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Financial institutions employ credit rating systems to classify new borrowers, set loan terms, and determine collateral requirements. Small and medium-sized businesses (SMEs) are frequently found to be unorganised when it comes to financial data management. Credit risk assessment using unstructured financial data is multifaceted for financial institutions. Most extant credit rating systems are data-intensive and have been criticised for breaching their data distribution and structural assumptions. Such approaches may struggle to estimate SME's credit ratings accurately with sparse and missing data. To address the finance gap for SMEs, this study extends the application of expert systems by proposing a multi-criteria credit rating system. The proposed method utilises existing fuzzy-BWM to determine the weight of criteria and a newly proposed fuzzy-TOPSIS-Sort-C approach to classify SMEs according to their characteristic profiles. The suggested decision support system is expert-driven and built on sparse financial and non-financial data. BWM and TOPSIS were integrated with fuzzy set theory to overcome uncertainty when making decisions. This paper extends the prior TOPSIS-Sort-C method to fuzzy TOPSIS-Sort-C as a theoretical contribution. The suggested system efficacy is demonstrated by a case study that compares it with a commercial rating model using real-world data. The system performs with considerable effectiveness and a true positive rate when applied to credit rating. It could assist financial institutions in identifying potential SMEs for lending. [ABSTRACT FROM AUTHOR]

Using a multi-criteria decision support method (WASPAS) to analyze and rank alternatives, this article proposes a method to assist in the selection of helicopter models that are the most suitable for police air activity in the State of Rio de Janeiro. A robust technical basis for defining the essential requirements of an aircraft is established, and solutions that can ensure the effective and safe execution of missions are indicated. Helicopter models were evaluated by considering predefined criteria, and the weights of these criteria were attributed using a questionnaire that was administered to pilots and aerostatic operators of Public Air Units (UAP) in several states of the federation. As a result of the evaluation of the 15 helicopter models used by police services in the State of Rio de Janeiro, the modeling with the WASPAS method ranked the Sikorsky UH-60 (Black Hawk) model in first place, the Leonardo AW 139 model in second place, and the Bell 412 model in third place. Based on the available data, we suggest that a comparative study integrating the Entropy and CRITIC methods be conducted to measure the weights of the criteria associated with the application of other multi-criteria techniques, such as COMET, MACAB, SPOTIS, VIKOR, SAPEVO, and PROMETHEE. [ABSTRACT FROM AUTHOR]

In Poland, there is a high ratio of private transport and unfavorable patterns of daily commuting. These patterns can be changed by introducing comfortable and eco-friendly vehicles, such as e-scooters and e-bikes. At the same time, the development of the e-micromobility-based vehicle sharing services market is developing. The aim of the article is to analyze selected e-scooters available on the Polish market and to identify the most useful vehicles from two opposing perspectives, i.e., the potential customer and owner of the vehicle sharing system. The PROSA GDSS (PROMETHEE for Sustainability Assessment—Group Decision Support System) method and the graphical representation of GAIA (Geometrical Analysis for Interactive Assistance) were used to search for a compromise and balance between the needs of the indicated stakeholders. The results of the methods used were compared with the results of the PROMETHEE GDSS method, which does not take into account the balance between the stakeholders and allows for a strong compensation of the assessments of decision makers. The conducted research allowed indicating the optimal e-scooter to meet the needs of both decision makers, and it is the JEEP 2xe Urban Camou. Both the sensitivity analysis and the solution obtained with the use of the PROMETHEE GDSS method confirmed that it is the optimal alternative, the least sensitive to changes in criteria weights and changes in the decision makers' compensation coefficients. [ABSTRACT FROM AUTHOR]

The Brazilian Federal Highway Patrol is an organ of public administration with the constitutional mission to carry out the extensive patrolling of federal highways. Stress and physical and emotional exhaustion are constant, causing illnesses along with frustration, demotivation, and depression. The objective of this research is the development of a self-evaluation model of performance for the Federal Highway Patrols, using their perceptions to enhance their motivation at work considering the factors under their control. The constructivist multi-criteria decision aid (MCDA-C) methodology was used to elaborate the model. The proposed model identifies, establishes, and structures a process to measure the performance of patrol officers on the relevant aspects that they can manage, to guide their decisions toward the desired consequences, thus regulating their stress levels. [ABSTRACT FROM AUTHOR]

