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This paper proposes the use of the AHP-Gaussian method to support the selection of a smart sensor installation for an electric motor used in an escalator in a subway station. The AHP-Gaussian methodology utilizes the Analytic Hierarchy Process (AHP) framework and is highlighted for its ability to save the decision maker’s cognitive effort in assigning weights to criteria. Seven criteria were defined for the sensor selection: temperature range, vibration range, weight, communication distance, maximum electric power, data traffic speed, and acquisition cost. Four smart sensors were considered as alternatives. The results of the analysis showed that the most appropriate sensor was the ABB Ability smart sensor, which scored the highest in the AHP-Gaussian analysis. In addition, this sensor could detect any abnormalities in the equipment’s operation, enabling timely maintenance and preventing potential failures. The proposed AHP-Gaussian method proved to be an effective approach for selecting a smart sensor for an electric motor used in an escalator in a subway station. The selected sensor was reliable, accurate, and cost-effective, contributing to the safe and efficient operation of the equipment.

This paper presents a new approach based on Multi-Criteria Decision Analysis (MCDA), named PROMETHEE-SAPEVO-M1, through its implementation and feasibility related to the decision-making process regarding the evaluation of helicopters of attack of the Brazilian Navy. The proposed methodology aims to present an integration of ordinal evaluation into the cardinal procedure from the PROMETHEE method, enabling to perform qualitative and quantitative data and generate the criteria weights by pairwise evaluation, transparently. The modeling provides three models of preference analysis, as partial, complete, and outranking by intervals, along with an intra-criterion analysis by veto threshold, enabling the analysis of the performance of an alternative in a specific criterion. As a demonstration of the application, is carried out a case study by the PROMETHEE-SAPEVO-M1 web platform, addressing a strategic analysis of attack helicopters to be acquired by the Brazilian Navy, from the need to be evaluating multiple specifications with different levels of importance within the context problem. The modeling implementation in the case study is made in detail, first performing the alternatives in each criterion and then presenting the results by three different models of preference analysis, along with the intra-criterion analysis and a rank reversal procedure. Moreover, is realized a comparison analysis to the PROMETHEE method, exploring the main features of the PROMETHEE-SAPEVO-M1. Moreover, a section of discussion is presented, exposing some features and main points of the proposal. Therefore, this paper provides a valuable contribution to academia and society since it represents the application of an MCDA method in the state of the art, contributing to the decision-making resolution of the most diverse real problems.

Personnel selection is increasingly proving to be an essential factor for the success of organizations. These issues almost universally involve multiple conflicting objectives, uncertainties, costs, and benefits in decision-making. In this context, personnel assessment problems, which include several candidates as alternatives, along with several complex evaluation criteria, can be solved by applying Multicriteria Decision Making (MCDM) methods. Uncertainty and subjectivity characterize the choice of personnel for missions or promotions at the military level. In this paper, we evaluated 30 Brazilian Navy officers in the light of four criteria and 34 subcriteria. To support the decision-making process regarding the promotion of officers, we applied the ELECTRE-Mor MCDM method. We categorized the alternatives into three classes in the modeling proposed in this work, namely: Class A (Promotion by deserving), Class B (Promotion by seniority), and Class C (Military not promoted). As a result, the method presented 20% of the officers evaluated with performance corresponding to class A, 53% of the alternatives to class B, and 26.7% with performances attributed to class C. In addition, we presented a sensitivity analysis procedure through variation of the cut-off level λ, allowing decision-making on more flexible or rigorous scenarios at the discretion of the Naval High Administration. This work brings a valuable contribution to academia and society since it represents the application of an MCDM method in state of the art to contribute to solving a real problem.

Lean management principles include customer focus, continuous improvement and quality through waste reduction for organizations, including IT, bringing benefits such as bringing people together and changing paradigms. In this context, this paper presents a literature review on the current characteristics of lean manufacturing applied to information technology departments or companies. The methodology includes the selection of documents from the Scopus and Web of Science databases, a bibliometric study and a literature review with the selected documents. The bibliometric study identified the document type, language, year of publication, authors, author network, author’s H-index, affiliation, keyword clusters, country or territory and field of knowledge. The VOSviewer software was used to create the maps of the author network and keyword clusters. The literature review presented the main topics of Lean IT, which is a relatively new field of knowledge yet to be fully explored and researched. The results showed that there is no typical pattern regarding the number of publications, and that the concept is still much more used in business than in academy. There is no core of well-defined authors. The Lean methodology is not just the so-called \"factory floor\". It has been adopted by several other areas; although 50% of the documents are concentrated in two areas: Computer Science and Engineering. Hopefully this paper can contribute as a source of data for future studies on lean management within IT.

Decision-support methods are crucial for analyzing complex alternatives and criteria in today's data-driven world. This Systematic Literature Review (SLR) explores and synthesizes knowledge about decision support methodologies that integrate Multicriteria Decision Making (MCDM) and Principal Component Analysis (PCA), an unsupervised Machine Learning (ML) technique. Both techniques optimize complex decisions by combining multiple criteria and dimensional data analysis. Focusing on performance evaluations, criterion weighting, and validation testing, this review identifies significant gaps in existing methodologies. These include the lack of consideration for non-beneficial criteria in PCA, insufficient validation tests in over half of the studies, and the non-use of communalities (the contribution of each criterion to the main factors) in decision support approaches. Additionally, this SLR offers a comprehensive quantitative overview, analyzing data from the Scopus, IEEE, and Web of Science databases and identifying 16 relevant studies. Furthermore, the scarcity of systematic reviews integrating MCDM and PCA techniques impedes evidence-based decision-making practices and theoretical evolution. This is particularly crucial as ML and data analysis advance rapidly, requiring models that reflect technological innovations. This article addresses this gap in the literature by providing an analysis of decision support methods and guiding further improvement in this field.

