Search Results (298)

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

Considering the complexity of laser cutting technology, and difficulties and limitations when applying traditional multi-criteria decision-making (MCDM) methods, this study proposes a fuzzy MCDM methodology for the analysis of the fibre laser cutting process, assessment of alternative cutting conditions and selection of favourable cutting conditions. The experiment in fibre laser cutting of mild steel was based on a Box–Behnken design by considering three input parameters (focus position, cutting speed and oxygen pressure) and four relevant criteria for the assessment of cutting conditions (kerf width on a straight and curved cut, surface roughness and surface productivity). The proposed fuzzy MCDM methodology makes use of expert knowledge and experimental data for criteria evaluation and decision matrix development, respectively, while three fuzzy MCDM methods (fuzzy TOPSIS, fuzzy WASPAS and fuzzy ARAS) were used to determine the complete ranking of alternatives. Kendall’s tau-b and Spearman’s rho correlation tests were applied to compare the obtained ranking lists, while the stability of the ranking was assessed with the application of the Monte Carlo simulation. Finally, to approximate the fuzzy decision-making rule, a second-order model was developed to reveal the significance of process parameters and identify favourable laser cutting conditions. Full article

The assessment of company performance requires a holistic approach, encompassing both financial and non-financial metrics. Accordingly, we develop a comprehensive airline performance evaluation model utilizing the Balanced Scorecard (BSC)-based multi-criteria decision-making (MCDM) framework. Based on contingency theory, we use 30 Key Performance Indicators (KPIs) derived from the literature and develop a novel performance model by combining the BSC framework with the Method based on the Removal Effects of Criteria (MEREC) for KPI weighting and the Combined Compromise Solution (CoCoSo) for ranking. The focus on Turkish Airlines, serving as a comparative benchmark, over the period 2020–2023 reveals that while financial KPIs hold the greatest weight, non-financial KPIs have the most significant impact on performance. The lowest performance is recorded in 2020, most probably attributable to the COVID-19 pandemic, followed by a remarkable recovery in 2021. We offer a methodological contribution for managers, decision-makers, and scholars—an objective, data-driven tool to assess airline performance. Furthermore, we furnish policymakers with tangible data for more effective industrial incentives and convenient regulatory strategies. In contrast to most of the literature emphasizing financial indicators and subjective weighting approaches that might yield biased rankings, we suggest a novel integrated performance evaluation model tailored for the airline industry. Full article

Renewable energy sources (RESs) are increasingly being recognized as sustainable and accessible alternatives for the energy future. However, their intermittent nature poses significant challenges to system reliability and stability, necessitating the integration of energy storage systems (ESSs) to ensure sustainability and dependability. This study examines various ESS alternatives, evaluating their suitability for different applications using a multi-criteria decision-making (MCDM) approach. The methodology accommodates diverse criteria types, including qualitative and quantitative factors, represented as linguistic terms, interval values, and crisp numerical data. A techno-socio-economic framework for ESS selection is proposed and applied to Jordan’s unique energy landscape. This framework integrates technical performance, economic feasibility, and social considerations to identify suitable ESS solutions aligned with the country’s renewable energy goals. The study ranks twelve energy storage systems (ESSs) based on key performance criteria. Pumped hydro storage (PHS), thermal energy storage (TES), supercapacitors (SCs), and lithium-ion batteries (Li-ion BESS) lead the ranking. These systems showed the best performance in terms of scalability, efficiency, and integration with grid-scale applications in Jordan. Key applications analyzed include renewable energy integration, grid stability, load shifting, peak load regulation, frequency regulation, and seasonal energy storage. Results indicate that Li-ion batteries are most suitable for renewable energy integration, while flywheels excel in grid stability and frequency regulation. PHS was found to be the preferred solution for load shifting, peak load regulation, and seasonal storage, with hydrogen storage emerging as a promising option for long-duration needs. These findings provide critical insights to guide policy and infrastructure planning, offering a robust model for comprehensive ESS assessment in energy transition planning for countries facing similar challenges. Full article

