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Accepted by: Prof. Ali Emrouznejad In discriminant analysis (DA) and some methods of multicriteria decision analysis (MCDA), we often wish to assign a 'candidate' to one of two or more groups, e.g. 'satisfactory' or 'unsatisfactory'. This requires specifying the characteristics of both groups. However, often we are only able or willing to specify the characteristics of one group, the reference or 'ideal' group. We propose a method for proceeding in this case, using the overlap index. This is shown to be the probability that a random variable could have come from a reference distribution. This article motivates and introduces the index, describes its estimation and computation, and illustrates its use with examples from discriminant analysis and MCDA. Two of these examples, one of choosing soccer players and another of appraising surgeons, involve managerial decisions. The novelty here is the introduction of '1-group discriminant analysis' based on the overlap index, the application to MCDA and the methodology for the computation of the overlap index. [ABSTRACT FROM AUTHOR]

The advancement of the circular bioeconomy in the agri-food system highlights the lack of harmony in relevant conceptual components and frailties in existing solution creation and performance analysis. Thus, the goal of this study is to provide a robust framework that not only promotes circularity designs but also consolidates the varied yet complementary components of the concept in driving a consistent, inclusive, and accountable practice. To achieve this goal, a traditional scientific and gray literature analysis was conducted to establish the relevant components of circular bioeconomy practices, specifically those relevant to solution design and performance monitoring, and the status of their exploration. The identified gaps and recommendations, primarily the missing harmony between stakeholder participation, sustainability assessment, and decision analysis in solution design, were explored in an integrative manner to develop a novel and robust framework termed the circular bioeconomy accounting tool. Following recommendations on circular bioeconomy indicator development, this study also developed a circular bioefficiency index as a performance indicator that allows practitioners to compare circularity solutions through the lens of their capacity to maximize value and minimize environmental impact using weighted efficiency ratios. With the circular bioeconomy gaining exponential traction in the agri-food system and the concept regarded as not always inherently beneficial, this framework is considered timely and relevant for guiding comprehensive and accountable practice and delivering solutions that do not compromise sensitive economic, environmental, and social boundaries. [ABSTRACT FROM AUTHOR]

• Assessing WEF nexus is crucial to ensure food security. • A novel approach is proposed embedding WEF nexus and circularity. • The percentage of circularity for each farm was measured using Circular Flow Tool. • The framework was applied to 30 dairy farms in Galicia (NW Spain). • Considering the whole dairy cooperative the circularity has increased significantly. The Water-Energy-Food (WEF) nexus approach is increasingly being used for supporting a transition to sustainable development, with initiatives involving the concept of circular economy (CE). In the agricultural sector in particular, assessing this nexus is crucial to ensure food security, control the consumption of key resources such as water and energy, as well as measure atmospheric emissions linked to climate change. This manuscript aims to propose a novel approach by coupling the WEF nexus with a circularity indicator, seeking to capture in a single index (the WEF+CEi) both performances in a sample of companies. The novel approach is applied to 30 dairy farms located in Galicia (NW Spain) to benchmark them in a holistic manner. To do this, the WEF nexus of each farm was represented through the following indicators: carbon footprint, water footprint, energy footprint, and food productivity. In addition, the percentage of circularity for each farm, and for the agro-industrial cooperative was measured thanks to the application of a circularity tool in percentage terms. Finally, the WEF+CEi indicator was obtained using the multicriteria mathematical tool of Data Envelopment Analysis (DEA). The results show that without considering the agro-industrial cooperative, the system is 51 % circular. On the other hand, considering the farms and the cooperative, the system goes up to 80 % of circularity. Finally, the proposed approach can support decision-making and provide insights for producers and stakeholders in the area. [ABSTRACT FROM AUTHOR]

Aquatic habitats provide a bridge for influenza transmission among wild and domestic species. However, water sources pose highly variable physicochemical and ecological characteristics that affect avian influenza virus (AIV) stability. Therefore, the risk of survival or transmissibility of AIV in the environment is quite variable and has been understudied. In this study, we determine the risk of waterborne transmission and environmental persistence of AIV in a wild/domestic bird interface in the Central Mexico plateau (North America) during the winter season using a multi-criteria decision analysis (MCDA). A total of 13 eco-epidemiological factors were selected from public-access databases to develop the risk assessment. The MCDA showed that the Atarasquillo wetland presents a higher persistence risk in January. Likewise, most of the backyard poultry farms at this wild-domestic interface present a high persistence risk (50%). Our results suggest that drinking water may represent a more enabling environment for AIV persistence in contrast with wastewater. Moreover, almost all backyard poultry farms evidence a moderate or high risk of waterborne transmission especially farms close to water bodies. The wildlife/domestic bird interface on the Atarasquillo wetland holds eco-epidemiological factors such as the presence of farms in flood-prone areas, the poultry access to outdoor water, and the use of drinking-water troughs among multiple animal species that may enhance waterborne transmission of AIV. These findings highlight the relevance of understanding the influence of multiple factors on AIV ecology for early intervention and long-term control strategies. [ABSTRACT FROM AUTHOR]

In the context of sustainable energy use, multiple criteria are involved in the decision to select the best energy generation projects, as well as its installation location. However, despite the widespread use of decision-making techniques, there is a noticeable gap due to the lack of a systematic process for selecting the best projects for energy transition. This paper evaluates alternatives of photovoltaic panels for energy generation in floating systems and proposes a procedure to select the best project using a multiple-criteria decision analysis. The Entropy method was used to determine the weight of eight criteria, including cost, number of cells, efficiency, area, panel weight, and power characteristics, and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was used to make the selection. A sensitivity analysis was conducted considering different weighing methods. Among the 20 photovoltaic panels analysed, the method proved to be effective in determining the most successful one for installation in floating systems. The chosen panel maintained the best performance in all scenarios tested. This paper provides a systematic approach for selecting the most suitable photovoltaic panel for floating energy systems, contributing to researchers to refine decision-making methodologies and practitioners to optimise project implementation in sustainable energy initiatives. [ABSTRACT FROM AUTHOR]

