During the last three decades, a number of studies based on national environmental monitoring data have found increased concentrations of total organic carbon (TOC) in surface waters in much of the northern hemisphere including Sweden. There are many hypothesis of what has been the main cause of this trend, including changes in land use, decreased atmospheric deposition of acidifying compounds and climate change. Different hypothesis may have different implications for quantifying pre-industrial levels and for future predictions of TOC concentrations, which in turn will have different implications for water classification according to the European Water Framework Directive, water management and drinking water treatment. To analyse the long term effects of industrialisation and climate change on TOC in surface waters there is a need for long term time series of data. Since environmental monitoring data in Sweden only extends back to the mid-1980s, other techniques must be used in order to reconstruct data. In this study, sediment cores from 17 lakes along a climatic and deposition gradient in Sweden were collected and analysed with visible near infrared spectroscopy (VNIRS), an analytical technique that makes it possible to reconstruct historic surface water concentrations of TOC to pre-industrial conditions. A previous study with VNIRS showed that TOC concentrations declined in response to sulfate deposition until peak sulfur deposition in 1980, and thereafter increased as a result of sharp reductions of sulfate emissions. It was noted that the rate of increase of TOC after 1980 was faster than the rate of decrease due to sulfate deposition before 1980. The purpose of this study was therefore to explore the hypothesis that increasing TOC concentrations have not only been due to recovery from acidification, but also due to changes in climate. It was possible to analyse the long term effects of industrialisation and climate change on surface water TOC by analysing the reconstructed TOC data together with climate data from the beginning of the 1900s, modelled data of atmospheric sulfate deposition and environmental monitoring data, with uni- and multivariate analysis methods. It was found that the recent increase in TOC concentrations could be explained by both decreases in acidifying atmospheric deposition and increased precipitation, while temperature may have a decreasing effect on TOC. It was also found that the rate of increase of TOC-concentrations has been faster in the colder northern parts of Sweden and slower in the warmer south. The results imply that TOC concentrations will continue to rise to unpreceded levels and should be of concern for drinking water treatment plants that will need to adapt their treatment processes in the future. / Under de senaste tre årtiondena har ett flertal studier baserade på data från nationella miljöövervakningsprogram rapporterat ökande koncentrationer av organiskt kol (TOC) i ytvatten på norra halvklotet inklusive Sverige. Det finns många hypoteser om vad som ligger bakom trenden, till exempel förändringar i markanvändning, minskad atmosfärisk deposition av försurande ämnen och klimatförändringar. Olika förklaringar till vad som ligger bakom den ökande trenden ger konsekvenser vid kvantifiering av förindustriella nivåer och för förutsägelser om framtida koncentrationer, vilket i sin tur ger konsekvenser för vattenklassificering enligt Ramvattendirektivet, vattenförvaltning och dricksvattenberedning. För att kunna analysera de långsiktiga effekterna av industrialisering och klimatförändringar på TOC i ytvatten behövs långa tidsserier av data. Då den svenska miljöövervakningen endast sträcker sig tillbaka till mitten av 1980-talet måste andra tekniker användas för att rekonstruera data. I den här studien har sedimentproppar från 17 sjöar längs en klimat- och depositionsgradient analyserats med visible near infrared spektroskopi (VNIRS), en analysteknik som gör det möjligt att rekonstruera TOC-koncentrationer i ytvatten till förindustriell tid. En tidigare studie med VNIRS visade att TOC-koncentrationer sjönk till följd av försurande nedfall fram till 1980 då nedfallet kraftigt minskade, varefter koncentrationer av TOC började öka. Det noterades i studien att ökningen av TOC efter 1980 varit snabbare än vad minskningen var före 1980 på grund av försurande nedfall. Syftet med den här studien var därför att undersöka hypotesen att den senaste tidens ökning av TOC inte bara berott på minskat nedfall av försurande ämnen, utan även på grund av klimatförändringar. Det var möjligt att undersöka de långsiktiga effekterna av industrialisering och klimatförändringar på TOC i ytvatten genom att analysera rekonstruerad TOC data, klimatdata från början av 1900-talet, modellerad sulfatdepositionsdata och miljöövervakningsdata med uni- och multivariata analysmetoder. Resultaten visade att den senaste tidens ökning av TOC kunde förklaras med både en minskande deposition av försurande ämnen och en ökad nederbörd, medan ökande temperaturer kan ha haft en minskande effekt på TOC. Resultaten visade även att förändringshastigheten av TOC-koncentrationer varit snabbare i de norra, kalla delarna av Sverige och långsammare i de varmare södra. Resultaten indikerar att koncentrationer av TOC kommer att öka till nivåer som aldrig tidigare skådats, vilket är något vattenreningsverk kommer att behöva anpassa sina reningsmetoder till i framtiden.

