Kelly Carvalho Vieira

Multivariate analysis of credit risk and bankruptcy research data: a bibliometric study involving different knowledge fields (1968---2014)

Bibliometrics are important evaluation tools to the scientific production. A bibliometric study was used to evaluate researches about credit risk and bankruptcy. Credit support technique studies on economic and social orders are relevant in this knowledge field. Therefore, the aim of the current study is to identify and describe the application of multivariate data analysis techniques to credit risk and bankruptcy scenarios. The herein presented data were collected in publications indexed to Thomson Reuters’ Web of Science database between 1968 and 2014. The results corroborate information in the literature and in previous bibliometric reviews, as well as highlight other indications regarding the construction and development of research fields. Since the 1990’s, the neural networks became relevant due to their increased use as study object in publications. However, both the discriminant analysis (J Finance 23(4):589–609, 1968. doi:10.2307/2978933) and the logistic regression (J Account Res 18(1):109–131, 1980. doi:10.2307/2490395) are still often used in researches, fact that shows the tendency to find articles using more than one technique or hybrid models, artificial intelligence techniques and complex computer systems. This field appears to be multidisciplinary in journals and Web Science databases involving the business and economy, operational research, management, mathematics, data processing, engineering and statistics fields. Another relevant discovery was the increased number of publications about this subject launched right after the 2008 crisis.

Using Crowdstorm to Prospect Innovations in Federal Institutions of Education in Brazil to Reduce Its Consumption of Electric Energy

The growing Brazilian demand for electricity, the untenable situation of the global energy matrix, and the representation of spending with the electricity consumption at the Matrix of Budget for Other Costing and Funds (OCC Matrix) of Federal Institutions of Education (FIEs) in Brazil: These all require special consideration. This work aims to identify, through social participation, innovative ideas that enable the FIEs to reduce their spending on electricity consumption. The results of this project have shown that social participation contributed not only to identifying prospective solutions but also to mobilizing and educating communities, academic or not, for the support of the subject. Although this work has not contemplated the implementation of solutions, it was realized that reducing spending on FIEs depends on actions involving actors other than the institution itself. In this sense, a social participation can contribute directly to the involvement and engagement of these actors.