Search Results (25)

Soil erosion in arid watersheds poses a significant threat to land productivity, water resources, and long-term sustainability, necessitating spatially explicit and data-driven prioritization frameworks for targeted conservation. This study developed an integrated GIS-based multi-criteria decision-making (MCDM) framework to assess soil erosion susceptibility and prioritize twelve sub-basins (SB) of the Wadi Numan basin (683 km²), Makkah Region, Saudi Arabia. Morphometric analysis was conducted using sixteen parameters derived from a 10 m Digital Elevation Model (DEM), and Land Use/Land Cover (LULC) data were obtained from the Esri Sentinel-2 10 m dataset. Four MCDM techniques—additive ratio assessment (ARAS), complex proportional assessment (COPRAS), multi-objective optimization by ratio analysis (MOORA), and technique for order preference by similarity to ideal solution (TOPSIS)—were applied under the criteria importance through inter-criteria correlation (CRITIC) objective weighting, and their consistency was evaluated using the Spearman correlation coefficient test (SCCT) and the Kendall Tau correlation coefficient test (KTCCT). MOORA achieved the highest consistency for morphometric analysis (SCCT: 0.982; KTCCT: 0.958), while TOPSIS performed best for LULC analysis (SCCT: 0.800; KTCCT: 0.731). The final combined prioritization used MOORA for morphometric analysis and TOPSIS for LULC analysis, with proportional weighting of 72.7% and 27.3%, respectively. The scheme categorized the sub-basins into five levels of soil erosion priority. The composite ranking classified SB-9 and SB-1 under very high priority (25.94%); SB-2 and SB-3 under high priority (6.40%); SB-5, SB-6, and SB-10 under medium priority (36.37%); SB-4 and SB-8 under low priority (18.11%); and SB-11, SB-12, and SB-7 under very low priority (13.18%). This integrated method provides a practical decision-support tool for identifying and managing sub-basins susceptible to soil erosion, thereby promoting the long-term sustainability of land and water resources. Full article

One of the most critical challenges in maritime transport decarbonization, as part of the EU greenhouse gas (GHG) neutrality strategy, is the reduction in GHG and harmful emissions from the energy systems of existing vessels. Furthermore, the potential for implementing decarbonization technologies in operating vessels remains significantly more limited compared to newly constructed ships. Selecting appropriate decarbonization measures requires a comprehensive evaluation of technological feasibility, economic viability, and environmental performance, in accordance with the regulatory frameworks established by the IMO and the EU. A major limitation in such decision-making processes is ensuring the representativeness and reliability of expert judgments. In order to improve the reliability of results by expanding and structuring the information base, this study proposes and implements a method based on the integration of SWOT analysis with multi-criteria decision-making (MCDM) methods. The objective of this study was to examine the methodological aspects of testing the integrated application of comprehensive analysis and ranking methods for decarbonization technologies as applied to a prototype oil tanker. Based on the SWOT analysis method, technological solutions that are available for practical application were identified for the medium-term decarbonization period considered in the study, up to 2030–2035. Subsequent rating based on several applied multi-criteria (MCDM) analysis methods (TOPSIS, COPRAS, SAW) allowed us to examine the range, stability and sensitivity of the obtained solutions in relation to the methods themselves and scenarios with variations in the weighting factors of the evaluation criteria. The complete match of the ratings obtained using the TOPSIS and COPRAS methods confirms the stability of the multi-criteria decision-making process (priority-compromise order): CCS, kite, air lubrication, Flettner rotor. The performed sensitivity analysis showed that the technology rankings remain relatively stable when the weighting factor for the CO₂ reduction criterion varies within a range of approximately ±10%, while larger deviations result in an increasing difference between all three MCDM methods. For the TOPSIS method, the change limits for the critical values of the threshold indicators were ±20%, the COPRAS method showed intermediate results, and changing the weighting coefficients within a ±20% range did not alter the selection of the best technology. The results obtained allow for a positive assessment of the effectiveness of the proposed integrated methodology when applied as an alternative in the initial stage of ranking decarbonization methods for in-service ships. Full article

