), who are in charge and responsible for budget projection. These data are analyzed using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method. Findings revealed that management commitment is the most critical factor, significantly impacting communication, procedural compliance, and legal adherence. The study underscores the importance of leadership, adequate funding, and standardized safety practices. Effective management fulfills not only organizational objectives but also the ethical and spiritual imperatives of Islamic law by protecting human life and property.

In modern society, the pursuit of well-being (WB) has become a crucial issue. This study aims to analytically elucidate the structure of WB concepts inherent in Japanese classical literature, particularly Matsuo Bashō's haiku, by applying engineering and mathematical methods. Specifically, using representative haiku by Bashō as the object of analysis, we model the psychological and philosophical elements underlying them as system components. We then utilize the "PlantUML C4 Model," used in software architecture description, to comprehensively visualize the components of WB concepts. Furthermore, we apply the "DEMATEL method (Decision Making Trial and Evaluation Laboratory)," one of the multi-criteria decision analysis techniques, to quantitatively identify causal relationships and influence levels among elements. This enables us to propose a multi-layered WB conceptual model unique to Japanese culture, encompassing "harmony with nature," "paradoxical integration of emotions," and "sustainable fulfillment through introspection" as demonstrated in Bashō's haiku. This research suggests possibilities for interdisciplinary fusion between classical literary studies and systems engineering, and contributes to the spiritual richness of modern people by presenting a new perspective on WB based on Eastern thought.

Type of the article: Research ArticleModern defense environments demand sustainable, knowledge-driven training systems that adapt to technological, organizational, and strategic challenges. This study explores the sustainability of military distance learning in Lithuanian military education and its role in enhancing adaptability and resilience. It assesses how digital, knowledge-based systems support long-term effectiveness and flexibility. Sustainability refers to maintaining scalable, resilient education under changing conditions. Adaptability is the ability to adjust learning processes and technologies, while resilience ensures institutional stability and performance during disruptions. The study employs fuzzy logic integrated with the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to analyze interdependencies among eight critical factors of sustainable distance learning. A structured expert survey was conducted in 2024 with 17 Lithuanian military education specialists, all holding Ph.D. degrees and possessing extensive academic and practical experience in e-learning, instructional design, and technology management. The analysis revealed that technological infrastructure, instructional design, and scalability function as primary causal drivers shaping learner engagement and institutional support. Quantitative results show that technological infrastructure exerted the highest influence weight (0.187), followed by instructional design (0.162), while psychological support acted primarily as an effect factor. These findings confirm that sustainable distance learning enhances adaptability by ensuring uninterrupted access to training, flexible pacing, and integration of emerging digital tools. In conclusion, the study demonstrates that sustainable military distance learning serves as a strategic enabler of knowledge transfer, leadership development, and organizational effectiveness, thereby strengthening both the adaptability and institutional resilience of military education systems.AcknowledgmentWe acknowledge the General Jonas Žemaitis Military Academy of Lithuania for financial support in publishing this article.

Purpose Although the effectiveness of emergency hospital projects in responding to pandemics and public health crises is well documented, the complexity inherent in these projects—characterized by compressed schedules and stringent infection control protocols—remains insufficiently examined, often resulting in suboptimal project performance. This study aims to advance the understanding and management of such project complexity by systematically investigating its intrinsic attributes and interdependencies. Design/methodology/approach A two-stage hybrid approach combining qualitative and quantitative methods was used. Initially, an emergency hospital project complexity framework was developed through content analysis. Subsequently, the interrelationships and hierarchical structure among the identified complexity attributes were analyzed using the Decision-Making Trial and Evaluation Laboratory Analysis coupled with Interpretive Structural Modeling (DEMATEL-ISM) methodology. Findings The results reveal that the complexity framework comprises eight dimensions and 25 corresponding indicators. Both complexity dimensions and indicators are categorized into root, mediator, and outcome groups based on their hierarchical roles. Environmental complexity and goal complexity are identified as root-group dimensions. Within the indicators, constantly evolving pandemic conditions and the laborious nature of installation tasks are classified as root-group attributes. Practical implications Practitioners are provided with systematic tools to manage complexity during the construction phase, facilitating improved risk and uncertainty mitigation. Emphasis is placed on adopting precautionary measures, enhancement of improvisational capabilities, prioritization of time goals, integration of modular design and digital technologies, and reinforcement of supply chain resilience. These insights hold relevance for a broader range of public emergency response projects. Originality/value This study makes three theoretical contributions. First, by offering novel insights into the attributes of complexity and highlighting the significance of their interrelationships, this study contributes to a systematic comprehension of complexity within pandemic-driven construction projects. Second, as one of the earliest efforts to comprehensively articulate the complexity of emergency hospital projects, it introduces a framework structured around a “root–mediator–outcome” three-tier hierarchy that elucidates the interdependent nature of complexity attributes. Third, by exploring unique characteristics and complex causal relationships, this research expands the theoretical understanding of project complexity in emergency hospital construction and other public emergency response initiatives.

ABSTRACT The World Population Prospects (2022) report by the United Nations highlights a decline in global population growth, underscoring the critical role of healthcare systems in reducing maternal and infant mortality rates. While birth rates vary across high-income and low- and middle-income countries, ensuring safe childbirth remains a fundamental healthcare objective. Despite the known risks associated with unnecessary caesarean sections, their prevalence continues to rise in developing countries. This study examines the underlying factors contributing to this trend, using Iran as a case study. A systems approach is employed, incorporating Causal Loop Diagrams (CLDs) and the Decision Making Trial and Evaluation Laboratory (DEMATEL) to identify and prioritise key influencing factors. The findings suggest that societal and cultural dynamics play a more significant role in the increasing rates of unnecessary caesarean sections than technical medical considerations and individual preferences. Notably, the influence of word-of-mouth and support from reference groups underscores the importance of a community-focused approach in addressing this challenge.

Technology-adoption studies often take a singular perspective; none have yet analyzed, in a comparative style, the viewpoints of diverse users, such as the students and teachers. To bridge this gap, the authors, using a fuzzy decision-making trial and evaluation laboratory method, analyzed the constructs that drive the acceptance of digital learning technology according to the perspectives of both students and administrators. The key results indicated that different users' perspectives can generate an entirely different set of clustering assignments that may affect the decision of whether to adopt a new technology in the educational domain. These results can aid stakeholders in designing technology specifically tailored to users' preferences.