A Geração de inovação na carcinicultura do RN: Uma análise a partir da imersão social

This dissertation examines the organizational innovation as a nonlinear process, which occurs in a social and political context and, therefore, socially immersed. Examines the case of shrimp in the state of RN, starting from the following problem: although the norteriograndense shrimp occupies the largest producer of farmed shrimp from Brazil, has a series of bottlenecks concerning the generation of industry innovation, concerning the social relationships and policies between the various actors in the network, whether private or public, and its consequences in terms of opportunity and limits generated for the innovative dynamics. The objective of the research is to understand how the social embeddedness of political actors affects norteriograndense shrimp within the context of structural relations, the industry generation of innovation, throughout its technological trajectory . The approach of social embeddedness balances atomised perspectives, undersocialized and oversocialized, of economic action, considering both the human capacity to act as sources of constraint, whose mechanisms are analyzed the structural and political. In methodological terms this is a case study, analyzed from the research literature, documentary and experimental. Primary data were collected through semi-structured interviews and analyzed in depth by the technique of content analysis. Was adopted a longitudinal approach, seeking to understand the phenomenon from the perspective of the subjects, describing it in an inductive process of investigation. After characterizing the sector and defining their technological trajectory, the analysis of the results followed its four stages: (1) Introduction of Technology: 1973-1980, (2) Intensification of Research: 1981-1991, (3) Technological Adaptation, 1992 -2003, (4) Technological Crisis: 2004-2009. A cross-sectional analysis along the evolutionary trajectory revealed the character of structural changes and policies over time, and implications on the generating process of innovation. Note that, the technological limit to which the sector reached requires changes in technology standards, but is more likely that the potiguar shrimp is entering a new phase of his career in technology rather than a new technological paradigm

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model