This study develops a prioritization framework to aid healthcare funding decision making in health technology assessment (HTA) in Australia using a multiple criteria decision analysis (MCDA) approach. MCDA frameworks for HTAs were reviewed through literature survey to identify the initial criteria and levels within each criterion. Key stakeholders and experts were consulted to confirm these criteria and levels. A conjoint analysis using 1000Minds was undertaken with policy makers from the Department of Health to establish ranking criteria and weighting scores. Monte Carlo simulations were used to examine the sensitivity of findings to factors affecting the ranking and weighting scores. The MCDA was then applied to 6 examples of chronic care models or technologies projects to demonstrate the performance of this approach. Five criteria (clinical efficacy/effectiveness, safety and tolerability, severity of the condition, quality/uncertainty, and direct impact on healthcare costs) were consistently ranked highest by healthcare decision makers. Among the criteria, patient-level health outcomes were considered the most important, followed by social and ethical values. The analyses were robust to inform the uncertainty in the parameter. This study has developed an MCDA tool that effectively integrates key priorities for HTA reviews, reflecting the values and preferences of healthcare stakeholders in Australia. Although this tool aims to align the assessment process more closely with health benefits, it also highlights the importance of considering other criteria. • Established knowledge includes prior studies on healthcare funding decision making and some regional pilot studies in Australia, notably in Queensland Health. The existing literature may touch upon multicriteria decision analysis frameworks but may lack a comprehensive examination of Australian policymakers' criteria preferences. • This study unveils the preferences of Australian policymakers, emphasizing "patient-level health outcomes" and "social and ethical values" over cost considerations, providing unique insights into decision-making criteria. • This study also demonstrates the multiple criteria decision analysis framework's practical utility as a transparent and cost-effective decision-aid tool, offering valuable implications for informed healthcare funding decisions and resource allocation. [ABSTRACT FROM AUTHOR]

In the context of sustainable energy use, multiple criteria are involved in the decision to select the best energy generation projects, as well as its installation location. However, despite the widespread use of decision-making techniques, there is a noticeable gap due to the lack of a systematic process for selecting the best projects for energy transition. This paper evaluates alternatives of photovoltaic panels for energy generation in floating systems and proposes a procedure to select the best project using a multiple-criteria decision analysis. The Entropy method was used to determine the weight of eight criteria, including cost, number of cells, efficiency, area, panel weight, and power characteristics, and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was used to make the selection. A sensitivity analysis was conducted considering different weighing methods. Among the 20 photovoltaic panels analysed, the method proved to be effective in determining the most successful one for installation in floating systems. The chosen panel maintained the best performance in all scenarios tested. This paper provides a systematic approach for selecting the most suitable photovoltaic panel for floating energy systems, contributing to researchers to refine decision-making methodologies and practitioners to optimise project implementation in sustainable energy initiatives.

Abstract This article develops a novel decision-oriented framework that strategically deconstructs systems resilience in a way that focuses on systems’ design, capabilities, and management. The framework helps evaluate and compare how system design choices impact system resilience. First, we propose a resilience score based on a piecewise linear approximation to a resilience curve. Using multicriteria decision analysis principles, we score system design alternatives in terms of system-specific capabilities. We estimate the relevance of these capabilities to resilience curve parameters associated with resilience phases. Finally, we interpret the derivatives of resilience with respect to the curve parameter values as the leverage of these parameters. Using multiple levels of weighted sums of the scores, we calculate the first order impact of system design choices first on a proxy for the generic resilience parameters and then on resilience, which allows situational characteristics to be incorporated in their natural terminology while mapping their impact on resilience with a traceable logic. We illustrate the approach by using existing materials to develop an example comparing engineered designs for minimizing post-wildfire flood impacts.

This study explores the main elements causing flooding in Pakistan's Swabi area and finds that elevation, slope, precipitation, and vicinity of rivers all play a major role in flooding occurrences. Low‐lying areas, steeper slopes, intense monsoon rainfall, and proximity to rivers increase vulnerability to floods. Additional factors such as curvature, normalized difference vegetation index (NDVI), topographic wetness index (TWI), land use and land cover (LULC), and soil type exhibit comparatively less impact on flooding. The evaluation of flood risk incorporates nine factors through the AHP procedure, assigning weights that emphasize the importance of rainfall, slope, elevation, and distance to rivers using GIS software. The resulting flood hazard map categorizes the region into high‐, moderate‐, low‐, and very low‐risk zones, with approximately 49.42% identified as high flood risk areas. Evacuation planning designates secure zones, moderate‐risk areas, and high‐risk zones, emphasizing the need for flexible and adaptable routes in response to evolving flood scenarios. The study's comprehensive approach, integrating GIS and AHP, provides valuable insights for effective flood management in the Swabi district, despite limitations related to data quality. The findings contribute to resolving flooding issues and offer a foundation for coordinated actions by authorities and communities in flood‐prone areas. [ABSTRACT FROM AUTHOR]