In the present study, dam site suitability mapping was carried out for the Purna sub-basin of the upper Tapi basin. Constructing dams in strategically chosen locations is a crucial water management approach to alleviate flood risks and water scarcity. Selecting appropriate dam sites requires considering criteria such as precipitation, elevation, soil properties, slope, geomorphology, geology, lithology, stream order, distance from a road, and fault tectonics. To address this complex problem, integrating Multiple-Criteria Decision-Making (MCDM) techniques with Geographic Information System (GIS) has become increasingly prevalent. Among these techniques, the Analytic Hierarchy Process (AHP) is particularly effective for addressing water-related challenges. In this study, we developed a Dam Site Suitability Model (DSSM) by evaluating nine thematic layers: precipitation, stream order, geomorphology, geology, soil, elevation, slope, land use and land cover (LULC), and major fault tectonics. The AHP technique was employed to assign weights to these thematic layers, which were then used in an overlay analysis to create a suitability map with five classes ranging from high to low suitability. This study revealed that approximately 14% of the Purna sub-basin falls into the very high suitability category, while 27.2% is classified as highly suitable. This cost-effective approach not only simplifies the traditional method of dam site selection but also enhances decision-making accuracy. This methodology can be universally applied to identify potential dam sites, aiding flood mitigation and addressing water scarcity exacerbated by global and regional climate change. The DSSM, leveraging GIS and the AHP, can significantly improve dam management and promote sustainable, environmentally responsible water resource management practices worldwide. Full article

In response to the growing demand for sustainable and performance-driven building design, this study proposes an integrated digital methodology that combines Building Information Modeling (BIM), parametric scripting, and multi-criteria decision-making (MCDM) to optimize external wall assemblies. The approach leverages Autodesk Revit and Dynamo to automate the parametrization of insulation thickness while ensuring compliance with regulatory thresholds for thermal transmittance and surface mass. Acoustic performance is estimated using ECHO software, and a Weighted Sum Model (WSM) is applied to evaluate and rank configurations based on four criteria: economic cost, Global Warming Potential (GWP), embodied energy, and acoustic insulation. A case study involving 24 wall assemblies—generated from eight base stratigraphies and three insulation materials—demonstrates the method’s ability to balance environmental impact, occupant comfort, and construction feasibility. The results indicate that natural and bio-based materials, such as rammed earth and cork, offer the best overall performance, while conventional systems remain competitive in terms of cost. The proposed workflow reduces design time, increases transparency, and supports informed decision-making during early design stages. This research contributes to the digitalization of sustainability assessment in architecture by promoting integrative, replicable, and regulation-aligned practices for low-impact building envelopes. Full article

The optimisation of airport infrastructure capacities lacks adequate tools that would enable airport owners and managers to make strategic decisions related to sustainable development and strengthening multimodal connectivity. Assessing the sustainability of the transport system is one of the important issues in creating transport policies worldwide. In this research, the methodology of multi-criteria decision making (MCDM) was used, which can be applied to decision making and the evaluation of transport projects, considering more than one criterion in the selection process. The Stepwise Weight Assessment Ratio Analysis (SWARA) method is one of the new MCDM methods. The SWARA method will assess the weights of the selected main criteria and sub-criteria for the multimodal connection of airports to the railway transport infrastructure. In this method, the expert plays an important role in the evaluation and calculation of the criteria weights. This research also aims to respond to the need to define a framework for objective and transparent decision-making based on the assessment of the weighting factors of the selected main criteria and sub-criteria. To assess the justification for the choice of railway transport for connecting airports, financial, traffic, environmental, and availability criteria were used. Full article

Industrial enterprises and their supply chain partners are increasingly seeking methods to optimise production and logistics processes while pursuing sustainable development goals. The complexity and high risk associated with implementing Industry 4.0 technologies calls for structured decision-making support. This study presents a novel multi-criteria evaluation framework that integrates technological, organisational, and sustainability dimensions to support strategic transformation efforts. The proposed model comprises four subspheres of manufacturing, four subspheres of supply chain and logistics, twenty-three emerging technologies, and four sustainability perspectives adapted to industrial contexts. A hybrid MCDM approach combining DEMATEL and PROMETHEE II is applied to identify causal relationships, prioritise technologies, and rank sustainability priorities across different dimensions. The methodology enables companies to determine which technologies should be implemented first and how these relate to broader sustainability objectives. The results provide a structured roadmap for decision-makers, highlighting five key strategic areas for the sustainable implementation of Industry 4.0. In addition to its managerial relevance, the proposed model offers scientific novelty by bridging previously siloed research areas and demonstrating a data-driven approach to transformation planning. Full article

