Search Results (144)

Against the backdrop of climate change and rapid urbanization, urban water resource management faces increasing complexity. Based on the OECD’s Twelve Principles of Water Governance, this paper aims to clarify the interaction relationships and relative priorities among dimensions and indicators, providing a structured basis for decision-making in urban water governance. The DANP method is applied to construct an analytical framework encompassing three major dimensions: effectiveness, efficiency, and trust and participation, together with twelve indicators. This study moves the OECD framework from a static structure toward a causal network. By identifying causal relationships and calculating local and global weights, the analysis reveals the driving structure and evaluation focus of governance elements. The results indicate that, from a causal perspective, efficiency (D₂) and effectiveness (D₁) are the primary driving dimensions of the governance system, while trust and participation (D₃) is primarily an outcome dimension. Weight analysis reveals that trust and participation have the highest weight, at 35.28%, reflecting the strong emphasis placed on transparency, public participation, and accountability in urban water governance evaluations. At the indicator level, Monitoring and Evaluation (C₁₂) ranks highest with a global weight of 9.44%. Overall, the study offers theoretical and practical insights for coordinating institutional efficiency and governance legitimacy in climate adaptation contexts. Full article

Against the backdrop of the accelerated development of the low-altitude economy and the structural transformation of modern logistics systems, systematically elucidating the key driving factors and their interaction structure is paramount for optimizing operational efficiency, promoting sustainable industry growth, and enhancing policy effectiveness. Integrating an extensive literature review with expert consultations, this study constructs a comprehensive indicator system of influencing factors for the coordinated development of the low-altitude economy and sustainable modern logistics. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is employed to characterize the causal relationships and influence directions among the factors. Empowered by these findings, an Analytic Network Process (ANP) model is established to calculate refined weights, forming a hybrid DEMATEL–ANP analytical framework. The results indicate that technological factors and institutional factors constitute the primary driving layer of the system. Specifically, System Integration and Operational Technology, Flight Control and Scheduling Capability, as well as the Standardisation of Airspace Management and the Completeness of the Regulatory and Standards Framework, exert pivotal influences on the systemic evolution. Social factors and infrastructure factors primarily function as the outcome and feedback layers, with their effectiveness contingent upon the maturity of the core driving elements. Further hybrid weight analysis demonstrates that the ranking of key influencing factors exhibits high stability and robustness. The coordinated development process presents a progressive transmission characteristic from “technology–institution” to “market–application” providing targeted practical guidance for promoting the sustainable and high-quality synergy between the low-altitude economy and modern logistics. Full article

Against the backdrop of intensified global talent competition, the return of overseas talents has become a key engine driving the enhancement of core competitiveness in developing countries. Accurately identifying its critical driving factors is essential for China to address the challenges of talent introduction. This study constructs a hybrid multiple-criteria decision-making framework to systematically explore the influence mechanism of overseas talent return: first, a 15-criterion decision structure covering economic, policy, educational, technological, and social aspects is established via systematic literature review and two-round Delphi expert surveys; second, the grey DEMATEL-ANP technique is adopted to quantify the inter-relationships and relative weights of the criteria and screen and rank the critical driving factors accurately. Empirical results show that the six core driving factors ranked by importance are talent policy support, economic development level, scientific and technological development strength, public service quality, educational resource supply, and attention to science and technology, with significant synergistic interaction effects among these factors. This research provides a scientific decision-making framework and empirical support for developing countries to formulate targeted talent introduction policies and optimize the talent development ecosystem. Full article

Construction safety has garnered extensive attention, among which the hoisting construction safety of prefabricated buildings constitutes a distinct concern warranting further focus, as it fundamentally differs from traditional cast-in situ construction. However, relevant studies remain relatively scarce, and there is a lack of research frameworks that enable the multi-dimensional comprehensive assessment of the significance of influencing factors. This study aims to comprehensively account for both the mechanisms of influence and the inherent importance of factors, thereby determining the significance of the influencing factors for hoisting construction safety in prefabricated buildings. Fifteen influencing factors were identified, and the fuzzy-DEMATEL and ANP methods were adopted, respectively to investigate the inter-factor mechanisms of influence and the systemic importance of these factors. This study finds that: at the level of the influence mechanism, factors such as workers’ behavior and construction process control play a core hub role in the system; management factors and external environments are the primary factors affecting workers’ behavior, and workers’ behavior tends to influence physical factors and construction site coordination; at the level of system importance, factor weights show a stepped distribution, among which management personnel competence is the most important factor; factors such as policies and regulations, as well as safety assurance plans, are also relatively significant. A comprehensive analysis of the two calculation results reveals that construction process control is the most critical factor, followed by workers’ behavior, the competence of management personnel, and construction operation coordination. Drawing on the functions of these factors, a series of recommendations was put forward, covering the aspects of safety resource allocation, safety training, and safety supervision. The present study facilitates a more comprehensive evaluation of the importance levels of each influencing factor and delivers practically accessible guidance for safety management in the hoisting operation of prefabricated buildings. Full article