This research paper proposes a framework utilizing multicriteria tools for optimal site selection of photovoltaic solar farms. A comparative analysis was conducted using three quantitative methods—CRITIC (criteria importance through intercriteria correlation), PCA (principal component analysis), and entropy—to obtain the weights for the selection process. The evaluation considered environmental, demographic, financial, meteorological, and performance system criteria. TOPSIS (technique for order preference by similarity to ideal solution) was employed to rank the alternatives based on their proximity to the ideal positive solution and distance from the ideal negative solution. The capital cities of the seven departments in the Colombian Caribbean region were selected for the assessment, characterized by high annual solar radiation, to evaluate the suitability of the proposed decision-making framework. The results demonstrated that Barranquilla consistently ranked in the top two across all methods, indicating its strong performance. Cartagena, for instance, fluctuated between first and third place, showing some stability but still influenced by the method used. In contrast, Sincelejo consistently ranked among the lowest positions. A sensitivity analysis with equal weight distribution confirmed the top-performing cities, though it also highlighted that the weight assignment method impacted the final rankings. Choosing the appropriate method for weight calculation depended on factors such as the diversity and interdependence of criteria, the availability of reliable data, and the desired sensitivity of the results. For instance, CRITIC captured inter-criteria correlation, while PCA focused on reducing dimensionality, and entropy emphasized the variability of information. [ABSTRACT FROM AUTHOR]

Recognising the urgency of addressing climate change and the imperative to mitigate its effects, the European Union (EU) has embarked on a transformative journey to reshape its energy landscape, with a pronounced emphasis on harnessing renewable energy sources (RESs) and augmenting their contribution to electricity generation. To propel Europe towards sustainable development through its energy transition, EU member states are encouraged to foster collaborative efforts on a European scale, inviting neighbouring countries to participate in joint ventures aimed at leveraging RESs for electricity generation. Consequently, it becomes imperative to evaluate the potential depth of cooperation among these nations, assessing how such partnerships can align with Europe's overarching objectives while fostering mutually beneficial conditions. This paper seeks to undertake a thorough analysis and evaluation of the potential impacts of such cooperation, both in advancing RES objectives and in promoting broader cooperation goals concerning the countries involved. The appropriate methodological framework has been developed, utilising and implementing the fuzzy PROMETHEE multicriteria decision analysis method, to address the problem's multidimensional character, intending to implement an appropriate action plan and promote production from RESs. The methodology has been applied to assess alternative strategies in two case study countries, Morocco and Egypt, while important outcomes have emerged towards the successful implementation of cooperation mechanisms promoting RES. [ABSTRACT FROM AUTHOR]

Vegetables, especially those eaten raw, have been implicated in several foodborne disease outbreaks. Since multiple vegetable matrices and hazards are involved, risk managers have to prioritize those with the greatest impact on public health to design control strategies. In this study, a scientific-based risk ranking of foodborne pathogens transmitted by leafy green vegetables in Argentina was performed. The prioritization process included hazard identification, evaluation criteria identification and definition, criteria weighting, expert survey design and selection and call for experts, hazard score calculation, hazard ranking and variation coefficient, and result analysis. Regression tree analysis determined four risk clusters: high (Cryptosporidum spp., Toxoplasma gondii, Norovirus), moderate (Giardia spp., Listeria spp., Shigella sonnei), low (Shiga toxin-producing Escherichia coli, Ascaris spp., Entamoeba histolytica, Salmonella spp., Rotavirus, Enterovirus) and very low (Campylobacter jejuni, hepatitis A virus and Yersinia pseudotuberculosis). Diseases caused by Norovirus, Cryptosporidium spp. and T. gondii do not require mandatory notification. Neither viruses nor parasites are included as microbiological criteria for foodstuff. The lack of outbreak studies did not allow to accurately identify vegetables as a source of Norovirus disease. Information on listeriosis cases or outbreaks due to vegetable consumption was not available. Shigella spp. was the main responsible for bacterial diarrhea, but it has not been epidemiologically associated with vegetable consumption. The quality of the available information for all hazards studied was very low and low. The implementation of good practice guidelines throughout the entire vegetable production chain could prevent the presence of the identified hazards. The current study allowed the identification of vacancy areas and could help reinforce the need for performing epidemiological studies on foodborne diseases potentially associated with vegetable consumption in Argentina. [ABSTRACT FROM AUTHOR]

This article develops a novel decision-oriented framework that strategically deconstructs systems resilience in a way that focuses on systems' design, capabilities, and management. The framework helps evaluate and compare how system design choices impact system resilience. First, we propose a resilience score based on a piecewise linear approximation to a resilience curve. Using multicriteria decision analysis principles, we score system design alternatives in terms of system-specific capabilities. We estimate the relevance of these capabilities to resilience curve parameters associated with resilience phases. Finally, we interpret the derivatives of resilience with respect to the curve parameter values as the leverage of these parameters. Using multiple levels of weighted sums of the scores, we calculate the first order impact of system design choices first on a proxy for the generic resilience parameters and then on resilience, which allows situational characteristics to be incorporated in their natural terminology while mapping their impact on resilience with a traceable logic. We illustrate the approach by using existing materials to develop an example comparing engineered designs for minimizing post-wildfire flood impacts. [ABSTRACT FROM AUTHOR]

Circular supply chains (CSCs) prioritize resource efficiency by reusing, remanufacturing, and recycling materials, offering environmental benefits and competitive advantages. However, they are facing various risks and organizational challenges that hinder their efficiency. To ensure long‐term sustainability, this study identifies the key risks and introduces a prioritization model for risk management in CSC strategies proposing a framework for the risk evaluation based on the set of criteria and prioritization model using a combination of three multicriteria decision‐making (MCDM) methods. The model applies fuzzy Delphi‐based analytical hierarchy process (AHP) method to determine the criteria weights and fuzzy axial distance‐based aggregated measurement (ADAM) method for ranking the alternatives. The findings of this study allow for the identification of the most important risks associated with CSC enabling stakeholders to allocate resources strategically and focus efforts on crucial areas. Results highlight that the most important risks are supply chain complexity, resource availability, and quality and technological challenges. The most important contributions are the identification of the most relevant risks that threaten the resilience and sustainability of CSCs, the establishment of the framework for their evaluation, and the development of a novel hybrid MCDM model for their ranking. These contributions are also the main theoretical implications of the study. On a practical level, it enables organizations to strategically manage risks, standardize risk assessment, and improve their competitive advantage by enhancing resilience, reducing disruptions, and lowering operational costs. [ABSTRACT FROM AUTHOR]

