Search Results (570)

Defining compensatory interactions among criteria is a critical yet often subjective step in multi-criteria decision analysis (MCDA). To address this gap, this study proposes a novel model centered around the Inter-Criteria Compensation Index (ICCI), which is a quantitative measure derived from the standard error between normalized criterion values. The ICCI, complemented by correlation analysis and statistical significance testing, provides a structured framework to objectively identify compensatory, non-compensatory, or partially compensatory criteria pairs. The model also includes a method for adjusting criterion weights based on the ICCI and a sensitivity analysis to detect redundancies. We demonstrate the applicability of this framework through a case study ranking the 17 best-selling small electric vehicles in Brazil based on eight technical and economic criteria. The analysis revealed that six of the eight criteria exhibited strong compensatory relationships, while two were identified as non-compensatory. The subsequent ranking, generated using the TOPSIS method with adjusted weights, identified the optimal vehicle choice, and the sensitivity analysis confirmed that all compensatory criteria were essential, as their removal significantly altered the results. The proposed model reduces subjectivity in method selection, enhances the robustness of MCDA, and provides researchers with a verifiable tool for analyzing complex decision problems. Full article

Objectives: To describe the perinatal outcomes of a series of monochorionic diamniotic (MCDA) twin pregnancies complicated by selective fetal growth restriction (sFGR), classified according to the umbilical artery (UA) Doppler flow pattern of the smaller twin, and managed in a single centre over a 12-year period. Methods: Retrospective cohort study involving MCDA twin pregnancies followed up at the Twin Pregnancy Care Unit of Sant’Anna Hospital, Turin, Italy, between January 2010 and May 2023. We compared perinatal outcomes of MCDA pregnancies classified based on the UA Doppler flow pattern of the smaller twin. Results: The percentage of sFGR in our sample was 14.8%. A total of 103 MCDA pregnancies with sFGR were included. In 34.9% cases, the UA flow pattern changed throughout pregnancy. At last examination, 58.3% cases were classified as type I, 25.2% as type II and 16.5% as type III. The perinatal survival rate of both twins in type I and III was 100%, in type II 88.5%. Type II sFGR had the highest perinatal mortality rate (7.7%). Type III twins were more likely to have malformations compared to type II and type I; compared to type I sFGR babies, they were more likely to develop RDS and to be admitted to NICU, where the length of stay was longer. Conclusions: Although the UA flow pattern correlates with perinatal outcome, it can change throughout pregnancy. Type III sFGR may have lower risk of fetal demise than traditionally thought. The main challenge remains finding the optimal balance between adverse outcomes and premature birth. Full article

The rising penetration of electric vehicles is driving huge demand for lithium batteries, making low-carbon manufacturing a critical objective. This goal is challenged by insufficient production scheduling flexibility and the neglect of carbon-reduction technologies. To address these challenges, this paper develops a low-carbon planning methodology for lithium battery plant energy systems by leveraging manufacturing chain flexibilities. First, a lithium battery energy–carbon material modeling approach is developed that accounts for process production delays and intermediate product storage to capture schedulable process energy consumption patterns. A nitrogen–oxygen coupling production framework is introduced to facilitate oxygen-enriched combustion technology application, while energy recovery pathways are incorporated given the high energy consumption of the formation stage. Subsequently, a process scheduling-driven planning model for lithium battery industrial integrated energy systems (IIES) is developed. Finally, the planning model is validated through four contrasting case studies and systematically evaluated using multi-criteria decision analysis (MCDA). The results demonstrate three principal conclusions: (1) incorporating process scheduling effectively enhances process energy flexibility and reduces total system costs by 19.4%, with MCDA closeness coefficient improving from 0.257 to 0.665; (2) oxygen-enriched combustion increases maximum combustion and carbon capture (CCS) rates from 90% to 95%, reducing carbon tax to 40.5% of the baseline; (3) energy recovery on the basis of process scheduling further reduces costs and carbon emissions, with battery recovery achieving an additional 30.2% cost reduction compared to 24.1% for heat recovery, and MCDA identifies this integrated approach as the optimal solution with a closeness coefficient of 0.919. Full article