Le supply chain management fait l'objet d'une attention particulière de la part des entreprises et des chercheurs notamment en sciences de gestion. Il s'articule autour de la mutualisation de ressources et des compétences de chaque membre de la supply chain et la synergie qui subsiste entre eux afin de créer collectivement une valeur supérieure à la somme des valeurs créées séparément par chacun. Cette alliance, qui nécessite la coopération collective dans la création et le partage équitable de la valeur, est caractérisée par des comportements opportunistes qui entraînent des défaillances comme l'effet Bullwhip. Ainsi, notre objectif est d'analyser ces comportements afin de comprendre leur dynamique au sein de la supply chain. A cet égard, nous nous appuyons sur la perspective des dilemmes sociaux pour proposer deux mécanismes : un mécanisme motivationnel (partage de l'identité de la supply chain) et un mécanisme structurel (investissement dans les ressources relationnelles) pour à la fois réduire et décourager l'opportunisme. Afin d'appuyer notre raisonnement, ces mécanismes sont articulés pour créer un capital social qui, en facilitant le supply chain management, permet d'améliorer la performance de la supply chain. Cela a donné lieu à la conception d'un modèle intégrateur de la dynamique sociale de la supply chain. Celui-ci a été validé auprès d'un échantillon de 130 répondants (Responsables supply chain, directeurs logistiques, etc.). Les données collectées ont été analysées tout d'abord par une analyse univariée, suivie d'une analyse en composantes principales afin d'épurer nos échelle de mesure. En second lieu, nous avons fait appel aux modèles d'équations structurelles PLS-PM (régressions aux moindres carrées partiels), pour estimer d'une part, la validité convergente ainsi que la validité discriminante des échelles de mesures, et d'autre part, valider nos hypothèses de recherche relatives aux antécédents et aux conséquences du capital social de la supply chain. Les résultats d'analyse nous ont permis de valider toutes les hypothèses selon lesquelles les deux mécanismes de résolution du dilemme social permettent de développer un capital social au sein de la supply chain qui, en agissant comme un lubrificateur des relations inter-organisationnelle, permet d'améliorer la performance de la supply chain. / Supply chain management is subject of particular interest to professionals and researchers especially in management science. It revolves around the sharing of resources and expertise between supply chain members, and the synergy that exists between them to collectively create value that is more than the sum of the values created separately by each member. This alliance, which requires collective cooperation in the creation and the equitable sharing of the value, is characterized by opportunistic behaviors that lead to failure, as illustrated by the Bullwhip effect. Thus, our objective is to analyze these behaviors in an attempt to understand their dynamics within the supply chain. In this regard, we rely on the perspective of social dilemmas to propose two mechanisms: a motivational mechanism (sharing the identity of the supply chain) and a structural mechanism (investment in relational resources) to discourage and reduce opportunism. To support our reasoning, these mechanisms are articulated to create social capital, facilitating supply chain management, in turn improving supply chain performance. This leads to the design of an integrative model of supply chain social dynamics. This was validated with a sample of 130 respondents (supply chain heads, logistics managers, etc.). The collected data were analyzed first by univariate analysis followed by principal component analysis to refine our scale. Second, we used PLS-PM (partial least squares regression) structural equation models to estimate, on one hand, the convergent and the discriminant validity of the measurement scales validity, and on the other hand, validate our research hypotheses on the antecedents and the consequences of social capital in the supply chain. The results of these analyses have allowed us to validate all the assumptions that the two mechanisms for resolving social dilemma help develop social capital within the supply chain, and act to lubricate inter-organizational relations, allowing improved supply chain performance.

O biodiesel tem sido amplamente utilizado como uma fonte de energia renovável, que contribui para a diminuição de demanda por diesel mineral. Portanto, existem várias propriedades que devem ser monitoradas, a fim de produzir e distribuir biodiesel com a qualidade exigida. Neste trabalho, as propriedades físicas do biodiesel, tais como massa específica, índice de refração e ponto de entupimento de filtro a frio foram medidas e associadas a espectrometria no infravermelho próximo (NIR) e espectrometria no infravermelho médio (Mid-IR) utilizando ferramentas quimiométricas. Os métodos de regressão por mínimos quadrados parciais (PLS), regressão de mínimos quadrados parciais por intervalos (iPLS), e regressão por máquinas de vetor de suporte (SVM) com seleção de variáveis por Algoritmo Genético (GA) foram utilizadas para modelar as propriedades mencionadas. As amostras de biodiesel foram sintetizadas a partir de diferentes fontes, tais como canola, girassol, milho e soja. Amostras adicionais de biodiesel foram adquiridas de um fornecedor da região sul do Brasil. Em primeiro lugar, o pré-processamento de correção de linha de base foi usado para normalizar os dados espectrais de NIR, seguidos de outros tipos de