A Mocca Pode Inovar?

Este caso é uma narrativa com enredo fictício baseado em fatos reais vivenciados pelos autores ao longo das suas trajetórias profissionais. Para tanto, apresenta-se a Mocca, uma empresa familiar do ramo calçadista com 34 anos de existência e que viveu seu ápice no final dos anos 90. Entretanto, no início dos anos 2000 viu suas vendas diminuírem por conta da redução de barreiras comerciais e da migração do setor calçadista para os grandes centros do país – desde então a empresa passa por uma estagnação. Agora a Mocca precisa se reinventar e inovar para voltar a crescer. Algumas questões são levantadas e os gestores da Mocca precisam identificar ferramentas de inovação que auxiliem a implementação de estratégias de inovação para o crescimento do negócio. Assim, a Mocca busca alternativas para implementar inovações que a recoloquem em um patamar competitivo. Neste caso, com o apoio de ferramentas de gestão da inovação, os alunos são orientados a discutirem e explorarem soluções para a Mocca.

Sociedade 5.0: explorando os dilemas do ecossistema social do futuro

A Sociedade 5.0 é um conceito que tem ganhado força em todo o mundo, com o objetivo de usar tecnologias digitais e habilidades humanas para promover inclusão, sustentabilidade e equidade. Por meio de uma revisão sistemática da literatura, de cunho reflexivo-crítico, apoiada pelo protocolo PRISMA-P, este trabalho identifica as principais pesquisas do campo de estudo e explora o conceito de Sociedade 5.0. Além disso, são discutidos os principais dilemas associados a nova proposta de ecossistema social e seus impactos na sociedade. Devido a incipiência do campo de estudo, poucos trabalhos discutiram as implicações do conceito e do fenômeno da Sociedade 5.0, e os trabalhos existentes evidenciam um pulsante antagonismo entre os pesquisadores da área. Apesar das divergências acerca do conceito, os resultados desta pesquisa mostram alinhamento no que tange ao objetivo geral da Sociedade 5.0. Entende-se que a sociedade evolui quando cidadãos, organizações e governo, com intermédio da tecnologia, desenvolvem um ecossistema social sustentável, cujo objetivo final é a qualidade de vida humana. As discussões, dilemas e lacunas levantadas nesta pesquisa podem gerar insights para outros pesquisadores e nortear trabalhos futuros no campo de estudo.

Covid-19 Outbreak in Brazil: Health, Social, Political, and Economic Implications

COVID-19 outbreak quickly spread to all corners of the globe. In Brazil, the outbreak was particularly frightening because it worsened existing health, political, economic, and social problems. The results already observed show the contagion ripple-spreading process across the country, causing the death of thousands of people each day and counting, added to a very serious wave of unemployment, scientific denial, and social precariousness. Based on this, this study reviews recent research that looked at the role of the government, the Brazilian health system, and the main economic and social impacts fostered by the pandemic. We perform a scoping review according to the PRISMA-ScR to structure the qualitative synthesis of the 67 associated documents. The results reinforce the negative effects of the country's mismanagement and its consequent impacts on the Brazilian economy and society. The battleground against COVID-19 has fueled political tensions, shaken the health system, and unleashed social despair tinged with thousands of deaths. Finally, in the present scoping review, we discuss concerns about the impacts of the COVID-19 outbreak in Brazil and what the world hopes the country has learned from the current crisis.

A Bibliometric Network Analysis of Recent Publications on Digital Agriculture to Depict Strategic Themes and Evolution Structure

The agriculture sector is one of the backbones of many countries’ economies. Its processes have been changing to enable technology adoption to increase productivity, quality, and sustainable development. In this research, we present a scientific mapping of the adoption of precision techniques and breakthrough technologies in agriculture, so-called Digital Agriculture. To do this, we used 4694 documents from the Web of Science database to perform a Bibliometric Performance and Network Analysis of the literature using SciMAT software with the support of the PICOC protocol. Our findings presented 22 strategic themes related to Digital Agriculture, such as Internet of Things (IoT), Unmanned Aerial Vehicles (UAV) and Climate-smart Agriculture (CSA), among others. The thematic network structure of the nine most important clusters (motor themes) was presented and an in-depth discussion was performed. The thematic evolution map provides a broad perspective of how the field has evolved over time from 1994 to 2020. In addition, our results discuss the main challenges and opportunities for research and practice in the field of study. Our findings provide a comprehensive overview of the main themes related to Digital Agriculture. These results show the main subjects analyzed on this topic and provide a basis for insights for future research.

