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Copyright of Revista Espacios is the property of Talleres de Impresos Oma and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Selecting a supplier for highly technical and expensive equipment as a weather radar is a very demanding process and a critical management task for procurement team. For such problems, the use of multiple criteria analysis is welcome. This paper introduces a decision aid model for weather radar supplier selection using a multi-attribute approach for public purchase procedures. As a model application, we developed the framework on a real public procurement to expand the weather radar network in Brazil, where two attributes were in conflict (cost and technical). The proposed model was demonstrated to be very useful in understanding the trade-off between cost and technical attributes, based on the stakeholders' preferences. The model also supported the decision-maker in the negotiation process to receive better commercial or technical proposals from the buyers' perspective. Based on these findings, it is advocated that for highly specialised equipment, a single attribute method centred on the lowest-cost bid is no longer supportive and robust enough in contemporary supplier selection. Modelling a multi-attribute decision process could also be a guide to improve interaction with expert and management teams in future weather radar selection evaluations. [ABSTRACT FROM AUTHOR]

Literature supports that buyers can influence suppliers to adopt sustainable practices. Much of this literature, however, is descriptive and takes only the perspective of a buyer trying to diffuse sustainability into its supply base. Alternatively, this study augments the literature through the development of a prescriptive mathematical model that maximizes a supplier's expected revenue from making a bid to a large buyer, inclusive of a sustainability criterion. Specifically, the model uses decision theory to determine an optimal level of sustainability to integrate into a bid to balance economic vs. sustainable trade‐offs based on perceived buyer preference. To illustrate the model's utility, it is then applied to a rich scenario, using data from an industrial supplier bidding for a contract to distribute a fuel additive in Brazil by balancing the trade‐off between decreased carbon emissions and increased distribution cost. A sensitivity analysis is then performed to illustrate how different forms of the buyer's objective function would influence the propagation of sustainability into optimal supplier bids. The research thereby adds to our understanding of sustainable sourcing by prescriptively modeling both buyer and supplier perspectives, when analyzing how buyer preferences can drive supplier behavior. [ABSTRACT FROM AUTHOR]

Background: Early detection of Mycobacterium leprae is a key strategy for disrupting the transmission chain of leprosy and preventing the potential onset of physical disabilities. Clinical diagnosis is essential, but some of the presented symptoms may go unnoticed, even by specialists. In areas of greater endemicity, serological and molecular tests have been performed and analyzed separately for the follow-up of household contacts, who are at high risk of developing the disease. The accuracy of these tests is still debated, and it is necessary to make them more reliable, especially for the identification of cases of leprosy between contacts. We proposed an integrated analysis of molecular and serological methods using artificial intelligence by the random forest (RF) algorithm to better diagnose and predict new cases of leprosy. Methods: The study was developed in Governador Valadares, Brazil, a hyperendemic region for leprosy. A longitudinal study was performed, including new cases diagnosed in 2011 and their respective household contacts, who were followed in 2011, 2012, and 2016. All contacts were diligently evaluated by clinicians from Reference Center for Endemic Diseases (CREDEN-PES) before being classified as asymptomatic. Samples of slit skin smears (SSS) from the earlobe of the patients and household contacts were collected for quantitative polymerase chain reaction (qPCR) of 16S rRNA, and peripheral blood samples were collected for ELISA assays to detect LID-1 and ND-O-LID. Results: The statistical analysis of the tests revealed sensitivity for anti-LID-1 (63.2%), anti-ND-O-LID (57.9%), qPCR SSS (36.8%), and smear microscopy (30.2%). However, the use of RF allowed for an expressive increase in sensitivity in the diagnosis of multibacillary leprosy (90.5%) and especially paucibacillary leprosy (70.6%). It is important to report that the specificity was 92.5%. Conclusion: The proposed model using RF allows for the diagnosis of leprosy with high sensitivity and specificity and the early identification of new cases among household contacts. [ABSTRACT FROM AUTHOR]

Objective: (i) To describe how aligned the 'Choosing Wisely' concept is with the medical culture among Brazilian cardiologists and (ii) to identify predictors for physicians' preference for avoiding wasteful care.Design: Cross-sectional study.Setting: Brazilian Society of Cardiology.Participants: Cardiologists who agree to fill a web questionary.Intervention: A task force of 12 Brazilian cardiologists prepared a list of 13 'do not do' recommendations, which were made available on the Brazilian Society of Cardiology website for affiliates to assign a supported score of 1 to 10 to each recommendation.Main Outcome Measurement: Score average for supporting recommendations.Results: Of 14 579 Brazilian cardiologists, 621 (4.3%) answered the questionnaire. The top recommendation was 'do not perform routine percutaneous coronary intervention in asymptomatic individuals' (mean score = 8.0 ± 2.9) while the one with the lowest support was 'do not use an intra-aortic balloon pump in infarction with cardiogenic shock' (5.8 ± 3.2). None of the 13 recommendations presented a mean grade >9 (strong support); 7 recommendations averaged 7-8 (moderate support) followed by 6 recommendations with an average of 5-7 (modest support). Multivariate analysis independently identified predictors of the score attributed to the top recommendation; being an interventionist and time since graduation were both negatively associated with support.Conclusions: (i) The support of Brazilian cardiologists for the 'Choosing Wisely' concept is modest to moderate, and (ii) older generations and enthusiasm towards the procedure one performs may be factors against the 'Choosing Wisely' philosophy. [ABSTRACT FROM AUTHOR]