Application of low-emission hydrogen production methods in the decarbonization process remains a highly relevant topic, particularly in the context of sustainable hydrogen value chains. This study evaluates hydrogen applications beyond industry, focusing on its role as an energy carrier and applying multi-criteria decision analysis (MCDA) to assess economics, environmental impact, efficiency, and technological readiness. The analysis confirmed that hydrogen use for heating was the most competitive non-industrial application (ranking first in 66%), with favorable efficiency and costs. Power generation placed among the top two alternatives in 75% of cases. Transport end-use was less suitable due to compression requirements, raising emissions to 272–371 g CO₂/kg H₂ and levelizing the cost of hydrogen (LCOH) to 13–17 EUR/kg. When H₂ transport was included, new pipelines and compressed H₂ clearly outperformed other methods for short- and long-distances, adding only 3.2–3.9% to overall LCOH. Sensitivity analysis confirmed that electricity price variations had a stronger influence on LCOH than capital expenditures. Comparing electrolysis technologies yielded that, proton-exchange membrane and solid oxide reduced costs by 12–20% and CO₂ emissions by 15–25% compared to alkaline. The study highlights heating end-use and compressed hydrogen and pipeline transport, proving MCDA to be useful for selecting scalable pathways. Full article

Satellite Precipitation Products (SPPs) play a crucial role in hydrological modeling, particularly in data-scarce and climate-sensitive basins such as the Magat River Basin (MRB), Philippines—one of Southeast Asia’s most typhoon-prone and infrastructure-critical watersheds. This study presents the first full-cycle evaluation of nine widely used multi-source precipitation products (2000–2024), integrating raw validation against rain gauge observations, bias correction using quantile mapping, and post-correction re-ranking through an Entropy Weight Method–TOPSIS multi-criteria decision analysis (MCDA). Before correction, SM2RAIN-ASCAT demonstrated the strongest statistical performance, while CHIRPS and ClimGridPh-RR exhibited robust detection skills and spatial consistency. Following bias correction, substantial improvements were observed across all products, with CHIRPS markedly reducing systematic errors and ClimGridPh-RR showing enhanced correlation and volume reliability. Biases were decreased significantly, highlighting the effectiveness of quantile mapping in improving both seasonal and annual precipitation estimates. Beyond conventional validation, this framework explicitly aligns SPP evaluation with four critical hydrological applications: flood detection, drought monitoring, sediment yield modeling, and water balance estimation. The analysis revealed that SM2RAIN-ASCAT is most suitable for monitoring seasonal drought and dry periods, CHIRPS excels in detecting high-intensity and erosive rainfall events, and ClimGridPh-RR offers the most consistent long-term volume-based estimates. By integrating validation, correction, and application-specific ranking, this study provides a replicable blueprint for operational SPP assessment in monsoon-dominated, data-limited basins. The findings underscore the importance of tailoring product selection to hydrological purposes, supporting improved flood early warning, drought preparedness, sediment management, and water resources governance under intensifying climatic extremes. Full article

Hybrid marine energy platforms that integrate wave energy converters (WECs) and hydrokinetic turbines (HKTs) offer potential to improve energy yield and system stability in marine environments. This study identifies a compatible WEC–HKT integrated system concept through a structured concept selection framework based on multi-criteria decision analysis (MCDA). The framework follows a two-stage process: individual technology assessment using eight criteria (efficiency, TRL, self-starting capability, structural simplicity, integration feasibility, environmental adaptability, installation complexity, and indicative cost) and pairing evaluation using five integration-focused criteria (structural compatibility, PTO feasibility, mooring synergy, co-location feasibility, and control compatibility). Criterion weights were assigned through a four-level importance framework based on expert judgment from 11 specialists, with unequal weights for the individual evaluation and equal weights for the integration stage. Four WEC types (oscillating water column, point absorber, overtopping wave energy converter, and oscillating wave surge converter) and four HKT types (Darrieus, Gorlov, Savonius, and hybrid Savonius–Darrieus rotor) are assessed using literature-derived scoring and weighted ranking. The results show that the oscillating water column achieved the highest weighted score among the WECs with 4.05, slightly ahead of the point absorber, which scored 3.85. For the HKTs, the Savonius rotor led with a score of 4.05, surpassing the hybrid Savonius–Darrieus rotor, which obtained 3.50, by 0.55 points. In the pairing stage, the OWC–Savonius configuration achieved the highest integration score of 4.2, surpassing the PA–Savonius combination, which scored 3.4, by 0.8 points. This combination demonstrates favorable structural layout, PTO independence, and mooring simplicity, making it the most promising option for early-stage hybrid platform development. Full article

