9 resultados para Truncated negative binomial model
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics
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Academics are often ranked on citation counts’, which is considered an adequate proxy for author's quality and reputation. This paper seeks to find what is behind a cited academic / a cited article. We constructed a rich dataset from Portuguese affiliated economists and use zero inflated negative binomial model. This procedure is appropriate for count outcomes, correcting for overdispersion and excess zeros. We also use a fixed effect poisson model to accomodate authors' unobserved heterogeneity. We analyze results in detail comparing with existing literature and making some theoretical considerations around.
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Due to global warming and shrinking fossil fuel resources, politics as well as society urge for a reduction of green house gas (GHG) emissions. This leads to a re-orientation towards a renewable energy sector. In this context, innovation and new technologies are key success factors. Moreover, the renewable energy sector has entered a consolidation stage, where corporate investors and mergers and acquisitions (M&A) gain in importance. Although both M&A and innovation in the renewable energy sector are important corporate strategies, the link between those two aspects has not been examined before. The present thesis examines the research question how M&A influence the acquirer’s post-merger innovative performance in the renewable energy sector. Based on a framework of relevant literature, three hypotheses are defined. First, the relation between non-technology oriented M&A and post-merger innovative performance is discussed. Second, the impact of absolute acquired knowledge on postmerger innovativeness is examined. Third, the target-acquirer relatedness is discussed. A panel data set of 117 firms collected over a period of six years has been analyzed via a random effects negative binomial regression model and a time lag of one year. The results support a non-significant, negative impact of non-technology M&A on postmerger innovative performance. The applied model did not support a positive and significant impact of absolute acquired knowledge on post-merger innovative performance. Lastly, the results suggest a reverse relation than postulated by Hypothesis 3. Targets from the same industry significantly and negatively influence the acquirers’ innovativeness.
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Computational Logic
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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica
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Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente, Perfil de Gestão e Sistemas Ambientais
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Double degree
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The aim of this research is to investigate if a celebrity can be a mediator between two brands so that a negative event happening to one brand can spill over to a completely unrelated brand, which shares with the first brand only the celebrity endorser. Even though celebrity endorsement is a popular marketing strategy and celebrities often endorse multiple brands, so far there has not been any systematic study on this topic. Drawing on Associative Network Theory and the Meaning Transfer Model as theoretical framework, this research finds out that negative publicity about a brand can spill over and thereby not only hurt consumers’ attitude toward the celebrity endorser but also toward a second brand that is endorsed by the same celebrity. An unexpected finding is that celebrities can act as a protective shield for brands by weakening the direct impact of negative publicity.
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Tenofovir (TFV) is one of the most used antiretroviral drugs. However, it is associated with tubular damage with mitochondria as a possible target. Tubulopathy precedes glomerular dysfunction, thus classic markers of renal function like the glomerular filtration rate (GFR) do not detect early TFV damage. Prediction and management of drug induced renal injury (DIRI) rely on the mechanisms of the drug insult and in optimal animal models to explore it. Zebrafish (Danio rerio) offers unique advantages for assessing DIRI, since the pronephros is structurally very similar to its human counterpart and is fully developed at 3.5 days postfertilization. The main aim of the present work was to evaluate the effects of TFV, as well as its pro-drug, tenofovir disoproxil fumarate (TDF), on the GFR and in mitochondria morphology in tubular cells of zebrafish larvae. Lethality curves were performed to understand the relationship between drug concentration and lethality. LC10 was selected to explore the renal function using the FITC-inulin assay and to analyze the mitochondrial toxicity by electron microscopy on larvae exposed to TDF, TFV, paracetamol and gentamicin (positive controls) or water (negative control). Lethality curves showed that gentamicin was the most lethal drug, followed by TDF, TFV and paracetamol. Gentamicin and paracetamol decreased the GFR, but no differences were found for either TDF or TFV, when compared to controls (%FITC Control = 33±8; %FITC TDF = 35±10; %FITC TFV = 30±10; %FITC Gentamicin = 46±17; %FITC Paracetamol = 83±14). Tubular mitochondria from treated larvae were notably different from non-treated larvae, showing swelling, irregular shapes, decreased mitochondria network, cristae disruption and loss of matrix granules. These results are in agreement with the effects of these drugs in humans and thus, demonstrate that zebrafish larvae can be a good model to assess the functional and structural damage associated with DIRI.