Search Results (557)

The construction industry faces persistent challenges, including low productivity, high waste generation, and resistance to technological innovation. Off-site modular construction, supported by Building Information Modeling (BIM), emerges as a promising strategy to address these issues and advance sustainability goals. This study aims to evaluate the practical impacts of industrialized off-site construction in the Brazilian context, focusing on cost, execution time, structural weight, and architectural–logistical constraints. The novelty lies in applying the methodology to a high standard, mixed-use multifamily building, an atypical scenario for modular construction in Brazil, and employing a MultiCriteria Decision Analysis (MCDA) to integrate results. A detailed case study is developed comparing conventional and off-site construction approaches using BIM-assisted analyses for weight reduction, cost estimates, and schedule optimization. The results show an 89% reduction in structural weight, a 6% decrease in overall costs, and a 40% reduction in project duration when adopting fully off-site solutions. The integration of results was performed through the Weighted Scoring Method (WSM), a form of MCDA chosen for its transparency and adaptability to case studies. While this study defined weights and scores, the framework allows the future incorporation of stakeholder input. Challenges identified include the need for early design integration, transport limitations, and site-specific constraints. By quantifying benefits and limitations, this study contributes to expanding the understanding of off-site modular adaptability of construction projects beyond low-cost housing, demonstrating its potential for diverse projects and advancing its implementation in emerging markets. Beyond technical and economic outcomes, the study also frames off-site modular construction within the three pillars of sustainability. Environmentally, it reduces structural weight, resource consumption, and on-site waste; economically, it improves cost efficiency and project delivery times; and socially, it offers potential benefits such as safer working conditions, reduced urban disruption, and faster provision of community-oriented buildings. These dimensions highlight its broader contribution to sustainable development in Brazil. Full article

Understanding the risk factors for vector-borne diseases, such as Crimean–Congo hemorrhagic fever (CCHF), is critical for effective public health strategies. This study aims to identify and map the environmental and climatic determinants influencing the distribution of Hyalomma marginatum, the primary vector of CCHF, in Türkiye, using a Multi-Criteria Decision Analysis (MCDA) approach. A rapid literature review was conducted to identify environmental, climatic, and methodological criteria used in MCDA studies on vector-borne diseases. Semi-structured interviews with local experts from Armenia, Serbia, and Türkiye provided fine-scale data on vector presence. These criteria were analyzed using the Analytic Hierarchy Process (AHP) and combined with Weighted Linear Combination (WLC) within the MCDA framework to produce risk maps for H. marginatum occurrence in Türkiye. Key environmental and climatic factors influencing H. marginatum distribution, such as temperature, humidity, vegetation, and precipitation, were identified. The MCDA analysis highlighted high-risk regions in Türkiye with elevated suitability for the vector, correlating with areas of human CCHF cases. MCDA risk maps are valuable tools for public health officials, enabling targeted surveillance and interventions. By integrating diverse environmental and climatic variables, this study enhances the understanding of CCHF dynamics and supports the development of focused control strategies. Full article

The paper’s priority aim is to review the scientific literature on multi-criteria analysis in the transport sector. The work is a continuation of research published in the previous works: Broniewicz, Ogrodnik, Multi-criteria analysis of transport infrastructure projects; and Broniewicz, Ogrodnik, A comparative evaluation of multi-criteria analysis methods for sustainable transport. This paper updates the literature review of the subject matter, considering scientific papers published between 2021 and 2024. Based on a literature review, the topic’s popularity under study was assessed, the most popular methods/groups of MCDM/MCDA methods applied to transportation decision-making problems were identified, and new research topics that emerged in recent years were also identified. The article also includes the case study—a multi-criteria analysis of a selected road investment in Poland. The project variant was selected using four different criteria weighting methods, and the obtained results were compared. The comparative analysis performed allowed for the assessment of the application potential of the selected MCDM/MCDA methods. Special attention was paid to the weighting methods. Based on the multi-criteria analysis, a comparable set of weights was obtained using the AHP and Fuzzy AHP methods, while different results were obtained using the CRITIC method characterized by an objective approach to weighting. The TOPSIS method was used for the final ranking of the variants of the selected real road investment. The results confirmed the ranking obtained from the official design documentation of the selected investment. Full article