This paper considers the problem of finding suitable sites for wind farms in a region of Catalonia (Spain). The evaluation criteria are structured into a hierarchy that identifies several intermediate sub-goals dealing with different points of view. Therefore, the recent ELECTRE-III-H hierarchical multi-criteria analysis method is proposed as a good solution to help decision-makers. This method establishes an order among the set of possible sites for the wind farms for each sub-goal. ELECTRE-III-H aggregates these orders into an overall order using different parameters. The procedure is based on the construction and exploitation of a pairwise outranking relation, following the principles of concordance (i.e. majority rule) and discordance (i.e. respect for the minority opinions). This paper makes two main contributions. First, it contributes to the ELECTRE-III-H method by studying its mathematical properties for the construction of outranking relations. Second, the case study is solved and its results show that we can effectively represent and manage the overall influence of the various criteria on the global result at different levels of the hierarchy. The paper compares different scenarios with strict, normal, and optimistic preference, indifference and veto thresholds. Results show that the best site differs for technical, economic, environmental, and social intermediate criteria. Therefore, the best overall solution changes depending on the preference and veto thresholds fixed at the intermediate level of the hierarchy. [ABSTRACT FROM AUTHOR]

Sustainability is a key word in modern transportation and logistics. It requires not only economic development but also environmental and social actions. The involvement of multiple stakeholders can express different perspectives and interests to achieve the balance between these three pillars. The multi-actor multi-criteria analysis (MAMCA) is a methodology that can include multiple stakeholders in the process of decision-making. It is important in the field of transport and logistic project appraisal, as many projects fail to be implemented because of a lack of support from one or more stakeholders. In MAMCA, multiple stakeholders can use different criteria trees and express their own preferences. At the end of the analysis, the advantages and disadvantages of each of the proposed scenarios are highlighted. Possible consensuses are then being discussed. However, this last step often turns out to be a difficult task. The purpose of this paper is to propose a way to help the facilitator to identify this (these) consensus(es). This will be based on the use of a weight sensitivity analysis model that was recently developed in the context of the PROMETHEE methods and which is based on inverse mixed-integer linear optimization. This approach allows finding the minimum weight modification for each stakeholder in order to improve the position of a given alternative in the individual rankings and, in an ideal case, to the first position of all the rankings simultaneously. This approach is illustrated on two real MAMCA logistic project cases to seek sustainable mobility solutions. [ABSTRACT FROM AUTHOR]

The aim of the paper is to provide support to an evaluation in urban planning, creating a useful approach for the choice of future alternative Operational Plans in Cava De' Tirreni (Salerno). They represent planning tools that are usually formed after public announcements to select the interventions to be implemented in the areas of transformation identified by the general Municipal Urban Plan. A suitable system of territorial indicators to verify the achievement of such goals is also taken into account. With reference to three different urban areas, the evaluation has been carried out by Multi-Criteria Decision Aid (MCDA), using the PROMETHEE (Preference Ranking Organisational Method for Enrichment Evaluation) multi-criteria method and GAIA (Graphical Analysis for Interactive Aid) tool. [ABSTRACT FROM AUTHOR]

Companies have been challenged to attend to multiple objectives and to achieve appropriate decisions facing dichotomies mentioned in literature, such as shareholder versus stakeholder; financial versus non-financial; single versus multiple measures. Since the translation of the sustainable development concept to business by the triple bottom line (TBL), there have been attempts to implement operational approaches. This study proposes a model that helps corporate decision-making considering the TBL framework and a stakeholder view. Multi-criteria decision aid methods are used to generate a sustainability balanced single measure and performance indices. We apply the model to a Brazilian electricity corporation, where the indices are calculated from existing GRI indicators, and the use of the model within the company's strategic plan annual review is demonstrated. The findings suggest that the model has the potential to support informed decisions and the integration of corporate sustainability performance measurement and reporting activities with traditional management control systems. [ABSTRACT FROM AUTHOR]

Background: Health literacy (HL) is low for 40-50 % of the population in developed nations, and is strongly linked to many undesirable health outcomes. Older adults are particularly at risk. The intervention research on health literacy in ageing populations project systematically created a large inventory of HL interventions targeting adults age 50+ , to support practical production of policy and practice guidelines for promoting health literacy in European populations. Methods: We comprehensively surveyed international scientific literature, grey literature and other sources (published 2003+) for implemented HL interventions that involved older adults. Studies were screened for eligibility criteria and further selected for aspects important in European public health policy, including priority diseases, risk factors and vulnerable target groups. Interventions were prioritised using a multiple criteria tool to select final interventions that also featured strong evidence of efficacy and a broad range of strategies. Results: From nearly 7000 written summaries, 1097 met inclusion criteria, of which 233 were chosen for scoring and ranking. Of these, seven had the highest multi-criteria scores. Eight more articles were selected based on rounded criteria including a high multi-criteria score as well as elements of innovation. Final selections were 18 articles describing 15 programmes, which feature strong evidence of efficacy among important diseases or risk factors and vulnerable groups, or that had success with elements of innovation were identified. Most programmes tried to increase skills in communication, self-management and understanding healthcare or lifestyle choices. Conclusions: These programmes have multiple positive attributes which could be used as guidance for developing innovative intervention programmes to trial on European older adults. They provide evidence of efficacy in addressing high priority diseases and risk factors. [ABSTRACT FROM AUTHOR]