E-commerce has been a rapidly growing sales channel in recent years, with a strong trend toward further expansion. However, logistics companies face significant challenges in the preparation and sorting of orders when delivering shipments purchased through e-commerce platforms. In this process, order pickers play a pivotal role, as their efficiency directly impacts both the operational performance of logistics companies and the quality of service provided to customers. During peak periods of high order volumes, it is common for order pickers to exceed the prescribed work norm, making them eligible for performance-based bonuses. This study aims to develop a model for evaluating order picker efficiency, ranking them, and determining the optimal allocation of bonuses. It addresses a critical gap in the existing literature, as only a handful of studies have explored this issue in depth. To assess the efficiency of 56 order pickers, the DEA method was applied, incorporating three input and five output variables. The analysis identified 18 order pickers as fully efficient. These individuals were then ranked using the IMF SWARA and COPRAS methods, where IMF SWARA was employed to determine the weights of nine evaluation criteria, while COPRAS was used for the final ranking process. Based on the ranking results, a structured bonus allocation model was developed, encompassing four distinct scenarios. Furthermore, a sensitivity analysis and model validation were conducted to ensure the robustness and reliability of the proposed approach. Full article

The development of high-performance, sustainable biocomposites requires biodegradable matrices and optimized natural reinforcements. In this study, flax fiber-reinforced polylactic acid (PLA) hybrid biocomposites incorporating waste pistachio nut shells (WPNS), waste tea leaf fiber (WTLF), and waste quail eggshell (WQES) were developed and evaluated, with direct comparison to previously reported jute-based hybrid systems to assess the benefits of fiber substitution. The composites were fabricated via compression molding and characterized for their mechanical, thermal, acoustic, surface, and moisture-related properties. Replacing the jute with flax resulted in a consistent performance enhancement. Among the hybrids, the flax–WPNS composite exhibited the highest tensile and flexural performance, achieving tensile strength improvements of approximately 30–40% over neat PLA due to effective stress transfer and crack deflection. The flax–WTLF composite showed superior acoustic behavior, attaining a maximum sound absorption coefficient of approximately 0.65–0.70 at mid-to-high frequencies, attributed to its porous microstructure. In contrast, the flax–WQES composite demonstrated the highest thermal conductivity (0.54 W/(mK)) and apparent density (2.24 g/cm³), reflecting dense packing and the presence of CaCO₃-rich particles. Scanning electron microscopy revealed distinct microstructural mechanisms governing these property-specific responses, including differences in interfacial bonding, void distribution, and filler packing efficiency. An integrated fuzzy CRITIC–COPRAS multicriteria decision-making approach identified the flax–WPNS hybrid as the optimal overall formulation. The results clearly demonstrate that flax fibers outperform jute as a reinforcement in PLA-based hybrid biocomposites, and that targeted combinations of flax and waste-derived fillers enable multifunctional performance optimization for sustainable engineering applications. Full article

Effective management of Environmental, Social, and Governance (ESG) practices within the framework of transparency and accountability in businesses is crucial for enhancing their compliance capacity in the face of regulatory pressures and contributing to the early detection of environmental and social risks. This study aims to evaluate the ESG disclosure-based performance of businesses operating in the textile, clothing, and leather sectors in Turkey by examining their ESG indicators from a transparency and accountability perspective. The CRITIC (Criteria Importance Through Intercriteria Correlation) method was used to determine the relative importance levels of the indicators, while the MABAC (Multi-Attributive Border Approximation Area Comparison) and COPRAS (Complex Proportional Assessment) methods were used to rank the performance of businesses within the framework of these indicators. Finally, clustering analysis was used to classify businesses with similar characteristics. The findings show that corporate governance principles are the most important indicator, and that Kordsa Teknik Tekstil A.Ş. and Söktaş Tekstil Sanayi ve Ticaret A.Ş. exhibit a significant and positive difference in terms of transparency and accountability in their ESG practices compared to other businesses. The combined use of CRITIC, MABAC, COPRAS, and cluster analysis offers an innovative, robust decision-making approach and holistic methodological integration for assessing ESG disclosure-based performance in the context of transparency and accountability for businesses. Full article