This study applies a multicriteria decision analysis to explore how experts from different backgrounds assess traditional and emerging criteria for urban cycling. A hierarchical model with 7 main criteria and 31 subcriteria was evaluated by 30 specialists from academic, technical, and user-focused groups. Using pairwise comparisons and aggregated judgments, this study reveals points of agreement and divergence among expert priorities. Safety and infrastructure were rated as the most important factors. In contrast, contextual and technological aspects, such as Multimodality, Environmental Quality, Shared Systems, and Digital Solutions, received moderate to lower weights, with differences linked to expert profiles. These results highlight how different disciplinary perspectives influence the understanding of bikeability-related factors. Conceptually, the findings support a broader view of cycling conditions that incorporates both established and emerging criteria. Methodologically, this study demonstrates the value of the Analytic Hierarchy Process (AHP) as a participatory and transparent tool to integrate diverse stakeholder opinions into a structured evaluation model. This approach can support cycling mobility planning and policymaking. Future applications may include case studies in specific cities, combining expert-based priorities with local spatial data, as well as longitudinal research to track changes in cycling conditions over time. Full article

This study assesses and maps the physical flood vulnerability within the Xerias, Krafsidonas, and Anavros ungauged catchments in Volos, Thessaly, Greece, using a Geographical Information Systems (GIS)-based Multi-Criteria Decision Analysis (MCDA) integrated with the Analytic Hierarchy Process (AHP). Six factors influencing flood dynamics were selected including slope, flow accumulation, geology, land use/cover, flood history and burned areas. The factors were weighted using the AHP based on their relative influence in flood occurrence. Physical flood vulnerability was assessed utilizing the Weighted Linear Combination (WLC) method and visualized through thematic flood-vulnerability maps. The analysis indicates that the southwestern and central-southern parts of the study area, which are highly urbanized and industrialized, exhibit the highest physical flood-vulnerability. Specifically, 32.76% of the Xerias catchment, 41.16% of the Krafsidonas catchment, and 34.71% of the Anavros catchment exhibit high to very high flood vulnerability. On the other hand, mountainous areas with steep slopes, permeable lithology, and dense forests exhibit low to very low physical flood vulnerability. The method’s accuracy was verified through sensitivity analysis and comparison with national flood-risk data for the study area. The results emphasize the physical vulnerability of Volos to flooding and the necessity for targeted flood mitigation measures, demonstrating the value of GIS in flood risk management. Full article

This study investigates the optimal sizing of photovoltaic (PV) and battery storage (BAT) systems for Estonian households operating under grid constraints that prevent selling surplus energy. We develop and compare three sizing models of increasing complexity, ranging from a simple heuristic to a full simulation based optimization. Their performance is evaluated using a multi-criteria decision analysis (MCDA) framework that integrates Net Present Value (NPV), Internal Rate of Return (IRR), Profitability Index Ratio (PIR), and payback period. Sensitivity analyses are used to test the robustness of each configuration against electricity price shifts and market volatility. Our findings reveal that standalone PV-only systems are the most economically robust investment. They consistently outperform combined PV + BAT and BAT-only configurations in terms of investment efficiency and overall financial attractiveness. Key results demonstrate that the simplest heuristic-based model (Model 1) identifies configurations with a better balance of financial returns and capital efficiency than the more complex simulation-based approach (Model 3). While the optimization model achieves the highest absolute NPV, it requires significantly higher investment and results in lower overall efficiency. The economic case for batteries remains weak, with viability depending heavily on price volatility and arbitrage potential. These results provide practical guidance, suggesting that for grid constrained households, a well-sized PV-only system identified with a simple model offers the most effective path to cost savings and energy self-sufficiency. Full article