Following recent legislations and public policies on solid waste and product take-back, companies in Brazil are now impelled to incorporate reverse logistics practices in their business processes. The Brazilian National Policy of Solid Waste – NPSW, approved in 2010, obligates companies to implement reverse logistics. Considering this, many companies in Brazil have studied the possibility to outsource these activities by engaging third-party reverse logistics providers – 3PRLP. Considering these demands, it is important to define which systematic approaches can be used to select the most suitable 3PRLP. The objective of this article is to identify the main criteria, the systematic methods that can be used in order to select the most appropriate 3PRLP and also propose a framework based in multicriteria decision aid approach to select 3PRLP. Thus, a Systematic Literature Review was carried out and a conceptual framework for decision making in this context using Multicriteria Decision Aid – MCDA modeling was proposed. Therefore, this paper presents two contributions: i) a SLR covering the past decade based on the MCDA experiences in 3PRLP selection, highlighting the main criteria and systematic approaches used; ii) based on this SLR, a proposal for a conceptual methodological framework to help decision makers and researchers in performing a MCDA in the area of 3PRLP selection. [ABSTRACT FROM AUTHOR]

This paper puts forward an integrated model to support the process of classifying projects and project managers (PM) using a multiple criteria decision aid (MCDA) approach and allocating projects according to organizational restrictions through mathematical programming. The model was formulated after reviewing the literature and being guided by the findings of searches; we used a MCDA method for project and PM classification (first stage) and mathematical programming for project allocation (second stage). A practical application of the proposed model was implemented at a Brazilian electric energy company. The results demonstrated that it was possible to classify projects and project managers into definable categories, thereby enabling the process of project allocation to be undertaken more effectively. The project allocation process can be conducted in a systematic and more efficient way. The proposed model can support an organization by allocating its most critical projects to its best qualified and experienced professionals. [ABSTRACT FROM AUTHOR]

This article is about improving non-motorized mobility in central urban areas. Multi-criteria decision aid (MCDA) is the methodological framework used to support two case studies in the city of Campinas, Brazil. The alternatives proposed in the structuring phase are specific to each of the cases and involve incremental solutions for meeting the stakeholders’ expectations. The evaluation shows that the most attractive alternatives are those that require the highest investment in infrastructure. On the other hand, the recommendation indicates the intermediate alternatives. A major benefit of applying the MCDA is the debate and the reflection about the problem throughout the decision-making process. [ABSTRACT FROM AUTHOR]

Highlights: [•] We develop an approach to manage conflict and imperfection of expert judgments represented with belief functions. [•] We assess expert reliability degrees (discount operators) based on multiple criteria using the PROMETHEE method. [•] We discount and combine expert judgments. [Copyright &y& Elsevier]

Abstract: Modern agriculture must meet new challenges such as production of healthy food, adaptation to climate change, protection of natural resources, and conservation of landscape. These challenges require changes in current agricultural systems and therefore, environmentally-friendly agricultural systems must be designed and their sustainability assessed. Over the past several years, various methods have been developed for making such assessments (e.g. the Balancing and Ranking Method, MEACROS, MODAM, the modelling framework of Pacini et al., ROTAT+FarmImages, MASC, and ROTOR) but few studies put forward simple solutions for selecting one method over another. In this paper, we propose a simple guide to distinguish methods one from another. Categories of the guide include the type of systems to assess, the spatial and temporal scales at which systems are assessed, the dimensions of sustainability for which systems are assessed, the type of visualisation for comparing options, the target users, and the ability to generate alternative systems. The guide was developed and tested with a group of farm advisors involved in a three-year project called RotAB, which aimed to assess the sustainability of organic arable farming systems: the advisors looked for a method for sustainability assessment of cropping systems. We presented seven recent assessment methods as well as the guide to advisors. The guide’s key points allowed them to clearly express their requirements: the method they looked for had to evaluate cropping systems and helped advisors to propose new ones; it had to evaluate multiple sustainability criteria that are easily understandable by farmers; indicators had to be scientifically based, without the need for many input data; the method had to be easy to use and produced graphical output that can be discussed with farmers. Finally, the guide helped advisors to choose one of the seven methods (in that case they chose MASC). This guide can help decision-makers distinguish assessment tools from one another using simple categories and choose the one best adapted to their expectations. [Copyright &y& Elsevier]