Selecting an appropriate business development model is central to strategic decision-making in economic and business management. These models shape sustainable growth, long-term scalability, and strategic flexibility. Existing evaluation methods rely on heuristic or qualitative judgments that lack transparency, reproducibility, and sensitivity to evaluation criteria. To address these limitations, this study introduces a hybrid multi-criteria decision-making (MCDM) framework that integrates VIKOR, entropy weighting, and simulation to evaluate 35 business development models derived from 245 real-world cases. The evaluation covers six strategic criteria: scalability, adaptability, risk exposure, financial sustainability, implementation complexity, and market relevance. Entropy weighting assigns criterion importance based on data variability, and simulation generates input sets for sensitivity and stability analysis. Results highlight Cross-Border Investment, Tiered Access, and Crowd-Backed models as top-performing strategies across multiple dimensions. By combining multiple tools in a unified framework, the research advances MCDM methodology and supports strategic business development planning under uncertainty. This contribution strengthens both academic insight and managerial practice in economics and business management. Full article

The Tibet Autonomous Region presents immense potential for concentrated solar power (CSP) development, driven by its exceptional solar irradiance levels (e.g., a peak DNI exceeding 2100 kWh/m²/day). This positions it as a strategic contributor to China’s 2060 carbon neutrality target and aligns with global energy transition imperatives. However, CSP deployment in this region faces challenges stemming from unique high-altitude geographic characteristics, a complex terrain, and extreme climatic conditions—including pronounced diurnal temperature fluctuations, high wind speeds, and heavy winter snowfall. Additionally, traditional site-selection models inadequately address these region-specific environmental constraints. To address these limitations, an integrated framework combining geographic information systems (GIS) and multi-criteria decision-making (MCDM) is proposed in this study. A localized evaluation system is developed, incorporating four novel high-altitude-specific indicators: the average and maximum wind speed and the average and maximum snow depth. Criteria weights are determined through a hybrid approach integrating the analytic hierarchy process (AHP) and the entropy weight method (EWM), while candidate sites are prioritized using the VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) ranking method. The case study results demonstrate that region-specific environmental factors exert a significantly stronger influence on site suitability than traditional solar resource indicators (e.g., direct normal irradiance) under Tibet’s extreme climatic conditions, emphasizing the necessity of localized evaluation frameworks. The proposed methodology not only provides a robust scientific foundation for CSP site selection in high-altitude regions with environmental complexities but also establishes a replicable framework for optimizing multiple trade-offs in renewable energy systems under geographically complex conditions. Full article

Business problems today are complicated and involve considering numerous dimensions to be weighed against each other, leading to opposing goals that must be compromised on to discover the best solution. Multi-Criteria Decision Making or MCDM plays an essential role in this situation here. MCDM techniques and procedures analyze, score, and select between options that have various conflicting criteria. This systematic review investigates applications of MCDM methods within Management Information Systems (MIS) based on evidence from 40 peer-reviewed articles selected from the Scopus database. Key methods discussed are Analytic Hierarchy Process (AHP), TOPSIS, fuzzy logic-based methods, and Analytic Network Process (ANP). These methods were applied across MIS strategic planning, re-source assignment, risk assessment, and technology selection. The review contributes further by categorizing MCDM application into thematic decision domains, evaluating methodological directions, and mapping the strengths of each method against specific MIS problems. Theoretical guidelines are suggested to align the type of decision with an appropriate MCDM strategy. The study demonstrates how the addition of MCDM enhances MIS capability with data-driven, transparent decision-making power. Implications and directions for future research are presented to guide scholars and practitioners. Full article