Universal accessibility remains a critical challenge for effective public transport and urban equity. This study addresses the need for operational prioritisation tools by proposing a robust hybrid methodology to rank interventions at urban mobility nodes. The approach combines the Analytic Hierarchy Process (AHP) for integrating expert and participatory criteria weighting with four Multi-Criteria Decision-Making (MCDM) techniques (TOPSIS, VIKOR, COPRAS, and ARAS) to ensure solution reliability. Empirical validation, conducted on 30 bus stops in Segovia, Spain, confirmed the methodological soundness, evidenced by near-perfect correlations (ρ = 0.99) among the compromise and additive ratio models (TOPSIS–VIKOR and COPRAS–ARAS) and stability across over 85% of sensitivity simulations. The findings validate that the methodology effectively guides resource allocation towards interventions yielding maximum social impact and demonstrate its transferability to complex urban supply chain contexts, such as logistics microhubs. Ultimately, this replicable and adaptable model supports the transition towards more equitable, resilient urban systems, aligning directly with Sustainable Development Goal 11 (Sustainable Cities and Communities). Full article

Iran is a uniquely compelling case due to its ancient and diverse culinary heritage, coupled with a strategic national mandate to significantly boost tourism, making the development of this high-impact sector a crucial policy imperative. The present study adopts a scenario planning approach to first identify the key factors influencing food tourism in rural areas of Iran, then explores plausible future scenarios for rural tourism development, and finally ranks strategic alternatives for enhancing food tourism in these regions. Methodologically, the research combines a goal-oriented, descriptive-analytical approach with future study techniques. Data for the initial phase were collected through a literature review, field studies (surveys, interviews), and expert surveys, and subsequently analyzed using MICMAC and ScenarioWizard software tools. Strategic alternatives were then evaluated using Picture Fuzzy Sets (PFSs) and the COPRAS method based on six critical factors. The findings reveal that six primary factors—promotional activities, pricing, food quality, infrastructure, government support, and investment—play pivotal roles in advancing food tourism in rural Iran. Based on these six primary factors, the study constructs three future scenarios: optimistic, stagnant, and crisis-driven scenarios. In the third phase of the analysis, employing Picture Fuzzy COPRAS and Picture Fuzzy Analytic Hierarchy Process (PF-AHP), the results indicate that “food festivals and promotional campaigns” carry the greatest weight and are deemed the most influential in attracting tourists, whereas “investment” ranks the lowest. Following normalization and application of weights, COPRAS analysis identifies “improving the quality of tourism infrastructure” as the most effective strategy, receiving the highest score (464.0620). A sensitivity analysis further confirms that the overall ranking of the strategies remains stable despite changes in the criteria weights, with only minor shifts observed among mid-ranked alternatives. These results offer policymakers a practical decision-making tool to allocate limited resources efficiently and focus on high-impact strategies that support the sustainable development of food tourism in Iran’s rural areas. Full article

Cement production significantly contributes to global warming, resource depletion, environmental degradation, and environmental pollution. Identifying sustainable alternatives is critical but requires balancing multiple, often conflicting, factors. The objective of this study is to determine the most preferred cement alternative produced in South Africa using an integrated life cycle assessment (LCA) and multi-criteria decision-making (MCDM) framework. The LCA quantified the environmental impacts of seven different cement-type alternatives across 18 midpoint impact categories. The LCA results showed that slag cement-based CEM III/A achieved a 50% reduction in global warming potential (GWP) compared to traditional CEM I (0.57 vs. 0.99 kg CO₂ eq. This study also used the entropy-weighted, COPRAS and ARAS methodologies to evaluate and rank cement types based on their environmental impacts and weighted sustainability criteria and the results showed that fly ash-based CEM II/B-V demonstrated the highest overall sustainability, with utility scores of 100.00 (COPRAS) and 0.7257 (ARAS) in MCDM ranking. These results highlight that fly ash-based cement offers substantial environmental benefits over traditional CEM I, particularly in reducing greenhouse gas emissions and resource consumption. The integrated LCA–MCDM method enables robust prioritization by linking quantitative environmental impacts with objective ranking criteria. Although this analysis focuses on South African cement formulations, the methodology and findings are applicable to other regions with similar production profiles and SCM availability. The framework offers a practical tool for policymakers and industry to support environmentally responsible decision-making in cement production. Full article