This study proposes an indicator system for evaluating AI-assisted learning in higher education, combining evidence-based indicator development with expert-validated weighting. First, we review recent studies to extract candidate indicators and organize them into coherent dimensions. Next, a Delphi session with domain experts refines the second-order indicators and produces a measurable, non-redundant, implementation-ready index system. To capture interdependencies among indicators, we apply a hybrid Decision-Making Trial and Evaluation Laboratory–Analytic Network Process (DEMATEL–ANP, DANP) approach to derive global indicator weights. The framework is empirically illustrated through a course-level application to examine its decision usefulness, interpretability, and face validity based on expert evaluations and structured feedback from academic staff. The results indicate that pedagogical content quality, adaptivity (especially difficulty adjustment), formative feedback quality, and learner engagement act as key drivers in the evaluation network, while ethics-related indicators operate primarily as enabling constraints. The proposed framework provides a transparent and scalable tool for quality assurance in AI-assisted higher education, supporting instructional design, accreditation reporting, and continuous improvement. Full article

The widening digital divide within the Global Critical Mineral Resource Supply Chain (GCMRS) 4.0 creates significant barriers to cross-border governance and operational efficiency. To quantify and address this disparity, this study identifies 20 Critical Success Factors (CSFs) through expert interviews with 15 industry specialists in South Korea. A hybrid multi-criteria decision-making framework integrating Fuzzy DEMATEL, Analytic Network Process (ANP), and the Choquet integral is developed to map causal relationships and determine factor weights. The empirical results reveal a distinct ‘technology-first’ dependency. Specifically, Scalable Technical Solutions and Cloud Computing Access emerge as the primary driving forces with the highest global weights, while Digital Investment Subsidies serve as the central hub for resource allocation. Unlike generic governance models, this study provides a quantifiable decision-making basis for policymakers. It demonstrates that bridging the hard infrastructure gap is a prerequisite for the effectiveness of soft collaborative mechanisms in the critical mineral sector. Full article

The acceleration of financial innovation and pro-crypto regulations in the digital asset space have spurred interest in cryptocurrencies among funds, and institutional and retail investors. Like any risky assets, investment in digital assets offers opportunities in terms of returns and challenges in terms of risk. However, unlike traditional assets, digital assets like cryptocurrencies are highly volatile. Accordingly, applying conventional single-criterion financial metrics for portfolio construction may not be sufficient as the method falls short in capturing the complex, multidimensional risk-return dynamics of innovative financial assets like cryptocurrencies. To address this gap, this study introduces a novel, integrated hybrid Multi-Criteria Decision-Making (MCDM) framework that provides a structured, transparent, and robust approach to cryptocurrency fund selection. The framework seamlessly integrates three well-established operations research methodologies: the Decision-Making Trial and Evaluation Laboratory (DEMATEL), the Analytic Network Process (ANP), and the Vlse Kriterijumsk Optimizacija I Kompromisno Resenje (VIKOR) algorithm. DEMATEL is utilized to map and analyze the intricate causal interdependencies among a comprehensive set of evaluation criteria, categorizing them into foundational “cause” factors and resultant “effect” factors. This causal structure informs the ANP model, which computes precise criterion weights while accounting for complex feedback and dependency relationships. Subsequently, the VIKOR algorithm is invoked to use these weights to rank cryptocurrency fund alternatives, delivering a compromise between optimizing group utility and minimizing individual regret. To illustrate the application and efficacy of the proposed method, a diverse set of 20 cryptocurrency funds is analyzed. From the analysis, it is shown that foundational criteria, such as “Fee (%)” and “Annualized Standard Deviation,” are the primary causal drivers of financial performance outcomes of funds. This proposed framework supports strategic capital allocation in a rapidly evolving domains of digital finance. Full article