This research investigates the implementation of multi-criteria decision analysis (MCDA) within the framework of the Common Agricultural Policy (CAP) for the period of 2023–2027, focusing on optimizing agricultural sustainability and profitability in Northern Greece. Using data from three farmer groups across Central and Western Macedonia, the study explores the application of MCDA models within three distinct case studies: the first optimizes a farm system focused on input minimization (Loudias), while the second and third (Ryakio and Agia Paraskevi) adopt a more comprehensive approach to farm management. More specifically, the first case focused on maximizing gross margin, minimizing variable costs, and reducing fertilizer use without targeting a reduction in water usage. By contrast, the second case study adopted a holistic approach to farm management, integrating water conservation in the Ryakio farmer group. The third included the requirement to keep arable land fallow in the Agia Paraskevi farmer group, reflecting the CAP’s new mandates. The results indicate that MCDA facilitates strategic crop selection and land changes that significantly enhance farm management efficiency and sustainability. The optimization led to more significant percentage increases in gross margin for the second (Ryakio) and third (Agia Paraskevi) case studies compared to the first, with the Agia Paraskevi group showing the most substantial improvement. Full article

Multi-criteria decision analysis (MCDA) in furniture design is challenged by increasing product complexity and component proliferation. This study introduces a novel framework that integrates entropy reduction—achieved through dimensional standardization and modularity—as a core factor in the MCDA methodologies. The framework addresses both individual furniture evaluation and product family optimization through systematic complexity reduction. The research employed a two-phase methodology. First, a comparative analysis evaluated two furniture variants (laminated particleboard versus oak wood) using the Weighted Sum Model (WSM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The divergent rankings produced by these methods revealed inherent evaluation ambiguities stemming from their distinct mathematical foundations, highlighting the need for additional decision criteria. Building on these findings, the study further examined ten furniture variants, identifying the potential to transform their individual components into universal components, applicable across various furniture variants (or configurations) in a furniture line. The proposed dimensional modifications enhance modularity and interoperability within product lines, simplifying design processes, production, warehousing logistics, product servicing, and liquidation at end of lifetime. The integration of entropy reduction as a quantifiable criterion within MCDA represents a significant methodological advancement. By prioritizing dimensional standardization and modularity, the framework reduces component variety while maintaining design flexibility. This approach offers furniture manufacturers a systematic method for balancing product diversity with operational efficiency, addressing a critical gap in current design evaluation practices. Full article

Wave energy converters (WECs) that are installed in nearshore environments offer several practical advantages, including easier access, lower maintenance, reduced transmission costs, and potential integration with the existing coastal infrastructure, leading to cost savings and improved commercial viability. This study presents a techno-economic analysis and power take-off (PTO) optimization for a vertical cylindrical WEC positioned adjacent to a vertical seawall under irregular wave conditions. The PTO system is connected via frames and hinges, with one end connected to the vertical seawall and the other end to the arm extending to the oscillating WEC. Hydrodynamic parameters were obtained from WAMIT, incorporating the seawall effect via the image method using linear potential theory. This analysis considers variations in WEC diameter, the lengths of frame segments supporting the PTO system, and the PTO damping. First, the geometric configuration is optimized. The results show that placing the WEC closer to the seawall and positioning the hinge joint of the PTO frame at the midpoint of the actuating arm significantly enhances power extraction, due to intensified hydrodynamic interactions near the seawall. A techno-economic analysis is then conducted using two techno-economic metrics, with one representing device cost and the other a newly introduced metric for PTO cost, combined through the weighted sum model (WSM) within a multi-criteria decision analysis (MCDA) framework. Our findings indicate that a smaller-diameter WEC is more cost-effective within a narrow range of PTO damping, while larger WECs, although requiring higher PTO damping capacity, become more cost-effective at higher PTO damping values, due to increased power absorption. Optimal PTO damping values were identified for each diameter of the WEC, demonstrating the trade-off between power output and system cost. These findings provide practical guidance for optimizing nearshore WEC designs to achieve a balance between performance and cost. Full article