This study investigates the mechanical properties and optimization of hybrid composites composed of flax, vetiver, and mahogany fruit fillers (MFFs) using epoxy resin as the matrix material. Nine distinct composite configurations were fabricated using different MFF concentrations (0, 5, and 10 wt.%) to evaluate their influence on tensile strength, flexural strength, and impact resistance. The MFF was subjected to alkali treatment and characterized using FTIR, XRD, and particle size analysis to enhance its compatibility with the polymer matrix. Vetiver and flax fibers also underwent alkali treatment to improve interfacial bonding. The composite fabrication process followed the Taguchi L9 orthogonal array to optimize the design. Mechanical testing revealed that the incorporation of MFF significantly improved the overall performance, with FVM9 (10 wt.% MFF) exhibiting the highest tensile strength (56.32 MPa), flexural strength (89.65 MPa), and impact resistance (10.46 kJ/m²). The CRITIC–EDAS method was employed to rank the composite configurations, and FVM9 was identified as the optimal configuration. Comparisons with alternative MCDM methods (WASPAS, COPRAS, TOPSIS, and VIKOR) validated the reliability of the rankings, and FVM9 consistently performed the best. The sensitivity analysis demonstrated the robustness of the CRITIC–EDAS approach, as the rankings remained stable despite variations in the criterion weights. The synergistic effect of flax, vetiver, and MFF, along with improved interfacial bonding, contributed to the superior mechanical properties of the hybrid composites. These findings highlight the potential of FVM composites as sustainable, high-performance materials for various industrial applications in the automotive, construction, and aerospace sectors. Full article

Low-energy bone fractures refer to injuries that occur from minimal trauma or impact. These fractures are often a result of activities, such as falls from standing height or minor accidents, where the force exerted on the bone is insufficient to cause a break under normal conditions. To design an effective orthotic splint, it is critical to select the appropriate material that mimics the mechanical properties of traditional materials like plaster, which has long been used for immobilization purposes. In this case, Ansys CES Edupack 2025 software was utilized to evaluate and identify materials with mechanical characteristics similar to those of plaster. The software provided a list of six materials that met these criteria, but selecting the most suitable material involved more than just mechanical properties. Three different multicriteria decision-making methods were employed to ensure the best choice: TOPSIS, VIKOR, and COPRAS. These methods were applied to consider various factors, such as strength, flexibility, weight, cost, and ease of manufacturing. The results of the analyses revealed a strong consensus across all three methods. Each approach identified PLA (Polylactic Acid) as the most appropriate material for the orthotic design. Following the material selection process, simulations were conducted to assess the structural performance of the orthotic splint. The results determined that the minimum thickness required for the PLA orthosis was 4 mm, ensuring that it met all necessary criteria for acceptable stresses and deformations during the four primary movements exerted by the wrist. This thickness was sufficient to maintain the orthosis’s functionality without compromising comfort or effectiveness. Moreover, a significant improvement in the design was achieved through topological optimization, where the mass of the preliminary design was reduced by 9.58%, demonstrating an efficient use of material while maintaining structural integrity. Full article

One of the foremost challenges in today’s global economy is ensuring energy security for individual countries and regions. In the contemporary context, this security plays a pivotal role in ensuring sovereignty, fostering innovation, and bolstering competitiveness, particularly in knowledge-based economies. The pursuit of energy independence while mitigating adverse environmental impacts stands as a key priority in European Union policy. Efforts towards achieving a zero-carbon economy encompass all member states, including those in Central and Eastern Europe (CEE). This paper delves into this pressing issue by evaluating the sustainable energy security and policy efficiency of CEE countries over a 15-year period. This research employed a well-defined methodology, employing a multidimensional approach to address the complexity of the issue. The outcome of this approach was the development of the Sustainable Energy Security Index (SESI) for the countries under study, serving as a benchmark for evaluating energy security and policy effectiveness. Multiple Multi-Criteria Decision-Making (MCDM) methods, including COPRAS, EDAS, MAIRCA, and the Hurwicz criterion, were utilized to determine the SESI value. Additionally, CRITIC, equal weights, standard deviation methods, and Laplace’s criterion were employed to ascertain the weights of the indices characterizing various dimensions of sustainable energy security. The findings reveal significant disparities in energy security and policy implementation effectiveness among CEE countries. Slovenia, Croatia, Latvia, Romania, and Hungary demonstrated notably strong performance, while Poland and Bulgaria lagged behind. These results underscore the necessity of integrating findings into the energy and climate strategies of both CEE countries and the EU-27 as a whole. Full article