Farmers’ markets in Latin America continue to face structural challenges such as informality limited value addition, and weak institutional support. This article applies a hybrid multi-criteria model that integrates DEMATEL, ANP, and SBWM to prioritize agri-food transformation strategies in the department of Meta, Colombia. The methodology combined stakeholder mapping, Delphi-based validation of criteria, and the evaluation of strategic robustness under three prospective scenarios. The results show that the creation of working groups with public and private institutions (E.3) consistently emerged as the most robust strategy (weight = 0.0669 in SBWM), followed by infrastructure development (E.2. 0.0649) and participatory workshops on food sustainability (E.8. 0.0602). Sensitivity analysis confirmed the stability of the prioritization structure, with strategy E.3 remaining in the first position across all scenarios and only moderate variations in the positions of E.2 and E.8. The study contributes methodologically by demonstrating the integration of DEMATEL–ANP with SBWM to address interdependencies and uncertainty in participatory decision contexts. It also provides practical guidance for local governments and cooperatives to strengthen farmers’ markets through institutional coordination, capacity building, and infrastructure investment, thereby supporting progress toward several Sustainable Development Goals (SDGs). Full article

E-learning systems that support personalized learning require sophisticated decision-making methods to adapt content to students optimally. This paper deals with applying multi-criteria decision-making methods in assigning learning objects in an e-learning system to students based on relevant customization criteria. The novelty of this study lies in the application of ANP and DEMATEL to improve content adaptation for students. Structuring the decision-making problem according to the DEMATEL and using ANP for prioritization has made the entire selection of learning objects better with respect to cognitive and learning styles and Bloom’s taxonomy levels. The method consists of various forms. In the first, DEMATEL has identified dependencies between criteria and clusters, mentioning their influence values on a 0–4 scale. A linear transformation model quantified the compatibility level of a student profile to a learning material. The transformed DEMATEL results were incorporated in all the interdependencies among criteria. The unweighted supermatrix was normalized by cluster weights assigned by experts before the iterative computation led to the converging weighted supermatrix. The outcome was that the individual students made these final priority rankings for learning materials. A pilot experiment was carried out to validate the system, and the results revealed that in the experimental group, the personalized learning environment showed the maximum statistical improvement over the control group. The research was conducted in Croatia, and the participants were students (N = 77) from two public universities and one polytechnic. Ultimately, the newly developed combined ANP-DEMATEL approach was effective in an instantaneous result-optimized dynamic learning path generation, ensuring knowledge acquisition. This research further contributes to developing intelligent educational systems by demonstrating how ANP and DEMATEL can be used synergistically to improve e-learning personalization. Future work could include optimizing weight assignment strategies or using new learning contexts to further adaptivity. Full article

Taipei’s metropolitan region faces frequent typhoon impacts that test its urban resilience. This study examines the relationship between Transit-Oriented Development (TOD) urban spatial forms and Taipei’s resilience against typhoons, considering both physical urban morphology and planning factors. We apply a Dynamic Analytic Network Process (DANP), an integrated DEMATEL-ANP multi-criteria approach to evaluate and prioritize key resilience-related spatial and planning factors in TOD areas. Rather than using GIS flood modeling, we emphasize empirical indicators derived from local data, including urban density, transit accessibility, historical typhoon flood impacts, infrastructure vulnerability, and demographic exposure. An extensive literature review covers TOD principles, urban resilience theory, and DANP methodology, with a particular emphasis on the Taiwanese context and case studies. Empirical results reveal that specific TOD characteristics indeed enhance typhoon resilience. High-density, mixed-use development around transit can reduce overall exposure to hazards by curbing sprawl into floodplains and enabling efficient evacuations. Using DANP, we find that infrastructure robustness and emergency planning capacity emerge as the most influential factors for resilience in Taipei’s TOD neighborhoods, followed by land use and management and transit accessibility. Weighted rankings of Taipei’s districts suggest that centrally located TOD-intensive districts score higher in resilience metrics, while peripheral districts with flood-prone areas tend to lag. The Discussion explores these findings, considering planning policies—noting that TOD can bolster resilience if coupled with adaptive infrastructure and inclusive planning—and compares them with examples like Singapore’s integrated land use and transit strategy, which dramatically reduced flood risk. The study concludes with policy implications for integrating TOD and climate resilience in urban planning, and contributions of the DANP approach for complex urban resilience evaluations. Full article