Sustainability has become a relevant element for organizations due to several motivators: companies adopt sustainability practices in need for regulatory compliance, anticipation of regulatory changes, understanding of limited natural resources, and a desire to limit expenditure associated with resource consumption and waste disposal. Thus, this article aims to identify the gaps present in maturity models, present an integrator theoretical model that considers the characteristic elements of the models present in the literature and affects the level of maturity in sustainability. The construction of the integrator theoretical model was based on the following stages: research questions; theoretical framework on Supply Chain Management; sustainability and concept of maturity model; maturity models and performance measurement systems; interpretation/analysis of research; and construction of the integrator theoretical model. The literature review was carried out in the Scopus and Web of Science databases. The main conclusions: maturity models focus on only one aspect or are excessively broad and do not include in detail the elements necessary to measure the level of maturity in sustainability. The proposed model aims to mitigate these gaps with the addition of the cross-sectional dimension, which offers an integrated and holistic view in relation to the other dimensions.

The production efficiency factor is widely used to measure the zootechnical performance of a batch of broilers. The unit cost of production brings new elements to improve efficiency evaluation and financial sustainability for this activity in agriculture. This research aims to evaluate the production efficiency level of the crop to maximize the return on investment. This study uses Data Envelopment Analysis (DEA) with the computational processing of the SIAD software (Integrated Decision Support System). The variables selected were poultry housing, age at slaughter, feed consumed, mortality, and unit cost. The chosen output variable was the total available weight. The analysis spans 31 decision-making units (DMUs) composed of integrated producers, unveiling a frontier of efficiency delineated by the most exemplary DMUs. Notably, only two DMUs, specifically DMU 4 and DMU 23, approached the threshold of maximum relative efficiency. This research illuminates the critical role of unit cost in enhancing the assessment of production efficiency and financial sustainability within the agriculture environment. By setting benchmarks for efficient management and operational protocols, our findings serve as a cornerstone for improving practices among less efficient DMUs, contributing significantly to the literature on agricultural efficiency and offering actionable insights for the poultry farming sector.

Purpose This paper aims to comprehensively analyze renewable energy alternatives in Brazil, focusing on identifying the most suitable option for investment in the country’s sustainable development. Design/methodology/approach The study adopts the step-wise weight assessment ratio analysis-multiobjective optimization by ratio analysis −3NAG (a combination of three normalization methods) methodology, a multicriteria decision-making approach, to evaluate and rank renewable energy sources based on key criteria such as resource availability, cost-effectiveness, job creation potential and environmental impact. Findings The analysis reveals that solar energy emerges as the preferred choice for Brazil, offering significant advantages over other alternatives such as hydroelectric, wind and biomass energy. Solar energy’s distributed generation capability, cost reduction trends and positive environmental impact contribute to its favorable position in meeting Brazil’s energy needs. Research limitations/implications While the study provides valuable insights into renewable energy selection, there are limitations regarding the criteria’ scope and the exclusion of specific renewable energy options. Future research could explore sensitivity analyses and incorporate additional criteria to enhance the study’s comprehensiveness. Originality/value This research contributes to the existing literature by thoroughly analyzing renewable energy alternatives in Brazil using a robust multicriteria decision-making methodology. The study’s findings provide actionable guidance for policymakers, businesses and stakeholders seeking to promote sustainable energy development in the country.

Decision-making in complex environments, especially sustainable ones, requires flexible methodologies to handle multiple criteria and stakeholder perspectives. This study introduces the SAPEVO-H2 method (Simple Aggregation of Preferences Expressed by Ordinal Vectors—Hybrid and Hierarchical), an extensive model from the SAPEVO family, which offers multi-criteria analysis through a hierarchical structure of variables evaluated by groups partitioned into levels concerning their respective responsibilities. The proposal allows flexible analysis, considering inputs through ordinal and cardinal information. The validation of the methodology is demonstrated through a case study involving an automobile manufacturing company, which focuses on prioritizing sustainability projects based on multiple objectives aimed at minimizing polluting gas emissions. Within a hierarchical structure of five levels, the individual level results are presented. In addition, a sensitivity analysis is applied, exposing the most sensitive variables to changes concerning the highest levels. Then, we discuss the main contributions and limitations concerning the mathematical proposal and the conclusions and proposals for future work.

The healthcare environment presents a large volume of personal and sensitive patient data that needs to be available and secure. Information and communication technology brings a new reality to healthcare, promoting improvements, agility and integration. Regarding high-level and complex decision-making scenarios, the Brazilian Navy (BN), concerning its healthcare field, is seeking to provide better management of its respective processes in its hospital facilities, allowing accurate control of preventive and curative medicine to members who work or have served there in past years. The study addresses the understanding, structure and clarifying variables related to the feasibility of technological updating and installing of a Hospital Information System (HIS) for BN. In this scenario, through interviews and analysis of military organization business processes, criteria and alternatives were established based on multi-criteria methodology as a decision aid. As methodological support for research and data processing, THOR 2 and PROMETHEE-SAPEVO-M1 methods were approached, both based on the scenarios of outranking alternatives based on the preferences established by the stakeholders in the problem. As a result of the methodological implementation, we compare the two implemented methods in this context, exposing the Commercial Software Purchase and Adoption of Free Software, integrated into Customization by the Marine Studies Foundation, as favorable actions to be adopted concerning HIS feasibility. This finding generates a comprehensive discussion regarding the BN perspective and changes in internal development in the military environment, prospecting alignment to the culture of private organizations in Information Technology for healthcare management. In the end, we present some conclusions concerning the study, exploring the main points of the decision-making analysis and for future research.