Rapid urbanization across Southern Asia’s coastal regions has significantly increased electricity demand, driving India’s solar sector expansion under the National Solar Mission and positioning the country as the world’s fourth-largest solar market. Nonetheless, methodological limitations remain in applying GIS-based multi-criteria decision analysis (MCDA) frameworks to coastal urban microclimates, which involve intricate land-use dynamics and resilience constraints. To address this gap, this study proposes a multi-criteria GIS- based Analytical Hierarchy Process (AHP) framework, incorporating remote sensing and geospatial data, to assess Solar Farm Sites (SFSs) suitability, supplemented by sensitivity analysis in Thoothukudi coastal city, India. Ten parameters—covering photovoltaic, climatic, topographic, environmental, and accessibility factors—were used, with Global Horizontal Irradiance (18%), temperature (11%), and slope (11%) identified as key drivers. Results show that 9.99% (13.61 km²) of the area has excellent suitability, mainly in the southwest, while 28.15% (38.33 km²) exhibits very high potential along the southeast coast. Additional classifications include good (22.29%), moderate (32.41%), and low (7.16%) suitability zones. Sensitivity analysis confirmed photovoltaic variables as dominant, with GHI (0.25) and diffuse radiation (0.23) showing the highest impact. The largest excellent zone could support approximately 390 MW, with excellent and very high zones combined offering up to 2080 MW capacity. The findings also underscore opportunities for dual-use solar deployment, particularly on salt pans (17.1%), as well as elevated solar installations in flood-prone areas. Overall, the proposed framework provides robust, spatially explicit insights to support sustainable energy planning and climate-resilient infrastructure development in coastal urban settings. Full article

Background/Objectives: This study aimed to apply a multicriteria decision analysis to assess the comprehensive value of omalizumab for moderate to severe pediatric asthma in China. Methods: A multidisciplinary panel of 17 experts assessed the value of omalizumab plus the standard of care (SOC) using SOC alone as a comparator. We developed a hierarchical criteria system with six main domains and 15 specific criteria. To establish a comprehensive evidence matrix, we integrated findings from a systematic literature review (SLR) and a real-world pharmacovigilance study based on the FAERS database. The overall estimated value of each strategy was obtained by combining the criterion weights with the score of each strategy in each criterion. A sensitivity analysis was conducted to validate the robustness of the results. Results: According to the AHP methods, the following weights were assigned to the criteria: safety (38.55%), effectiveness (28.85%), economics (9.65%), innovation (8.24%), accessibility (7.84%), and applicability (6.88%). Based on the evidence matrix, omalizumab plus SOC scored higher than the SOC in effectiveness (2.53 vs. 1.94) and innovation (0.70 vs. 0.15). When the weight and score of each strategy in each criterion were combined, the overall estimated values were 7.40 points for omalizumab plus SOC and 7.19 points for SOC. Conclusions: Adding omalizumab was assessed as a conditionally recommended strategy for treating moderate to severe asthma in Chinese children. Full article

The digital economy is a key driver of industrial upgrading and regional growth. Focusing on Gansu Province—an under-represented, less-developed region in northwest China—this study constructs a multidimensional digital economy index (DEI) for 2009–2023 under a unified normalisation and weighting scheme. Two complementary MCDA approaches—entropy-weighted TOPSIS and SESP-SPOTIS—are implemented on the same 0–1 normalised indicators. Robustness is assessed using COMSAM sensitivity analysis and is benchmarked against a PCA reference. The empirical analysis then estimates log-elasticity models linking modern logistics production (MLP) and the DEI to the provincial GDP and sectoral value added, with inferences based on White heteroskedasticity–robust standard errors and bootstrap confidence intervals. Results show a steady rise in the DEI with a temporary dip in 2021 and recovery thereafter. MLP is positively and significantly associated with GDP and value added in the primary, secondary, and tertiary sectors. The DEI is positively and significantly associated with GDP, the primary sector, and the tertiary sector, but its effect is not statistically significant for the secondary sector, indicating a manufacturing digitalisation gap relative to services. Cross-method agreement and narrow sensitivity bands support the stability of these findings. Policy implications include continued investment in digital infrastructure and accessibility, targeted acceleration of manufacturing digitalisation, and the development of a “digital agriculture–smart logistics–green development” pathway to foster high-quality, sustainable regional growth. Full article