Vertical greening (VG) delivers measurable urban ecosystem benefits, yet maintenance is constrained by at-height safety risks, heterogeneous facade geometries, and low labor efficiency. Although unmanned aerial vehicles show promise, most studies optimize isolated modules rather than providing a user-oriented, system-level pathway. This paper proposes a closed-loop, multi-method framework integrating the Decision-Making Trial and Evaluation Laboratory-Analytic Network Process, the Functional Analysis System Technique, and the Theory of Inventive Problem Solving. DEMATEL-ANP models causal interdependencies among requirements and derives prioritized weights,; FAST decomposes functions and localizes conflicts, and TRIZ converts those conflicts into principle-guided structural concepts—establishing a traceable requirements → functions → conflicts → structure pipeline. We illustrate the approach at the prototype level with Rhino–KeyShot visualizations under near-facade constraints, showing how prioritized requirements propagate into candidate UAV architectures. The framework structures the identification and resolution of tightly coupled technical conflicts, supports adaptability in facade-proximal scenarios, and provides a transparent mapping from user needs to structure-level concepts. Claims are restricted to methodological feasibility; comprehensive quantitative field validation remains for future work. The framework offers a reproducible methodological reference for the systematic design and decision-making of intelligent UAV maintenance systems for VG. Full article

Historic buildings make up a significant proportion of the existing building stock. Most are characterised by poor technical condition and high energy demand. In Poland, many historic buildings are still in use today, but it is also common to find these buildings subjected to adaptive reuse. Adaptive reuse, often combined with modernisation, is problematic, especially in terms of finding a use that is optimal in the light of use-specific decision criteria. In previous studies, the authors used and developed the potential for the modelling and structural analysis of decision-making problems for the selection of new uses for historic buildings. In this paper, we present a test of this methodology on a Polish historic building. To further the application of our approach in sustainability-focused contexts, we performed the analysis using criteria focused on environmental and energy performance, in addition to other established criteria. In our study, the highest ranking use was a kindergarten, which scored 18% higher than the second-ranked alternative and over 90% higher than the lowest-ranked alternative. Full article

Aiming at the problems that the random probability characteristics of large-scale source and load resources lead to the ineffectiveness of deterministic planning methods, the standard grid structure is difficult to adapt to the demands of diversified scenarios. This paper proposes a grid-based scenario delineation method for distribution networks based on fuzzy comprehensive evaluation and SNN-DPC (density peak clustering based on shared-nearest-neighbors). First, analyze the response characteristics of various types of flexible resources, and establish a multi-dimensional comprehensive assessment index system that integrates operational characteristics and structural features. Second, the comprehensive weights of each index in the index layer are calculated based on the DEMATEL-ANP method and the CRITIC method, and the assessment value of the intermediate layer is calculated by the fuzzy comprehensive evaluation method. Finally, the assessment value of the intermediate layer is clustered based on the improved SNN-DPC algorithm, so as to classify the distribution grid scenarios. The results indicate that the proposed method can effectively and accurately classify distribution network scenarios. Full article

The current research on smart construction sites is mainly from the perspective of the whole life cycle of the project, and often focuses on the identification of factors at the macro level. It lacks in-depth quantitative analysis of the complex interdependence between influencing factors, and it is difficult to accurately identify key driving factors and weight distribution. This paper takes engineering project management as the perspective, constructs a smart site construction model. The advantages of DEMATEL method and ANP method are innovatively combined to construct the DEMATEL-ANP evaluation model, which overcomes the limitations of single method in weight determination and relationship analysis, and provides a more detailed and scientific analysis framework for the evaluation of smart site construction, and, taking the Urumqi region as an example, its smart construction is evaluated and analyzed. The results of the study show that the correlation between the indicators affecting the construction of smart construction sites is strong, in which the comprehensive influence of personnel safety management, construction quality management, and construction safety management play a greater role, with the comprehensive weights of 0.0917, 0.0817 and 0.0767, respectively; the total score of smart construction site construction of Urumqi region is 63.959, which is in the primary construction stage. Among them, the construction and application of meteorological monitoring are the best, scoring 70.26; the construction and application of most indicators, such as personnel safety management, cost comparison decision-making, dust monitoring, and noise monitoring, are the second best; the construction progress control and wastewater monitoring construction are poor, scoring 55.21 and 57.741. The results of this study can provide direct value to key audiences such as construction enterprise managers, government regulators, and smart site solution providers. This paper considers regions with unique climate types to provide a reference for the construction of intelligent construction sites in the same type of regions. 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