The maintenance of a satisfactory quality of life in rural areas is fundamental for sustainable development. One of the ways to improve quality of life indicators is through the gathering of rural workers in solidarity economy organizations as these enterprises aim to integrate development with economic, social, and environmental sustainability. Because solidarity economy organizations have a robust social purpose, their performance must be evaluated based on both social and financial indicators. The objective of this article is to propose a performance evaluation model for rural solidarity economy enterprises, aiming to support decision making in these enterprises based on multicriteria decision analysis (MCDA), particularly the ELECTRE-TRI methodology. In order to demonstrate the applicability of the developed model and to perform sensitivity analyses, the model was applied to a group of eight family agriculture co-operatives in the southwest state of Paraná, Brazil. All the participating co-ops were considered part of the solidarity economy, and they served 2500 rural producer families across at least 15 municipalities. The results showed the applicability and stability of the model, enabling us to identify the dimensions in which each co-op should concentrate their efforts to improve not only their performance but also the outcomes for the farmers that they serve. Based on these results, organizational and improvement activities can be developed and implemented. This analysis contributes to economic and social indicators by offering improvement strategies for the professionalization and strategic management of RSEEs, thus strengthening these enterprises and, consequently, family agriculture. [ABSTRACT FROM AUTHOR]

This research utilized various data types, including remote sensing (RS), aeromagnetic (AM), vertical electrical sounding (VES), and hydrogeological (HG) information, to create a groundwater potential map (GPM) of the Ogbomoso region in southwestern Nigeria. The lineaments obtained from the RS and AM results were merged to produce the lineament density (LD) map of the Ogbomoso area. One hundred and sixty-five VES data were collected for this study. The Ogbomoso area has a distinct geoelectric sequence that consists of various layers. These include the topsoil, weathered/saprolite, saprock, fractured basement, and fresh basement rock. Eight groundwater conditioning factors (GwCFs) were considered to ensure an accurate assessment of the groundwater potential (GP) in the Ogbomoso area. Stepwise weight assessment ratio analysis (SWARA), a multicriteria decision analysis (MCDA) technique, was used to assign weights to each GwCFs. The given weight was normalized, and a coefficient of coherence was established. SWARA helped characterize GP in the Ogbomoso area into different categories. It was discovered that there is a 0.63-degree correlation between well locations and GPM produced for the Ogbomoso area. This confirms that the SWARA modeling technique is reliable for predicting groundwater potential in any typical basement complex terrain worldwide. [ABSTRACT FROM AUTHOR]

Sustainable Development Goals (SDGs) show the breadth of the concept of sustainability and indicate the changes that are needed to provide a future for next generations. A quantitative approach allows the performance of several countries to be framed to assess the state of progress. This work is based on multicriteria decision analysis (MCDA) in which 58 indicators referring to the period 2018–2020 are considered and the performance of 27 European countries is compared. The MCDA makes it possible to calculate a SDG Index that rewards Sweden with positive results also for the Netherlands, Denmark, and Finland. The overall value is broken down by the three dimensions of sustainability (economic, environmental and social) in which again Sweden excels and has also a leadership position in two macro-goals such as security and energy. In contrast, Denmark prevails in innovative future and Netherlands in waste circularity. The main implications of this work confirm that Europe is proceeding to the SDGs goals in an uneven manner, and therefore, there is a need to identify a program that will see greater cooperation among several countries. In fact, Europe will be united when it pursues together a pragmatic vision of sustainability that goes beyond ideology in order to identify solutions that will benefit more stakeholders. [ABSTRACT FROM AUTHOR]

A holistic approach to decision-making in modern energy systems is vital due to their increase in complexity and interconnectedness. However, decision makers often rely on narrowly-focused strategies, such as economic assessments, for energy system strategy selection. The approach in this paper helps considers various factors such as economic viability, technological feasibility, environmental impact, and social acceptance. By integrating these diverse elements, decision makers can identify more economically feasible, sustainable, and resilient energy strategies. While existing focused approaches are valuable since they provide clear metrics of a potential solution (e.g., an economic measure of profitability), they do not offer the much needed system-as-a-whole understanding. This lack of understanding often leads to selecting suboptimal or unfeasible solutions, which is often discovered much later in the process when a change may not be possible. This paper presents a novel evaluation framework to support holistic decision-making in energy systems. The framework is based on a systems thinking approach, applied through systems engineering principles and model-based systems engineering tools, coupled with a multicriteria decision analysis approach. The systems engineering approach guides the development of feasible solutions for novel energy systems, and the multicriteria decision analysis is used for a systematic evaluation of available strategies and objective selection of the best solution. The proposed framework enables holistic, multidisciplinary, and objective evaluations of solutions and strategies for energy systems, clearly demonstrates the pros and cons of available options, and supports knowledge collection and retention to be used for a different scenario or context. The framework is demonstrated in case study evaluation solutions for a novel energy system of clean hydrogen generation. [ABSTRACT FROM AUTHOR]

One of the most important things to do at the stage of preparing an investment process in the construction business is to develop a few possible solutions and then to choose the variant which best fulfils the expectations of various groups of stakeholders. Making a decision about which variant to select depends on how it satisfies a number of criteria, which in turn reflect the requirements set for the planned investment. The process analysing variant solutions employs multi-criteria analysis methods. In order to make analyses and to identify the importance of measurable and non-measurable criteria, surveys and interviews are carried out to acquire the information on the role of the previously defined criteria. Opinions given by experts tend to be divergent due to differences in education, professional background as well as various professional and private experiences. This article reviews data processing methods, and discusses an example of a procedure, which is part of a more extensive analysis of the route of a planned road. The case presented in this paper focuses on the evaluation of five criteria from the category ‘impact on the natural environment’, which are significant in such development projects. The calculations involved in this assessment proved to be time- and labour-consuming, while raising a number of doubts concerning the stage of data aggregation. Hence, the objective of this study has been to develop a method that will enable more efficient data processing while taking into account all assessments.