Data mining and knowledge discovery in databases for urban solid waste management: A scientific literature review

The processes related to solid waste management (SWM) are being revised as new technologies emerge and are applied in the area to achieve greater environmental, social and economic sustainability for society. To achieve our goal, two robust review protocols (Population, Intervention, Comparison, Outcome, and Context (PICOC) and Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA)) were used to systematically analyze 62 documents extracted from the Web of Science database to identify the main techniques and tools for Knowledge Discovery in Databases (KDD) and Data Mining (DM) as applied to SWM and explore the technological potential to optimize the stages of collecting and transporting waste. Moreover, it was possible to analyze the main challenges and opportunities of KDD and DM for SWM. The results show that the most used tools for SWM are MATLAB (29.7%) and GIS (13.5%), whereas the most used techniques are Artificial Neural Networks (35.8%), Linear Regression (16.0%) and Support Vector Machine (12.3%). In addition, 15.3% of the studies were conducted with data from China, 11.1% from India and 9.7% of the studies analyzed and compared data from several other countries. Furthermore, the research showed that the main challenges in the field of study are related to the collection and treatment of data, whereas the opportunities appear to be linked mainly to the impact on the pillars of sustainable development. Thus, this study portrays important issues associated with the use of KDD and DM for optimal SWM and has the potential to assist and direct researchers and field professionals in future studies.

Data Mining in Healthcare: Applying Strategic Intelligence Techniques to Depict 25 Years of Research Development

In order to identify the strategic topics and the thematic evolution structure of data mining applied to healthcare, in this paper, a bibliometric performance and network analysis (BPNA) was conducted. For this purpose, 6138 articles were sourced from the Web of Science covering the period from 1995 to July 2020 and the SciMAT software was used. Our results present a strategic diagram composed of 19 themes, of which the 8 motor themes ('NEURAL-NETWORKS', 'CANCER', 'ELETRONIC-HEALTH-RECORDS', 'DIABETES-MELLITUS', 'ALZHEIMER'S-DISEASE', 'BREAST-CANCER', 'DEPRESSION', and 'RANDOM-FOREST') are depicted in a thematic network. An in-depth analysis was carried out in order to find hidden patterns and to provide a general perspective of the field. The thematic network structure is arranged thusly that its subjects are organized into two different areas, (i) practices and techniques related to data mining in healthcare, and (ii) health concepts and disease supported by data mining, embodying, respectively, the hotspots related to the data mining and medical scopes, hence demonstrating the field's evolution over time. Such results make it possible to form the basis for future research and facilitate decision-making by researchers and practitioners, institutions, and governments interested in data mining in healthcare.

Thirty Years of Human Rights Study in the Web of Science Database (1990-2020)

The study of human rights (HR) is vital in order to enhance the development of human beings, but this field of study still needs to be better depicted and understood because violations of its core principles still frequently occur worldwide. In this study, our goal was to perform a bibliometric performance and network analysis (BPNA) to investigate the strategic themes, thematic evolution structure, and trends of HR found in the Web of Science (WoS) database from 1990 to June 2020. To do this, we included 25,542 articles in the SciMAT software for bibliometric analysis. The strategic diagram produced shows 23 themes, 12 of which are motor themes, the most important of which are discussed in this article. The thematic evolution structure presented the 21 most relevant themes of the 2011-2020 period. Our findings show that HR research is directly related to health issues, such as mental health, HIV, and reproductive health. We believe that the presented results and HR panorama presented have the potential to be used as a basis on which researchers in future works may enhance their decision making related to this field of study.

A Bibliometric Network Analysis of Coronavirus during the First Eight Months of COVID-19 in 2020

The COVID-19 pandemic has affected all aspects of society. Researchers worldwide have been working to provide new solutions to and better understanding of this coronavirus. In this research, our goal was to perform a Bibliometric Network Analysis (BNA) to investigate the strategic themes, thematic evolution structure and trends of coronavirus during the first eight months of COVID-19 in the Web of Science (WoS) database in 2020. To do this, 14,802 articles were analyzed, with the support of the SciMAT software. This analysis highlights 24 themes, of which 11 of the more important ones were discussed in-depth. The thematic evolution structure shows how the themes are evolving over time, and the most developed and future trends of coronavirus with focus on COVID-19 were visually depicted. The results of the strategic diagram highlight 'CHLOROQUINE', 'ANXIETY', 'PREGNANCY' and 'ACUTE-RESPIRATORY-SYNDROME', among others, as the clusters with the highest number of associated citations. The thematic evolution. structure presented two thematic areas: "Damage prevention and containment of COVID-19" and "Comorbidities and diseases caused by COVID-19", which provides new perspectives and futures trends of the field. These results will form the basis for future research and guide decision-making in coronavirus focused on COVID-19 research and treatments.