This paper explores the issue of sustainability at the macro scale employing multi-criteria decision aid (MCDA) methods. The incommensurability of values and the essentially multi-dimensional and dynamic nature of sustainability challenge the use of composite measurement indices. This determined the choice of MCDA methods. Austria was chosen as a case study, due to the wide availability of data, especially on indicators of strong sustainability. The structure of the multi-criteria problem comprised the evolution of different sustainability dimensions over time. The process for selecting criteria included a critical assessment of institutional sustainability agendas (UN, EU and Austrian Government) and theoretical recommendations. After an assessment of MCDA methods, the NAIADE method demonstrated the most suitable properties for sustainability assessment. The application of this outranking approach was undertaken in three separate settings: long-term from 1960 to 2003, medium-term, 1970–1995, and short-term, 1995–2003 with varying numbers of criteria. The response of results to the addition of evaluating criteria and periods was tested. The degree of credibility for accepting preference relations was also employed for sensitivity analysis. According to the results of long-term and medium-term assessments, especially in the weak sustainability setting, sustainable progress is taking place in Austria. In the short term, in the stronger sustainability setting and, especially as the number of criteria increases, more incomparable periods appear and trends are less determined. Moreover, it is shown how results crucially depend on the methodological choices. This is one of the first applications of the multi-criteria tools to the dynamic analysis of sustainability at the macro scale. [Copyright &y& Elsevier]

Integrated sustainability assessment is part of a new paradigm for urban water decision making. Multi-criteria decision aid (MCDA) is an integrative framework used in urban water sustainability assessment, which has a particular focus on utilising stakeholder participation. Here MCDA is reviewed in the context of urban water management used in a decision making framework. Three other commonly used integrated approaches in urban water management (cost-benefit analysis, triple bottom line and integrated assessment) are compared with MCDA. Generic types of shortcomings associated with MCDA are discussed to provide an understanding of MCDA's limitation in urban water management decision making; including 1) preferential independency, 2) double counting and under-counting, and 3) transparency of MCDA methods and results. [ABSTRACT FROM AUTHOR]

Abstract: Each alternative scheme for treating a vehicle at its end of life has its own consequences from a social, environmental, economic and technical point of view. Furthermore, the criteria used to determine these consequences are often contradictory and not equally important. In the presence of multiple conflicting criteria, an optimal alternative scheme never exists. A multiple-criteria decision aid (MCDA) method to aid the Decision Maker (DM) in selecting the best compromise scheme for the management of End-of-Life Vehicles (ELVs) is presented in this paper. The constitution of a set of alternatives schemes, the selection of a list of relevant criteria to evaluate these alternative schemes and the choice of an appropriate management system are also analyzed in this framework. The proposed procedure relies on the PROMETHEE method which belongs to the well-known family of multiple criteria outranking methods. For this purpose, level, linear and Gaussian functions are used as preference functions. [Copyright &y& Elsevier]

In this paper, we propose a method to locate the company’s crucial knowledge for improving the quality of decision making in a design project. It comprises of a preliminary survey regarding the approach that has been carried out at automotive company for identifying the crucial knowledge, aiming at choosing and justifying the necessary investment to capitalize on the knowledge. This method will then be used as basis for a dialogue between the stakeholders involved in the identification of the crucial knowledge developed and/or used in a design project. [ABSTRACT FROM AUTHOR]

A group decision-making approach can be seen as a two stage process. The first stage allows for multi-cirteria evaluation of the alternatives and the second aims at deriving a collective weak ordering from the partial orderings supplied by the members after the first stage. The problem of combining the weak orderings to form a collective ranking is investigated. An axiomatic structure relating to the concept of distance between binary relations is developed. An algorithm for deriving the collective weak ordering is proposed, based on the idea of ranking first the least dominated alternatives. [ABSTRACT FROM AUTHOR]

