O BPM SOCIAL COMO UMA FORMA MAIS RÁPIDA DE ALCANÇAR RESULTADOS NAS UNIVERSIDADES PÚBLICAS FEDERAIS BRASILEIRAS

A gestão de processos de negócios ou BPM (Business Process Management) é um modelo de gestão que objetiva a efetividade na entrega de resultados e apresenta uma visão horizontalizada dos processos das organizações, respeitando, em suma, o fluxo de entrada de recursos e o processamento destes para gerar produtos como saídas. Sequencialmente, o BPM Social agrega ao BPM padrão as nuances que as mídias sociais podem trazer tanto pra o comportamento humano no ambiente de trabalho, quanto para a melhoria dos resultados das organizações. Neste ínterim, o presente texto apresenta uma pesquisa qualitativa descritiva dos fatos estudados considerando a literatura existente e a leitura de casos práticos, resultando, consequentemente, na percepção de uma afinidade entre o modelo de gestão advindo do BPM Social e o novo contexto das universidades públicas federais brasileiras. Houve, portanto, a preocupação em respeitar o momento atual de mudanças no ambiente e almejaram-se melhorias na prestação do serviço à sociedade como um todo, no sentido de tornar as entregas de tais universidades não só mais efetivas como também mais ágeis

A MODEL FOR EVALUATING INFORMATION SECURITY WITH A FOCUS ON THE USER

This study presents a theoretical model to evaluate the level of information security in an organizational environment with a focus on the knowledge, attitudes and behaviour of the end user, identifying the level and origin of the gap between the information security guidelines laid down by the company and the actual practices of its internal staff, third party partners and suppliers. The model is designed to assist in meeting the objectives and policies set for the management of information security by senior management, and contributes to maintaining an effective program of training and in raising awareness on information security

Exploring Text Mining and Analytics for Applications in Public Security: An in-depth dive into a systematic literature review

Text mining and related analytics emerge as a technological approach to support human activities in extracting useful knowledge through texts in several formats. From a managerial point of view, it can help organizations in planning and decision-making processes, providing information that was not previously evident through textual materials produced internally or even externally. In this context, within the public/governmental scope, public security agencies are great beneficiaries of the tools associated with text mining, in several aspects, from applications in the criminal area to the collection of people's opinions and sentiments about the actions taken to promote their welfare. This article reports details of a systematic literature review focused on identifying the main areas of text mining application in public security, the most recurrent technological tools, and future research directions. The searches covered four major article bases (Scopus, Web of Science, IEEE Xplore, and ACM Digital Library), selecting 194 materials published between 2014 and the first half of 2021, among journals, conferences, and book chapters. There were several findings concerning the targets of the literature review, as presented in the results of this article

Multicriteria Model of Preventive Maintenance

It is extremely important to guarantee that the performance levels required by productive systems can be maintained. As well, it is essential to assure the quality of process outputs. For this reason, preventative maintenance has become a very useful instrument to gain a competitive edge. In maintenance decisions, there are some contradictory criteria or points of view that are vital and must to be looked at simultaneously. Optimization approaches are not so useful in this situation, since usually no decision or solution exists which is the best from all points of view at the same time. So, in this context, the multicriteria decision aid (MCDA) approach is very important, allowing not only for the trade-off of multiple factors, but also taking in account the preference structure of the decision-maker with respect to these contradictory criteria. To address this issue, this article proposes a multicriteria decision aid model to support the decision-maker in the choice of times for preventative maintenance. The model preserves some important concepts from the classic models of component replacement and improves an existing multicriteria model, by taking criterion downtime into consideration, making a more appropriate treatment possible than the previous model for situations in cases where repair time cannot be ignored

Multi-criteria model for classifying clients of companies distributing liquefied petroleum gas

Liquefied Petroleum Gas (LPG) is a fossil fuel that has been attracting a lot of attention in national and global markets because of its logistical versatility, its calorific power, and because it emits a low level of pollutants. The history of its exploitation in the sharply competitive Brazilian market has been marked by various crises which made the exploitation of LPG an activity that has been subject to a number of uncertainties. The product is in the production chain of different market segments and is an important component in the national energy matrix. As a result of this, the process of classifying consumers by LPG distributors is a strategic task and subject to a set of criteria that need to be observed. In this context, this article concentrates on multi-criteria modeling in order to resolve the problematic of classifying clients in a LPG distribution company. A model is proposed based on the ELECTRE TRI method and the aim is to allocate the portfolio of clients to a set of ranked classes.

A Grey Theory Based Approach to Big Data Risk Management Using FMEA

Big data is the term used to denote enormous sets of data that differ from other classic databases in four main ways: (huge) volume, (high) velocity, (much greater) variety, and (big) value. In general, data are stored in a distributed fashion and on computing nodes as a result of which big data may be more susceptible to attacks by hackers. This paper presents a risk model for big data, which comprises Failure Mode and Effects Analysis (FMEA) and Grey Theory, more precisely grey relational analysis. This approach has several advantages: it provides a structured approach in order to incorporate the impact of big data risk factors; it facilitates the assessment of risk by breaking down the overall risk to big data; and finally its efficient evaluation criteria can help enterprises reduce the risks associated with big data. In order to illustrate the applicability of our proposal in practice, a numerical example, with realistic data based on expert knowledge, was developed. The numerical example analyzes four dimensions, that is, managing identification and access, registering the device and application, managing the infrastructure, and data governance, and 20 failure modes concerning the vulnerabilities of big data. The results show that the most important aspect of risk to big data relates to data governance

DSS Research Collaboration in the EWG-DSS

DSS Collab-Net on line: An on line platform for DSS-research collaboration in EWG-DSS. The main goal of the Collab-net is to allow researchers to analyze their own collaborative network, as well as possibilities for future collaboration among EWG-DSS members only using a Web-based platform, in anywhere at anytime