This study investigates the impact of Environmental, Social, and Governance (ESG) certifications on the performance of Class A office buildings within Madrid’s Central Business District (CBD). Employing a Multi-Criteria Decision Making (MCDM) methodology, the research evaluates 21 office properties, analyzing the influence of ESG certifications on key performance indicators, including green building certifications, valuation, market perception, and financial outcomes. The findings reveal that ESG-certified buildings demonstrate superior performance, commanding higher valuations, mitigating brown discounts, and achieving increased rental rates, thereby enhancing their investment attractiveness. These results underscore the importance of ESG certifications in the Spanish office market and provide valuable insights for investors, developers, and policymakers navigating the integration of sustainability and commercial real estate. Full article

Total Hip Arthroplasty (THA) is a widely used surgical procedure to restore mobility and reduce pain in patients with hip joint disorders. Implant success and longevity are influenced by the selection of appropriate materials. This study presents a comprehensive literature review based on structured searches in Scopus and Web of Science, focusing on material selection criteria and methods in THA. The inclusion criteria targeted original studies and reviews addressing material properties, selection techniques, and clinical performance. A bibliometric analysis and keyword co-occurrence network were used to highlight major research themes. The review examines traditional materials such as Metal-on-Polyethylene (MoP), as well as advanced options like ceramics, composites, and Functionally Graded Materials (FGMs). Key challenges discussed include aseptic loosening, wear resistance, and stress shielding. Selection methodologies such as Multi-Criteria Decision-Making (MCDM), Weighted Properties Methods (WPM), and computational tools like Ashby charts and CES Selector are analyzed. The findings from international arthroplasty registries show that more than half of implant failures are linked to material-related factors. This study therefore aims to guide material selection processes in THA by aligning clinical performance with biomechanical and biological requirements, supporting improved implant outcomes and long-term surgical success. Future developments should focus on patient-specific solutions and continuous innovation. Full article

This literature review provides a structured quantitative analysis of existing research on the application of machine learning models (MLMs) and multi-criteria decision-making methods (MCDM) in the context of port state control (PSC). The aim of the study is to capture current research trends, identify thematic priorities, and demonstrate how these analytical tools have been used to support decision-making and risk assessment in the maritime domain. Rather than evaluating the effectiveness of individual models, the study focuses on the distribution and frequency of their use and provides insights into the development of methodological approaches in this area. Although several studies suggest that the integration of MLMs and MCDM techniques can improve the objectivity and efficiency of PSC inspections, this report does not provide a comparative assessment of their performance. Instead, it lays the groundwork for future qualitative studies that will assess the practical benefits and challenges of such integration. The findings suggest a fragmented but growing research interest in data-driven approaches to PSC and highlight the potential of advanced analytics to support maritime safety and regulatory compliance. Full article

Sustainability is increasingly prioritized in infrastructure design; however, its integration into the conceptual design phase remains limited, particularly for pedestrian bridges, where structural performance plays a critical role. While existing frameworks address environmental and economic impacts in later stages, they typically fail to incorporate structural performance and sustainability holistically at the outset. To address this gap, this study introduces a quantitative decision-support framework tailored for the conceptual design of footbridges. The methodology integrates five key indicators, Global Warming Potential (GI), Total Cost (TC), Robustness (RO), Inspection (IN), and Maintenance (MA), using a Multi-Criteria Decision Making (MCDM) approach, specifically the Weighted Sum Model (WSM), supported by Pearson correlation analysis, to identify trade-offs and interdependencies among metrics. The framework is tested on two real-world case studies involving steel pedestrian bridges in different urban contexts. The results reveal a strong correlation between inspection and maintenance, suggesting that designs optimized for inspection accessibility can significantly reduce life cycle maintenance efforts and costs. Robustness appears to be largely independent from environmental impact, indicating the potential to improve structural resilience without compromising sustainability. Furthermore, cost–sustainability relationships are shown to be highly context-dependent. The practical implications of these findings are substantial: by offering a structured, data-driven tool for early-stage evaluation, the framework enables engineers, urban planners, and policymakers to make informed design choices that align with long-term sustainability goals. It offers a methodological basis for comparing design options based on quantifiable sustainability and structural metrics, contributing to evidence-based decision making in line with evolving standards for sustainable infrastructure. Full article