A health technology assessment (HTA) does not systematically account for the circumstances and needs of children and youth. To supplement HTA processes, we aimed to develop a child-tailored value assessment framework using a multicriteria decision analysis approach. We constructed a multicriteria-decision-analysis-based model in multiple phases to create the Comprehensive Assessment of Technologies for Child Health (CATCH) framework. Using a modified Delphi process with stakeholders having broad disciplinary and geographic variation (N = 23), we refined previously generated criteria and developed rank-based weights. We established a criterion-pertinent scoring rubric for assessing incremental benefits of new drugs. Three clinicians independently assessed comprehension by pilotscoring 9 drugs. We then validated CATCH for 2 childhood cancer therapies through structured deliberation with an expert panel (N = 10), obtaining individual scores, consensus scores, and verbal feedback. Analyses included descriptive statistics, thematic analysis, exploratory disagreement indices, and sensitivity analysis. The modified Delphi process yielded 10 criteria, based on absolute importance/relevance and agreed importance (median disagreement indices = 0.34): Effectiveness, Child-specific Health-related Quality of Life, Disease Severity, Unmet Need, Therapeutic Safety, Equity, Family Impacts, Life-course Development, Rarity, and Fair Share of Life. Pilot scoring resulted in adjusted criteria definitions and more precise score-scaling guidelines. Validation panelists endorsed the framework's key modifiers of value. Modes of their individual prescores aligned closely with deliberative consensus scores. We iteratively developed a value assessment framework that captures dimensions of child-specific health and nonhealth gains. CATCH could improve the richness and relevance of HTA decision making for children in Canada and comparable health systems. • Health technology assessment (HTA) methods for child health technologies are challenged by evidentiary limitations and incomplete consideration of the unique biological and social circumstances and needs of children and youth. Multicriteria decision analysis has emerged as an HTA tool for explicitly considering nonconventional values. • This article presents novel child-specific value assessment criteria based in societal preferences, which reflect the importance of family impacts and long-term flourishing of children beyond immediate health gains obtained through treatment. • A child-tailored multicriteria decision analysis approach facilitating HTA deliberations may broaden the normative lens through which child health technologies are evaluated, contributing to more comprehensive and relevant decision making. [ABSTRACT FROM AUTHOR]

This study propose a framework for integrating Multi-Criteria Decision Analysis (MCDA) and Structure Time Series (STS) prediction for multivariate operational risk assessment often with highly dynamic risk determinants. In particular, by utilizing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) as an MCDA method, the framework is able to prioritize risk determinants according to their inherent uncertainties' impacts on their respective operational objectives, and by employing Seasonal Autoregressive Integrated Moving Average (SARIMA) as an STS technique, the framework emphasizes real-time knowledge utilization for iteratively reducing uncertainty. By integrating SARIMA and TOPSIS, the framework aims to construct a multivariate operational risk assessment profile that is prioritized and continuously updated by the latest data and knowledge. Based on the proposed framework, the study constructs a mathematical model coded in Python to perform an empirical assessment of 161 countries' operational risk using real-time data from the Armed Conflict Location & Event Data Project's. A comprehensive analysis of the model's functionality, quality, and sensitivity based on the assessment result is provided. Conclusions and limitations are also discussed, highlighting the model's theoretical novelty and practical implications. [ABSTRACT FROM AUTHOR]

Sustainable development monitoring reveals the extent to which local and national territories are progressing towards sustainability goals. This study considered 105 indicators associated with the Equitable and Sustainable Wellbeing (BES) framework and 139 indicators associated with the Sustainable Development Goals (SDGs), using multicriteria decision analysis (MCDA) and cluster analysis to compare regional performance across the Italian territory in 2022. At the SDG level, Lombardia exhibited the highest performance, while the provinces of Trento and Bolzano led at the BES level. The results were further analyzed with respect to geographic macro-areas and the three dimensions of sustainability, via separate cluster analyses comparing the BES and SDG results. Northeast regions emerged as the top performers, and comparable performance was shown by regions in the center and northwest. The development of a sustainable innovation model, alongside territorial cooperation and synergy between regional specificities, may generate competitive advantages, especially when combined with resources and skills with an international profile. [ABSTRACT FROM AUTHOR]

The world has been facing an increase in various natural hazards. The coastal regions are recognized as one of the most vulnerable due to high population pressure and climate change intensity. Mediterranean countries have one of the most burnable ecosystems in the world, one of the most exposed to pluvial floods, and have the highest erosion rates within the EU. Therefore, the aim of this study was to develop the first multihazard susceptibility model in Croatia for the Sali settlement (island of Dugi otok). The creation of a multi-hazard susceptibility model (MHSM) combined the application of geospatial technology (GST) with a local perception survey. The methodology consisted of two main steps: (1) creating individual hazard susceptibility models (soil erosion, wildfires, pluvial floods), and (2) overall hazard susceptibility modeling. Multicriterial GIS analyses and the Analytical Hierarchy Process were used to create individual hazard models. Criteria used (32) to create models are derived from very-high-resolution (VHR) models. Two versions of MHSM are created: 1) all criteria with equal weighting coefficients and 2) weight coefficients determined based on public perception. According to MHSM 1, most of the research (58%) area is moderately susceptible to multiple hazards. Highly and very highly susceptible areas are 27% of the drainage basin and are mostly located near roads and houses. MHSM 2 reveals similar results to MHSM 1. The public perceives that the research area is the most susceptible to wildfires. The wildfire ignition risk is ranked as moderate (3.00) with a standard deviation of 1.16. Pluvial flood risk is ranked low (2.78), with a standard deviation of 1.15. The risk of soil is most inferior (2.24) with a standard deviation of 0.91. The the most significant difference between public perception and the GIS-MCDA model of hazard susceptibility is related to soil erosion. However, the accuracy of the soil erosion model was confirmed by ROC curves based on recent traces of soil erosion in the research area. The proposed methodological framework of multi-hazard susceptibility modeling can be applied, with minor modifications, to other Mediterranean countries. [ABSTRACT FROM AUTHOR]