This paper presents a procedural method aimed at protecting maritime critical infrastructure, which is essential for the functioning of developed nations. A novel approach, developed by the authors, is introduced—focusing on the behavioral analysis of vessels to enable early identification of suspicious maritime activity and to prevent damage or destruction to key infrastructure elements. An integrated system is proposed, combining real-time electronic surveillance with continuous access to and analysis of data from both national and international databases. Drawing inspiration from medical sciences, a screening-based methodology has been developed. Data on vessels collected from various sources are processed according to the criteria adopted by the authors, using a multi-criteria decision analysis (MCDA) approach. MCDA is a decision-support method that considers multiple criteria simultaneously. It allows for the comparison and evaluation of different options, even when they are difficult to compare directly. This characteristic is used to select high-risk vessels for further monitoring. An initial classification of a vessel as suspicious does not constitute proof of criminal activity but rather serves as a trigger for further coordinated actions. Data on vessels is collected from the AIS (automatic identification system) and platforms that store vessel history. The AIS is a powerful tool that processes parameters such as a ship’s speed and course. This article presents sample results from surveillance and pre-selection analyses using the AIS, followed by a multi-criteria assessment of the behavior of vessels identified through this process. The results are presented both graphically and numerically. The authors conducted several scenarios, analyzing different groups of vessels. Based on this analysis, recommendations were developed for the interpretation of the findings. Full article

As organizations continue to embrace digital transformation, the need for robust cybersecurity strategies has never been more critical. This paper explores the Zero Trust Architecture (ZTA) as a contemporary cybersecurity framework that addresses the challenges posed by increasingly interconnected systems. Zero Trust (ZT) operates under the principle of “never trust, always verify,” ensuring that every access request is thoroughly authenticated, regardless of the requester’s location within or outside the network. However, implementing ZT is a challenging task, requiring an adequate roadmap to prioritize the different initiatives in agreement with company culture, exposure and cyber posture. We apply multi-criteria decision analysis (MCDA) to evaluate the relative importance of various components within a ZT framework, using the Incomplete Analytic Hierarchy Process (IAHP). Expert opinions from professionals in cybersecurity and IT governance were gathered through structured questionnaires, leading to a prioritized ranking of the eight key ZT pillars, as defined by the Cybersecurity and Infrastructure Security Agency (CISA), Washington, DC, USA, along with a prioritization of the sub-elements within each pillar. The study provides actionable insights into the implementation of ZTA, helping organizations prioritize security efforts to mitigate risks effectively and build a resilient digital infrastructure. The evaluation results were used to create a prioritized framework, integrated into the ZEUS platform, developed with Teleconsys S.p.A., to enable detailed assessments of a firm’s cyber partner regarding ZT and identify improvement areas. The paper concludes by offering recommendations for future research and practical guidance for organizations transitioning to a ZT model. Full article

Rainwater harvesting for sustainable agriculture (RWHSA) offers a viable and eco-friendly strategy to alleviate water scarcity in semi-arid regions, particularly for agricultural use. This study aims to identify optimal sites for implementing RWH systems in northern Iraq to enhance water availability and promote sustainable farming practices. An integrated geospatial approach was adopted, combining Remote Sensing (RS), Geographic Information Systems (GIS), and Multi-Criteria Decision Analysis (MCDA). Key thematic layers, including soil type, land use/land cover, slope, and drainage density were processed in a GIS environment to model runoff potential. The Soil Conservation Service Curve Number (SCS-CN) method was used to estimate surface runoff. Criteria were weighted using the Analytical Hierarchy Process (AHP), enabling a structured and consistent evaluation of site suitability. The resulting suitability map classifies the region into four categories: very high suitability (10.2%), high (26.6%), moderate (40.4%), and low (22.8%). The integration of RS, GIS, AHP, and MCDA proved effective for strategic RWH site selection, supporting cost-efficient, sustainable, and data-driven agricultural planning in water-stressed environments. Full article