Student selection is a complex decision-making process, in which several criteria need to be considered simultaneously. In this paper, we address this problem for a Brazilian university that has created an interdisciplinary degree in which several intermediate selection processes are required during the course, defining the final title degree. The university is currently using an aggregated score based on the performance of a student in the course. However, this method is facing difficulties in selecting the best students, because deficiencies in the way transferred, dropped and quit course credits are accounted for. As a possible alternative for the current method, we developed a hybrid ranking algorithm, called ELECTRE–TOPSIS (E–T). This method combines elements of the ELECTRE family and TOPSIS, two well-known multi-attribute analysis tools, to rank students based on objective criteria. Computational experiments and a case study were conducted to evaluate E–T. The results show that our approach provides quite competitive rankings in comparison with similar methods, through simultaneously eliminating ranking reversal and better balancing the formation time and the academic performance of the evaluated students. [ABSTRACT FROM PUBLISHER]

Purpose The purpose of this paper is to present a hybrid modelling that combines concepts and techniques for scenario building together with a Multi-criteria Decision Aid (MCDA) outranking approach. The paper presents a case to illustrate the proposed methodology.Design/methodology/approach The research method is a qualitative and quantitative mixture and it is presented as a study case. Bibliographic research is used to construct the theoretical framework. There are a number of studies that develop a sensibility analysis in MCDA modelling; however, none of them explore the robustness of the MCDA solution with use of scenarios variation.Findings The methodology allows the criteria that must be taken into account, according to the decision makers’ values and preferences. It is interesting to note that, depending on the scenario, different weights were applied for each criterion, and the performances of alternatives under each criterion has changed as well.Practical implications This need arises in decision problems that are susceptible to the influence of scenario variation.Originality/value This proposal was applied to a real case that has taken into account six alternatives, with a prospective analysis of three scenarios, evaluated by four criteria. The authors use prospective scenarios to choose the criterion weights and alternatives evaluation. [ABSTRACT FROM AUTHOR]

The strategies used to perform the transportation of agricultural commodities by truck in Brazil are a challenge to decision-making. This article brings together the widely held theories vertical coordination and decision analysis to present a discussion of decision-making in organizations. From a model capable of processing main objectives, multiple criteria, and variables found in transport verticalization problems, the results showed worse performance than hybrid or outsourced alternatives. These results support that in environments with high dependence on low costs and asset specificity, they are no more likely to meet hybrid structures or market coordination. As the price difference between the outsourced and vertical model decreases, there is a preference for hierarchical structure, given its better performance related to the benefits offered. Changes in the institutional environment, such as transport regulations, may modify competitive arrangements. This type of preference by decision-makers for vertical structures could allow larger scale in conjunction with strategies by shippers, as operation costs remain close to those charged by carriers. [ABSTRACT FROM AUTHOR]

This article presents an application of the multicriteria method PROMÉTHÉE V to the problem of prioritizing telecommunication projects. The study was conducted inside of a major telecommunications company in Brazil. The adherence to a multicriteria approach allowed for taking into consideration technical as well as non technical evaluation criteria. Using PROMÉTHÉE V was particularly appropriate not only because the method performed an initial ranking of the set of projects, but also because it led to a constrained optimization of the obtained selection. It is then concluded that the application of PROMÉTHÉE V to the problem in question achieved its key purpose in the sense of organizing and solving a complex process of decision analysis. It also provided for interactivity during the analysis and useful simulations, giving transparency to the analysis and thus providing for a common base of understanding for all involved. [ABSTRACT FROM AUTHOR]

This article applies a transformation into probabilities of preference, to rank papers submitted to the XLI Brazilian Symposium of Operational Research. Some 42 papers were divided into sets according to their main topics of interest and measures for 12 attributes were considered, for each paper separately, and also for sets of papers on the same topic, based on the referees' evaluations. Four alternative forms of composition of the probabilistic preferences are illustrated. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Economia e Administração is the property of INSPER Instituto de Ensino e Pesquisa and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The increasing production of oil and gas in the marine environment and the growing participation of companies of different nationalities and sizes require the use of tools to support the sustainable management of offshore oil and gas production units. This paper presents the results of the application of a sustainability indicator system, developed from the identification of the economic, environmental, social, and operational impacts of the activities of these production units. The sustainability performances of 3 oil and gas production units operating in the Brazilian marine environment were compared to the performance of one considered ideal, through the application of the PROMETHEE II and ordinal COPELAND multicriteria methods. The indicator system applied favored the analysis of the sustainability management of offshore oil and gas production activity in a multidimensional approach, considering the points of view of experts from various areas of knowledge, and proved to be a reliable tool to support the sustainable management of these offshore production units. Integr Environ Assess Manag 2021;17:614-625. © 2020 SETAC., (© 2020 SETAC.)

Resurgent outbreaks of vaccine-preventable diseases that have previously been controlled or eliminated have been observed in many settings. Reactive vaccination campaigns may successfully control outbreaks but must necessarily be implemented in the face of considerable uncertainty. Real-time surveillance may provide critical information about at-risk population and optimal vaccination targets, but may itself be limited by the specificity of disease confirmation. We propose an integrated modelling approach that synthesizes historical demographic and vaccination data with real-time outbreak surveillance via a dynamic transmission model and an age-specific disease confirmation model. We apply this framework to data from the 1996-1997 measles outbreak in São Paulo, Brazil. To simulate the information available to decision-makers, we truncated the surveillance data to what would have been available at 1 or 2 months prior to the realized interventions. We use the model, fitted to real-time observations, to evaluate the likelihood that candidate age-targeted interventions could control the outbreak. Using only data available prior to the interventions, we estimate that a significant excess of susceptible adults would prevent child-targeted campaigns from controlling the outbreak and that failing to account for age-specific confirmation rates would underestimate the importance of adult-targeted vaccination., (© 2018 The Author(s).)