Este trabalho apresenta e exemplifica a aplicação de metodologia que apoia a seleção e a priorização de um conjunto de dados bibliográficos que represente o estado da arte do assunto pesquisado. O processo envolve a formação de uma base de dados preliminar bruta, seguida da aplicação de uma série de etapas de filtro para a formação de uma base de dados convergente com os objetivos da pesquisa e termina com a priorização desses dados através de um método de apoio à decisão (MAD). O método adotado para exemplificar a aplicação da metodologia foi a Composição Probabilística de Preferências (CPP). A metodologia foi aplicada com sucesso à seleção de artigos em diferentes contextos.

The recruitment of athletes with limited resources is a global problem in professional sports. In US Major League Baseball, the experience of the Oakland Athletics’ general manager in the last decade turned his “Moneyball” model into a synonym of quantitative analysis in the transfer market of baseball players. His strategy focused on hiring players with outstanding technical skills but relatively low market value. This study adapted this model to the framework of a multiple criteria decision aid (MCDA), by selecting undervalued players who have complementary abilities. The novelty here refers to the joint use of four algorithms explored by the composition of probabilistic preferences (CPP) (i.e., ranking, classification, dynamic evaluation and regularity analysis) and their application to soccer player performance evaluation. The new model analysed the recent transfer of a left-back soccer player to Europe. The results indicated 12 opportunities for better investment, among 32 left and right-back players considered. Two years later, the value of the same player was considerably lower. He played only five matches in the 2018–2019 season, without scoring or providing any assists. On the other hand, the players better classified by the CPP-MB model presented higher performances and market values.

Resumo Embora existam muitas abordagens sobre a exposição ocupacional ao ruído, a análise da percepção individual do trabalhador e suas implicações sobre o seu comportamento constituem ainda um tema raramente abordado. Objetivando colaborar em minimizar esta lacuna, fez-se um levantamento do estado da arte das publicações que relacionam às variáveis que estariam associadas à exposição ao risco físico ruído no meio laboral com o uso do equipamento de proteção auditivo. Após, utilizou-se uma amostra de 278 trabalhadores industriais expostos a níveis de pressões sonoras superiores a 80 dB (A) para examinar a relação entre a percepção do ruído ocupacional e o uso do equipamento individual auditivo. A aplicação da técnica de análise fatorial a esses dados permitiu ainda quantificar efeitos diretos e indiretos de um conjunto de fatores sobre o uso do equipamento. Concluiu-se que a percepção da exposição ao risco do ruído pelos trabalhadores é um importante preditor sobre a decisão de uso do equipamento de proteção auditiva.

The main purpose of the present work is to present an application of the probabilisticpreferences composition method to the vendor and carrier selection process in the construction sector of the Southern Region of Rio de Janeiro state, in Brazil. The traditional measures associated with vendor and carrier evaluation are considered in the model and are combined through a preferences composition, which considers the options' uncertainties. In the application, we considered three different suppliers of sand for construction and three different logistics providers, two of them outsourced. Our intention was to verify if outsourcing can be considered a better solution, as proposed by many authors. The results show thatoutsourcing is the best option for different probabilistic composition points of view as well as when the overall evaluation is obtained by average composition.

Airlift operations are vital to support contingency plans during the major humanitarian and disaster relief (HDR) events. The access to disaster zones is often limited by unsafe conditions, poor road infrastructure, and lack of commercial air services. To overcome these limitations, the development of larger planes has allowed bulkier equipment and larger quantities of supplies to be transported by fewer flights. Embraer developed the KC-390 airplane to carry out logistics support and HDR missions. Multinational HDR events usually call for a wide variety of aircraft. The comparison between the KC-390 and the C-130 gains relevance under these circumstances, where the two will be competing for use in emergency support. This article aims to provide support for the allocation of the appropriate aircraft to each mission, by quantifying the advantages (and possible disadvantages) of the KC-390 compared with the C-130 based on the relative difference of their technical performance. Consolidated scores are established through the probabilistic composition of preferences by combining preference probabilities using weighted sums. The weights are calculated based on the experience of pilots applying the analytical hierarchical process. Among the types of missions analyzed, search and rescue present the highest difference in technical performance, in favor of the KC-390.

The aim of this article is to demonstrate the advantages of the Composition of Probabilistic Preferences method in multicriteria problems with data from Likert scales. Multicriteria decision aids require a database as a decision matrix, in which two or more alternatives are evaluated according to two or more variables selected as decision criteria. Several problems of this nature use measures by Likert scales. Depending on the method, parameters from these data (e.g., means, modes or medians) are required for calculations. This parameterization of data in ordinal scales has fueled controversy for decades between authors who favor mathematical/statistical rigor and argue against the procedure, stating that ordinal scales should not be parameterized, and scientists from other areas who have shown gains from the process that compensates for this relaxation. The Composition of Probabilistic Preferences can allay the protests raised and obtain more accurate results than descriptive statistics or parametric models can bring. The proposed algorithm in R-code involves the use of probabilities with empirical distributions and fitting histograms of data measured by Likert scales. Two case studies with simulated datasets having peculiar characteristics and a real case illustrate the advantages of the Composition of Probabilistic Preferences.