The selection of the most economically advantageous tender (MEAT) in public procurement procedures requires transparent evaluation systems capable of integrating heterogeneous criteria, including qualitative ones, to reconcile quality and cost. This systematic review analyzes 74 studies published between 1998 and 2023 to explore the application of multi-criteria decision analysis (MCDA) methods in public construction procurement. The vast majority of MCDA applications focus on the award phase, with constant growth over the last 10 years. However, applications in the prequalification and verification phases are much less frequent and remain under-represented. Geographically, Europe is the most active area in terms of publications, followed by China and some countries in the Asia-Pacific area. In these regions, MCDA has been employed more systematically over time, while in other areas (e.g., Africa, Latin America), applications are sporadic or absent. Analytic Hierarchy Process (AHP) is confirmed as the most widely used technique. Emerging techniques (such as BWM, MABAC, EDAS, VIKOR, advanced TOPSIS) show greater computational rigor and in some cases better theoretical properties, but are less used due to complexity, less practical familiarity and the lack of accessible software tools. The operationalization of environmental and social criteria is still poorly standardized: clear indications on metrics, measurement scales and data sources are often lacking. In most cases, the criteria are treated in a generic or qualitative way, without common standards. Furthermore, the use of sensitivity analyses and procedures for aggregating judgments between evaluators is limited, with a consequent risk of poor robustness and transparency in the evaluation. In order to consider proposing a framework or guidelines based on the review findings, a six-step operational framework that connects selection of criteria and their operationalization, choice of method based on the context, robustness checks and standard minimum reporting, with clear assignment of roles and deliverables, is provided. The framework summarizes and makes the review evidence applicable. Full article

Hydrogen is key to achieving a net-zero carbon future, yet current production remains predominantly fossil-based. Biohydrogen derived from agricultural residues represents a sustainable alternative aligned with circular economy principles. While several studies have assessed the bioenergy potential from agricultural residues in various African countries, their potential in Togo remains largely unexplored. This study employed an exploratory mixed-methods approach to quantify residue availability, evaluate production pathways, and estimate potential biohydrogen yields. Secondary data on crop production from the Food and Agriculture Organization (FAO) and theoretical conversion factors were used to assess the availability of agricultural residues from the eight major crops in Togo, resulting in a residue potential of 7.95 million tons per year. Considering ecological and competing aspects of residue utilization, a sustainable share of 3.1 to 6.6 million tons was estimated to be available for biohydrogen production, depending on the residue recoverability assumptions. A multi-criteria decision analysis (MCDA) was used to evaluate different biohydrogen production processes, identifying dark fermentation as the most suitable due to its low energy requirements and decentralized applicability. The theoretical biohydrogen potential was estimated at 20,991–42,293 tons per year (2.5–5.1 PJ per year) based on biochemical residue composition data and stoichiometric calculations. This study established a baseline assessment of biohydrogen potential from agricultural residues in Togo, offering a methodological framework for assessing biohydrogen potential in other regions. The results also underscore the need for site-specific data to reduce uncertainty and support evidence-based energy planning. Full article

This study presents a novel methodology for mapping Fault- and Thrust-based Structural Lineaments (FT-SL) in the rugged and inaccessible Oued-Laou watershed of the Rif Belt, Morocco. Combining optical (Landsat-8 OLI, Sentinel-2 MSI) and radar (Sentinel-1 SAR) remote sensing data, the research employs manual, semi-automatic, and automatic extraction methods enhanced by spatial filtering (Sobel, Laplacian, Kuan). A Knowledge-Based System (KBS) integrated with Multi-Criteria Decision Analysis (MCDA) evaluates the effectiveness of these methods, focusing on lineament statistics, orientation, density distribution, and correlation with existing geological maps. The results highlight Sentinel-1 SAR’s superior performance in detecting subsurface structures, while manual extraction yields the highest accuracy. This study also demonstrates the potential for generalizing this approach to other Alpine orogenic regions, such as the Alps, due to shared geological characteristics. The findings provide a robust framework for structural lineament mapping in mountainous terrains, addressing challenges of accessibility and data scarcity. Full article

In the developing countries (e.g., Palestine) a reliable assessment of climate vulnerability, exposure, and consequently risk is a key step in developing successful adaptation and mitigation plans. This study aims to examine the spatial distribution of climate risk across the different governorates of the West Bank (Palestine) by assessing climate-risk exposure. A GIS-based Multi-Criteria Decision Analysis approach was employed to estimate climate exposure across the West Bank governorates. Additionally, sensitivity analysis is used to explore the impact of indicator weight on the final climate-risk map. The climate-risk map was subsequently developed based on the exposure map, classifying the governorates into five risk categories: very high, high, moderate, low, and very low. This analysis revealed that 42% of the West Bank population resides in areas classified as having high to very high climate exposure, which corresponds to approximately 39% of the total land area. Conversely, about 21% of the West Bank area is categorized under low to very low risk conditions. By measuring risk based on this exposure, and considering vulnerability, it was determined that 82% of the population lives within areas identified as high to very high zones, underscoring the significant climate risk of populated regions. This study offers the first spatially explicit climate-risk assessment for the West Bank, applying a widely accepted approach that integrates vulnerability and exposure components. The results provide critical insights to inform targeted adaptation and mitigation efforts, supporting decision-makers in enhancing climate resilience across the region. Full article

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