The present study presents a hybrid approach to the evaluation of decision-making in the context of sustainable development, combining the methods of Multicriteria Decision Analysis (MCDA) Combined Compromise Solution (CoCoSo) and Simple Aggregation of Preferences Expressed by Ordinal Vectors – Principal Components (SAPEVO-PC). The objective was to create a ranking of 153 countries, considering 14 essential criteria in the environmental, social, and economic dimensions. The methodology employed allows an integrated analysis of these criteria, reflecting the concept of Triple Bottom Line. The results revealed Japan, Sweden, and Finland as the best-positioned countries, indicating the effectiveness of their sustainable policies and practices. The hybrid approach of the above methods offered a robust tool for complex analysis and decision-making with a relatively large number of alternatives and criteria. [ABSTRACT FROM AUTHOR]

Complex environments, conflicting criteria, uncertainties, and inaccurate information are common in many real-world decision problems. The Multicriteria Decision Analysis (MCDA) methodology plays a significant role in making decision-making processes more rational, efficient, and effective. In the military sphere, the Armed Forces of several countries have used MCDA methods to select operational means—means of transportation—that the Armed Forces have to carry out operations on the battlefield or in various operational scenarios, contributing to a more robust and informed approach to decision-making. This article aims to present a review of the literature on the main applications of MCDA in the selection of operative means. The methodology includes a bibliometric study and a bibliographic review of documents from the Scopus and Web of Science databases. The bibliometric study identified the types of documents, year of publication, H and G indexes of the most relevant journals and authors, authors' publications, affiliation, clusters of keywords, area of knowledge, country, and main applications of the MCDA Methods in this area of research. Through this methodology, it was possible to identify that the Analytic Hierarchy Process (AHP) is the most applied MCDA method in the research area. [ABSTRACT FROM AUTHOR]

The current study aims at GIS-based multicriteria decision analysis to generate a landslide-susceptible map from Baramulla to Uri Road segment along NH-1, Kashmir Himalaya, India. The landslide causative factors examined to generate our AHP matrix are slope gradient, elevation, slope aspect, curvature, distance to drainage, distance to roads, distance to lineaments, geology, land use/land cover, and Rainfall. The study mapped and identified the active landslides along NH-1 through extensive field investigations and other secondary data sources. The landslide events were dominated by rockfall and debris slides. Based on their importance in landslide occurrences, the thematic layers were given relative relevance scores using Saaty's scale. Besides, the Analytic Hierarchy Process was employed to normalize the relative weights and attributes of the various thematic layers. In addition, all thematic data layers were combined using a weighted linear approach to generate the landslide susceptibility map. Furthermore, the resultant landslide susceptibility map was classed into five categories viz., very high (24.18%), high (30.24%), medium (28.61%), low (15.28%), and very low (1.69%). The study reveals that 54.42% of the area falls under the high and very high susceptible zones. Likewise, 78.9% of overall model accuracy of final landslide susceptible zonation map was computed using the area under curve method. Moreover, this study would aid infrastructural, geo-environmental, and landslide hazard planning in the studied region. [ABSTRACT FROM AUTHOR]

In many West African countries, ongoing rapid urbanization urges reliable and proactive land use plans for sustainability purposes, which hinges on a complete assessment of land suitability. GIS-based multi-criteria decision analysis (GIS-MCDA) is one of the most widely applied techniques in land-use suitability analysis. It is pivotal that planners and analysts in the developing world have adequate support in conducting such analysis. To lower the financial and technological barriers, a new free and open-source software (FOSS) for GIS-MCDA is developed, called PyLUSATQ. It is designed as a QGIS plugin following a tight-coupling integration strategy, where analytic tools for GIS-based suitability analysis and MCDA are interconnected and seamlessly integrated into QGIS's processing framework. With this implementation, users can create customized models with the PyLUSATQ tools using QGIS's Graphical Modeler to automate the workflow for suitability analysis. PyLUSATQ is the first of its kind amongst all plugins published on the QGIS Python Plugin Repository, offering a range of tools for GIS-MCDA within the context of land use planning. To demonstrate its practical application, we created two 2050 future land-use scenarios in the Ashanti Region of Ghana. The first scenario depicts a "business-as-usual" model, whereas the second shows an "alternative" scenario if a higher development density was adopted. Comparisons of such scenarios provide evidential support for making informed decisions on land-use policies. Additionally, the methodology introduced here is easily replicable for developing new QGIS plugins based on third-party Python libraries. [ABSTRACT FROM AUTHOR]