• Developing an approach that combines different types of uncertainty in decision-making. • Interpretation taking into account the preferences of the society made up of individual users. • Aggregation into the fuzzy form of many theoretically certain data from various sources. • Verification of the approach by solving the decision problem of electric vehicles assessment. • Indication of the relationship between fuzziness, outranking, and stochastic uncertainty. In recent years, a number of legal solutions have been adopted in Poland aimed at reaching the number of 1 million electric cars in use in 2025. Therefore, an important research issue is the assessment of electric vehicles available on the Polish market and the identification of vehicles that meet consumers' expectations to the greatest extent. The assessment of electric vehicles is a multi-criteria issue, characterized by a number of uncertainties related to their operational parameters, as well as the preferences of individual users and, more broadly, the preferences of society. A novelty of the article is the application of the fuzzy multi-criteria decision aid method called NEAT F-PROMETHEE (New Easy Approach To Fuzzy PROMETHEE), combined with the Monte Carlo method and elements of the SMAA (Stochastic Multicriteria Acceptability Analysis) method for the assessment of vehicles under uncertainty conditions. The theoretical contribution of this research therefore includes the synthesis of a fuzzy and stochastic approach to decision-making support, supported by outranking and incomparability relationships. Such a set of approaches to uncertainty makes it possible to improve the accuracy of decision-making, because the approaches indicated verify each other's results. Moreover, the application of the NEAT F-PROMETHEE method has solved the problem of evaluating electric vehicles from the perspective of a single decision-maker, while the combination of NEAT F-PROMETHEE and the stochastic approach has made it possible to simulate preferences of the society. Although there are many uncertainties in the decision-making problem, the approach has allowed to identify almost unambiguously the electric vehicle that is likely to gain the highest acceptance. As a result of the conducted research it was found that the approaches to uncertainty based on fuzzy sets, outranking relations and stochastic analysis complement each other, allowing the decision-maker to conduct a wider analysis of the imprecision of the obtained solution. [ABSTRACT FROM AUTHOR]

In recent years, the dynamic development of renewable energy has been visible all over the world, including Poland. Wind energy is one of the most used renewable energy sources. In Poland, by 2030, it is planned to commission at least six offshore wind farms with a total capacity of 3.8 GW. It is estimated that these investments will increase Poland's GDP by approximately PLN 60 billion and increase tax revenues by PLN 15 billion. Therefore, they could be a strong stimulus for the development of the Polish economy and may be of great importance in recovering from the crisis caused by the economic constraints related to the COVID-19 pandemic. The aim of the article is a multi-criteria evaluation of the investments planned in Poland in offshore wind farms and identification of potentially the most economically effective investments. To account for the uncertainty in this decision problem, a modified fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was used and a comprehensive sensitivity analysis was performed. As a result of the research, a ranking of the considered projects was constructed and the most preferred investments were identified. Moreover, it has been shown that all the investments considered are justified and recommended. [ABSTRACT FROM AUTHOR]

• MCDA application in corporate credit risk and distress prediction is extended. • PROMETHEE II is proposed as a multicriteria evaluation framework for DPMs. • A comparison between statistical and machine learning classifiers is provided. • The effect of corporate governance indicators in developing DPMs are evaluated. • The superiority of machine learning models in predicting distress is demonstrated. Conflicting rankings corresponding to alternative performance criteria and measures are mostly reported in the mono-criterion evaluation of competing distress prediction models (DPMs). To overcome this issue, this study extends the application of the expert system to corporate credit risk and distress prediction through proposing a Multi-criteria Decision Aid (MCDA), namely PROMETHEE II, which provides a multi-criteria evaluation of competing DPMs. In addition, using data on Chinese firms listed on Shanghai and Shenzhen stock exchanges, we perform an exhaustive comparative analysis of the most popular DPMs; namely, statistical, artificial intelligence and machine learning models under both mono-criterion and multi-criteria frameworks. Further, we address two prevailing research questions; namely, "which DPM performs better in predicting distress?" and "will training models with corporate governance indicators (CGIs) enhance the performance of models?"; and discuss our findings. Our multi-criteria ranking suggests that non-parametric DPMs outperform parametric ones, where random forest and bagging CART are among the best machine learning DPMs. Further, models fed with CGIs as features outperform those fed without CGIs. [ABSTRACT FROM AUTHOR]

The paper presents a possibility to use a new PVM-VSI (Preference Vector Method computed in Vector Space of Increments) method in making decisions that demand that different variants should be considered, while being evaluated with respect to different criteria. Hence, knowledge about them is a must, and that knowledge is not necessarily available quantitatively, whereas the very evaluation should be relatively objective; that is, independent from the decision maker's preferences or opinions. The paper presents the use of the PVM-VSI method in support decisions related to urban development—to rank projects submitted for implementation within the framework of a citizen budget. The ranking will make it feasible to determine which of the submitted projects will have the dominant influence on the town's sustainable development, and, subsequently, which ones should be presented to citizens as the better ones out of the projects submitted, and to compare the method mentioned with methods used in similar decision-making problems in the past: Fuzzy AHP (Analytic Hierarchy Process), Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and Fuzzy PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluation). [ABSTRACT FROM AUTHOR]