This article presents a comprehensive assessment of mudflow risk in the Talgar River basin through the application of Multi-Criteria Decision Analysis (MCDA) methods and numerical modeling using the Rapid Mass Movement Simulation (RAMMS) environment. The first part of the study involves a spatial assessment of mudflow hazard and susceptibility using GIS technologies and MCDA. The key condition for evaluating mudflow hazard is the identification of factors influencing the formation of mudflows. The susceptibility assessment was based on viewing the area as an object of spatial and functional analysis, enabling determination of its susceptibility to mudflow impacts across geomorphological zones: initiation, transformation, and accumulation. Relevant criteria were selected for analysis, each assigned weights based on expert judgment and the Analytic Hierarchy Process (AHP). The results include maps of potential mudflow hazard and susceptibility, showing areas of hazard occurrence and risk impact zones within the Talgar River basin. According to the mudflow hazard map, more than 50% of the basin area is classified as having a moderate hazard level, while 28.4% is subject to high hazard, and only 1.8% falls under the very high hazard category. The remaining areas are categorized as very low (4.1%) and low (14.7%) hazard zones. In terms of susceptibility to mudflows, 40.1% of the territory is exposed to a high level of susceptibility, 35.6% to a moderate level, and 5.5% to a very high level. The remaining areas are classified as very low (1.8%) and low (15.6%) susceptibility zones. The predictive performance was evaluated through Receiver Operating Characteristic (ROC) curves, and the Area Under the Curve (AUC) value of the mudflow hazard assessment is 0.86, which indicates good adaptability and relatively high accuracy, while the AUC value for assessing the susceptibility of the territory is 0.71, which means that the accuracy of assessing the susceptibility of territories to mudflows is within the acceptable level of model accuracy. To refine the spatial risk assessment, mudflow modeling was conducted under three scenarios of glacial-moraine lake outburst using the RAMMS model. For each scenario, key flow parameters—height and velocity—were identified, forming the basis for classification of zones by impact intensity. The integration of MCDA and RAMMS results produced a final mudflow risk map reflecting both the likelihood of occurrence and the extent of potential damage. The presented approach demonstrates the effectiveness of combining GIS analysis, MCDA, and physically-based modeling for comprehensive natural hazard assessment and can be applied to other mountainous regions with high mudflow activity. Full article

This study was conducted using Geographic Information Systems (GISs), Remote Sensing (RS) techniques, and the SLEUTH model based on Cellular Automata (CA) to analyze the spatial and temporal dynamics of urban growth in Sanliurfa Province and to create future projections. The model in question simulates urban sprawl by using Slope, Land Use/Land Cover (LULC), Excluded Areas, urban areas, transportation, and hill shade layers as inputs. In addition, disaster risk areas and public policies that will affect the urbanization of the city were used as input layers. In the study, the spatial pattern of urbanization in Sanliurfa was determined by using Landsat satellite images of six different periods covering the years 1985–2025. The Analytical Hierarchy Process (AHP) method was applied within the scope of Multi-Criteria Decision Analysis (MCDA). Weighting was made for each parameter. Spatial analysis was performed by combining these values with data in raster format. The results show that the SLEUTH model successfully reflects past growth trends when calibrated at different spatial resolutions and can provide reliable predictions for the future. Thus, the proposed model can be used as an effective decision support tool in the evaluation of alternative urbanization scenarios in urban planning. The findings contribute to the sustainability of land management policies. Full article

Supplier selection is a crucial factor for ensuring compliance with the circular economy’s principles. Existing approaches often overlook the integration of circularity and risk assessment in supplier evaluation, limiting their effectiveness in achieving sustainability goals. This paper addresses this gap by applying suitable criteria and proposing a structured decision-making model for circular supplier selection. The model innovatively integrates Multi-Criteria Decision Analysis (MCDA) techniques with risk evaluation, providing a comprehensive framework for assessing suppliers in circular supply chains. By advancing the theoretical understanding of circular supplier selection, this research contributes to both academia and practice, reinforcing the alignment between supply chain decision-making and the Sustainable Development Goal (SDG), particularly Target 12.5. Full article