This research investigates the optimal integration of Blockchain Technology (BT) in Supply Chain Management (SCM) within Chile's maritime ports. Utilizing fuzzy Logarithmic Methodology of Additive Weights (LMAW) and Double Normalization-based Multiple Aggregation Methods (DNMA), the study systematically identifies, prioritizes, and ranks key factors influencing BT adoption in SCM. The study's findings highlight crucial factors like enhanced transaction security, good supply chain practices, and risk management. Furthermore, it ranks the application of ports as prime candidates for BT integration. The research contributes theoretically by developing a hybrid model combining MCDA methods, and practically by guiding the strategic application of BT in the maritime logistics sector, aligning with the principles of Industry 5.0. This paper presents a novel approach that explores the utilization of BT in maritime supply chain management, incorporating MCDA in a vague environment. The research gap of this study lies in defining new contexts in both theoretical and practical literature reviews for extending the use of BT in SCM in the ports of Chile, according to Industry 5.0, to increase the efficiency and effectiveness of all aspects of operations in these places. The contribution of this research is applying hybrid MCDA methods in an uncertain environment to assist decision-makers (DMs) in better implementing BT in SCM in Chilean ports, according to Industry 5.0. [ABSTRACT FROM AUTHOR]

• A risk analysis interface is developed to assess unmovable cultural heritage. • It includes the asset risk evaluation cards, factsheets, and multicriteria model. • The results are integrated to obtain a risk index for fire, earthquake, and flood. • A comparative assessment of two unmovable cultural assets is performed. • The interface can support the implementation of actions pre and post-events. The present article illustrates the application of the Risk Analysis Interface (RAI), which was developed within the European project ResCult. This assessment model is focused on the risk evaluation of immovable cultural assets and their different components, that need to be preserved and managed in case of extreme events. In detail, this article describes the application of this risk assessment model to the two selected pilot case studies of the project, the Church of Santa Maria dei Miracoli in Venice and the Convent of San Nicola in Tolentino (Italy). This article highlights the application procedure and the results obtained by its implementation in the two pilot case studies. The focus of this article is underlying and explaining in-depth the functioning of the specific evaluation tools, to underline their suitability to be applied in ex-ante, in-itinere, and ex-post phase of a disaster occurrence. The outcome of this article is providing information about how applying the RAI developed within the ResCult project. [ABSTRACT FROM AUTHOR]

Groundwater resources are depleting worldwide owing to climate change and exponential rise in population. In order to manage groundwater resources, consideration must be given to availability of the groundwater and the functioning of the aquifer system. In this regard, the present study aims to explore groundwater potential zones for Guercif, Morocco for highlighting the importance of groundwater resources management. The groundwater potential zones are investigated using multicriteria decision analysis technique in GIS software from perspectives of slope, drainage density, land use landcover, geology, soil type and groundwater levels. As per results, poor groundwater potential zones in the study area were minimum (about 1 km²) followed by excellent (257 km²), fair (632 km²), moderate (2710 km²) and good (6064 km²) groundwater potential zones, respectively. Watershed of the study area has good groundwater potential zones of about 62.75% whereas only 0.01% falls in poor groundwater potential zones. The current research concluded that estimating the groundwater potential zones using GIS and RS remote sensing techniques could saves time and money as compared to the conventional methods. The study is recommended for decisions making and managing the groundwater resources for betterment of the region in future. Therefore, the study provides critical insights for public and government sectors to understand the potential zones for sustainable groundwater utilization and management. [ABSTRACT FROM AUTHOR]

The issue of criteria interactions has been well addressed in multicriteria decision analysis research, whereas the interactive effects of alternatives on decision results are yet to be further investigated. To provide new insights into the issue of alternative interactions, we propose a novel approach for measuring alternative interactions by using the λ-capacity, Choquet integral, and criteria interactions. With the notion of alternative interactions being reflected and measured by criteria interactions, the approach first develops an absolute interaction index and a relative interaction index to objectively measure the degree of interactive effects between alternatives under different decision contexts. It then testifies the impact of criteria interactions on alternative interactions. To examine the effectiveness and applicability of the approach, an empirical study on city environmental performance evaluation is conducted. The empirical results show that the interaction between cities as alternatives provides valuable insights into city planning for developing effective city alliance forms. [ABSTRACT FROM AUTHOR]

Many primate species are threatened by the pet trade, and rehabilitated monkeys require suitable habitats for release back into the wild. The process of identifying suitable release sites involves finding areas with adequate resources and minimizing negative impacts on resident species and human populations. To address this challenge, this study was designed to identify and map suitable areas for the reintroduction of bearded capuchin monkeys (Sapajus libidinosus) into the Caatinga biome in northeastern Brazil. We used a multicriteria decision analysis (MCDA) to identify suitable release areas. Using a species distribution model, we located suitable habitats for seven species of vegetation that are vital resources during the dry season: Syagrus romanzoffiana, Attalea speciosa, Syagrus oleracea, Commiphora leptophloeos, Manihot epruinosa, Pilosocereus pachycladus, and Tacinga inamoena. We then created an MCDA by using vegetation suitability, water availability, proximity to protected areas, and distance from roads and cities as key variables. To increase accessibility, we coded the results into a Google Earth Engine app, allowing for easy and free access to researchers and others interested in capuchin monkey conservation. The resulting suitability maps cover the entire Caatinga biome, providing a valuable tool for conservation efforts by simplifying the initial step of locating potential release sites. This study demonstrates the application of geospatial tools in mapping suitable habitats for the translocation and release of rehabilitated primates at a time when biodiversity loss, the exotic pet trade, land use change, and climate change are threatening nonhuman primates worldwide. [ABSTRACT FROM AUTHOR]