Jordan, which depends largely on imported fuel, is confronted with an increasing demand for energy due to regional socio-political dynamics and population growth. This dependence highlights the necessity of locally supplied, sustainable energy sources to reduce environmental damage and economic vulnerability. Thus, the goal of this study is to categorize these sources based on their priorities for use, as well as to develop and evaluate sustainable RE technologies. In order to diversify the energy portfolio, lessen reliance on fossil fuels, and offer suggestions for sustainable growth, this study investigates renewable energy sources (RES) in Jordan. A model is developed to study and evaluate RES technologies and introduce actions for their exploitation. In order to prioritize renewable energy sources and improve energy independence and sustainability, this paper looks at renewable energy technologies that are feasible for Jordan, using a variety of MCDM methodologies. This study emphasizes Jordan’s urgent need for green, sustainable energy, highlighting solar, hydropower, and wind projects as the most advantageous options, promoting energy independence. The outcomes designate the applicability of the proposed model and integrated tools for analyzing renewable energy technology. The findings assist a shift toward energy independence and sustainability by providing decision-makers with a systematic, data-driven method for prioritizing green energy investments. Full article

Sub-watershed prioritization using morphometric analysis and multi-criteria decision-making (MCDM) techniques is a systematic approach to identifying and ranking sub-watersheds based on their susceptibility to soil erosion. This helps in implementing targeted soil conservation measures. In this study, sub-watersheds in the Narangi basin are prioritized by employing morphometric analysis integrated with advanced MCDM techniques, including additive ratio assessment (ARAS), complicated proportional assessment (COPRAS), multi-objective optimization by ratio analysis (MOORA), and the technique for order preference by similarity to ideal solution (TOPSIS). Weights for various MCDM methods are determined using the criteria importance through an inter-criteria correlation approach (CRITIC: criteria importance through inter-criteria correlation method), while geospatial techniques ensure precise spatial analysis. The results provide a unified ranking of sub-watersheds, revealing that sub-watershed 3 (SW3) and SW9 are in the high-priority soil erosion category; SW1, SW2, SW5, and SW8 are medium-priority; and SW4, SW6, SW7, and SW10 are low-priority. This comprehensive and sustainability-oriented approach equips decision-makers with robust tools to identify and manage sub-watersheds at risk of soil erosion, ensuring the long-term sustainability of land and water resources. This study aligns with sustainable development goal 15 (life on land) and promotes sustainable land use practices to combat soil degradation. Full article

Energy plays an important role in both the economic and social development of countries and is a critical factor in human life. The high consumption of fossil fuels in energy production leads to serious environmental problems such as increasing greenhouse gas (GHG) emissions that lead to global warming and climate change. Many countries around the world have actively turned to renewable energy or sustainable energy sources in order to cope with the environmental crises caused by climate change. In this study, the renewable energy use performance of OECD countries in terms of sustainable development is evaluated. In the study, 38 countries were divided into three clusters for each year with the 13 variable K-means algorithm for the years 2018–2022. The criteria of the countries in the determined clusters were weighted with the CRITIC (Criteria Importance Through Intercriteria Correlation) method for each year during the study period. Countries with weighted criteria were ranked separately for each year within their own clusters using the COPRAS method. With these rankings, it is understood that the biggest share in achieving Türkiye’s “Net Zero 2053” targets among OECD countries is the transition from fossil fuels to renewable energy. Full article

With the rapid development of the economy, data have become a new production factor and strategic asset, enhancing efficiency and energy for technological innovation and industrial upgrading in enterprises. The evaluation of enterprise digital asset value (EDAV) is a typical multi-attribute decision-making (MADM) problem. Generalized hesitant fuzzy numbers (GHFNs) can better express the uncertainty and fuzziness of evaluation indexes, thus finding wide applications in MADM problems. In this paper, we first propose the Kullback–Leibler (K-L) divergence distance of GHFNs and prove its mathematical properties. Second, recognizing that decision-makers often have finite rationality in practical problems, we combine the cumulative prospect theory (CPT) with the Complex Proportional Assessment (COPRAS) method to propose the GHF-CPT-COPRAS model for solving MADM problems. Simultaneously, we extend the distance correlation-based Criteria Importance Through Intercriteria Correlation (D-CRITIC) method to the GHF environment to rationally calculate the weights of attributes in the EDAV evaluation problem. Finally, we apply the proposed GHF-CPT-COPRAS model to the EDAV evaluation problem and compare it with existing GHF decision-making methods to verify its effectiveness and feasibility. This study provides an important reference for addressing the EDAV assessment problem within an uncertain fuzzy environment and extends its application methods in the decision-making field. Full article