Indoor paths conveyed to pedestrians should align with their spatial cognition for a successful wayfinding experience. In this respect, indoor paths and navigation patterns of pedestrians should be geometrically similar. In this study, four navigation networks frequently used in the literature were created for the study area. Then, various geometric similarity measures were calculated for the indoor paths and navigation patterns of the pedestrians. The geometric similarity measures were weighted with the Fuzzy Analytical Hierarchy Process (FAHP) method, and the indoor paths and the navigation patterns of pedestrians were compared with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method in terms of geometric similarity. According to the findings of the experimental study, the Middle Point Relation Structure Segment Entrance (MPRSSE) navigation network was found to be the most similar to navigation patterns of pedestrians for the study area. The MPRSSE navigation network was followed by the Medial Axis Transform (MAT) based navigation network and the Grid based navigation network, respectively. The visibility partitioning-based Universal Circulation Network (UCN) navigation network, which was found to be the most suitable for path length and number of turns criteria in the literature, fell behind in terms of geometric similarity. [ABSTRACT FROM AUTHOR]

The blockchain has been proposed for use in various applications in the energy field. Although the blockchain has technical strengths, several obstacles affect the application of the technology in energy services. The scope of this study is to highlight and prioritise the most important barriers to such applications. The first step in this direction is specifying the potential areas of the implementation of blockchain technology in the energy sector. Two useful tools for market analysis were used: Political, Economic, Social, Technological, Legal and Environmental, PESTLE Analysis, and Strengths, Weaknesses, Opportunities and Threats, SWOT Analysis, which examine external and internal factors, respectively. Thus, a list of the most important elements hindering the incorporation of the blockchain in the energy sector was extracted. The detected barriers were classified and ranked by energy and IT experts using the multicriteria method, "Analytical Hierarchy Process for Group Decision Making". The results reveal that legal barriers relating to the complexities of deficiencies of regulations are the most significant, while technological barriers, especially those related to security issues, are also important. Sociopolitical barriers related mainly to lack of trust in blockchain, as well as economic concerns such as high upfront costs, are less influential but should still be considered. The conclusions of the conducted research have the potential to guide market actors in their endeavours to modernise energy systems through the use of the blockchain, assisting them in designing the most appropriate market strategies. [ABSTRACT FROM AUTHOR]

This article develops a mechanism for automatically classifying rewarded collaboration proposals. The research's purpose is to increase transparency in the rewarded collaboration process, thereby inviting more collaboration proposals, to aid in the fight against criminal organizations. The research focuses on critical facets of the public security system and of the organized crime in Brazil. Through rewarded collaboration, a new approach to plea bargaining is achieved that helps detect, disrupt, and ultimately dismantle illicit operations. This multi-criteria approach enables the consideration of the interests of detainees, the priorities of police institutions, and the perspective of the community. This approach results in the formation of a holistic understanding of the issue, taking into account the costs and benefits to society of punishing defendants whose guilt can be established. Composition of Probabilistic Preferences Trichotomic is the multi-criteria method employed to take imprecision into consideration while performing classification into predetermined classes. It enables the evaluation of each proposal independently. This boosts the system's objectivity and consequently its attractiveness. Taking the interaction between the criteria into consideration, the analysis naturally applies to any number of evaluation criteria and individuals involved in the investigated crimes. Novel forms of interaction modeling are compared in practical instances. [ABSTRACT FROM AUTHOR]

Moving towards horizontal expansion in the vast barren lands to alleviate overpopulation along the Nile River is imperative to Egypt’s 2030 sustainable development strategy. Accordingly, a mega reclamation project was advocated with a key goal of achieving food self-sufficiency. Solar-powered groundwater pumping system was adopted as the main water supply. Planning efforts are therefore inevitable to help locate the most favourable sites for such extensive cultivation activities. Herein, a multicriteria decision analysis was conducted to facilitate the zoning of potential rural communities across the northern portions of the Western Desert of Egypt. For this purpose, data of groundwater exploration, soil characterization, terrestrial accessibility, insolation intensity, and terrain information were fused to produce a high-resolution suitability map. The analytical hierarchy process approach was adopted to set the weighted importance of adopted criteria. The study area was categorized into Best, Good, Moderate, Fair, Poor, and Restricted classes at 1.7%, 13%, 42.6%, 26%, 10%, and 3%, respectively, of the entire region, while the constrained plots were masked out. The implemented and proposed wells fields within the underway national rural development project extend over agriculturally suitable pixels affirming the validity of the developed geospatial model. About 1.5 million ha, representing 7.2% of the undeveloped area, were found to be highly suitable for future expansion of agribusiness activities. The generated priority map will assist the decision-makers in the planning procedures for ongoing reclamation activities throughout Egypt.

Abstract Child health is an important public health issue in China and the Chinese government always attached great importance to child health care. With the implementation of a series of medical and health reforms in China in recent decades, the status of child health improved year by year. Objectives This study aims to comprehensively evaluate if the measures implemented in the medical and health reforms effectively promoted the development of Chinese child health care in recent years and provide theoretical support for future decision-making on the policies of child health care in China. Methods A total of six indicators were selected from the China Health Statistics Yearbook. Based on the multi-criteria decision analysis (MCDA) algorithm, three different evaluation methods were applied in the study, which are the weighted technique for order preference by similarity to an ideal solution (TOPSIS) method, the weighted rank-sum ratio (RSR) method, and the fuzzy comprehensive evaluation (FCE). Each indicator's weight was calculated by the entropy weight methods objectively. The sensitivity analysis was conducted to validate the stability and accuracy of the rank results. Results The results indicated that the rank values of each year’s child health care calculated by the different evaluation methods were not exactly the same, but the overall trend is consistent which is that child health care in China improved year by year from 2000 to 2020. The top 5 were ranked from 2016-2020 and the bottom 5 were ranked from 2000-2004. Conclusions The results indicated that the policies and measures implemented in the medical and health reforms, as well as improved sanitation conditions, availability of healthy food and water, etc., have jointly promoted the development of child health care in China in the past 20 years, providing a scientific theoretical basis for future policy-making to promote child health care.