pré-processamentos que foram aplicados, tais como centralização dos dados na média, 1 derivada e variação de padrão normal. O melhor resultado para a previsão do ponto de entupimento de filtro a frio foi utilizando os espectros de Mid-IR e o método de regressão GA-SVM, com alto coeficiente de determinação da previsão, R2Pred=0,96 e baixo valor da Raiz Quadrada do Erro Médio Quadrático da previsão, RMSEP (C)= 0,6. Para o modelo de previsão da massa específica, o melhor resultado foi obtido utilizando os espectros de Mid-IR e regressão por PLS, com R2Pred=0,98 e RMSEP (g/cm3)= 0,0002. Quanto ao modelo de previsão para o índice de refração, o melhor resultado foi obtido utilizando os espectros de Mid-IR e regressão por PLS, com excelente R2Pred=0,98 e RMSEP= 0,0001. Para esses conjuntos de dados, o PLS e o SVM demonstraram sua robustez, apresentando-se como ferramentas úteis para a previsão das propriedades do biodiesel estudadas / Biodiesel has been widely used as a renewable energy source which contributes to the mineral diesel decrease demand. Therefore, there are several properties that must be monitored in order to produce and distribute biodiesel with the required quality. In this work, the biodiesel physical properties such as specific mass, refractive index and cold filter plugging point were measured and associated with near infrared spectroscopy (NIR) and mid-Infrared spectroscopy (mid-IR) spectra using chemometric tools. The Partial Least Squares Regression (PLS), Interval Partial Least Squares Regression (iPLS), and Support Vector Machines Regression (SVM) with variable selection by Genetic Algorithm (GA) methods were used to model the aforementioned properties. The biodiesel samples were synthesized from different sources such as canola, sunflower, corn, and soybean. Additional biodiesel samples were purchased from a Brazil South Region supplier. Firstly, the preprocessing baseline correction was used to normalize the NIR spectral data, following others preprocessing types were applied in such as the mean center, the first derivative and standard normal variate. The best result for predicting the cold filter plugging point was using Mid-IR spectra and GA-SVM regression method, with high coefficient determination of prediction, R2Pred = 0.94 and low value of the Root Mean Square Error of Prediction, RMSEP (C) = 0.7. For the specific mass prediction model, the best result was obtained using the Mid-IR spectrums and PLS regression, with the R2Pred = 0.98 and RMSEP (g/cm3) = 0.0002. As for a prediction model for the refractive index, the best result was obtained using the Mid-IR spectrums and PLS regression, with the R2Pred = 0.98 and RMSEP = 0.0001. For these datasets, the PLS and SVM models demonstrated theirs robustness, presenting themselves as useful tools for the biodiesel properties prediction studied

O biodiesel tem sido amplamente utilizado como uma fonte de energia renovável, que contribui para a diminuição de demanda por diesel mineral. Portanto, existem várias propriedades que devem ser monitoradas, a fim de produzir e distribuir biodiesel com a qualidade exigida. Neste trabalho, as propriedades físicas do biodiesel, tais como massa específica, índice de refração e ponto de entupimento de filtro a frio foram medidas e associadas a espectrometria no infravermelho próximo (NIR) e espectrometria no infravermelho médio (Mid-IR) utilizando ferramentas quimiométricas. Os métodos de regressão por mínimos quadrados parciais (PLS), regressão de mínimos quadrados parciais por intervalos (iPLS), e regressão por máquinas de vetor de suporte (SVM) com seleção de variáveis por Algoritmo Genético (GA) foram utilizadas para modelar as propriedades mencionadas. As amostras de biodiesel foram sintetizadas a partir de diferentes fontes, tais como canola, girassol, milho e soja. Amostras adicionais de biodiesel foram adquiridas de um fornecedor da região sul do Brasil. Em primeiro lugar, o pré-processamento de correção de linha de base foi usado para normalizar os dados espectrais de NIR, seguidos de outros tipos de pré-processamentos que foram aplicados, tais como centralização dos dados na média, 1 derivada e variação de padrão normal. O melhor resultado para a previsão do ponto de entupimento de filtro a frio foi utilizando os espectros de Mid-IR e o método de regressão GA-SVM, com alto coeficiente de determinação da previsão, R2Pred=0,96 e baixo valor da Raiz Quadrada do Erro Médio Quadrático da previsão, RMSEP (C)= 0,6. Para o modelo de previsão da massa específica, o melhor resultado foi obtido utilizando os espectros de Mid-IR e regressão por PLS, com R2Pred=0,98 e RMSEP (g/cm3)= 0,0002. Quanto ao modelo de previsão para o índice de refração, o melhor resultado foi obtido utilizando os espectros de Mid-IR e regressão por PLS, com excelente R2Pred=0,98 e RMSEP= 0,0001. Para esses conjuntos de dados, o PLS e o SVM demonstraram sua robustez, apresentando-se como ferramentas úteis para a previsão das propriedades do biodiesel estudadas / Biodiesel has been widely used as a renewable energy source which contributes to the mineral diesel decrease demand. Therefore, there are several properties that must be monitored in order to produce and distribute biodiesel with the required quality. In this work, the biodiesel physical properties such as specific mass, refractive index and cold filter plugging point were measured and associated with near infrared spectroscopy (NIR) and mid-Infrared spectroscopy (mid-IR) spectra using chemometric tools. The Partial Least Squares Regression (PLS), Interval Partial Least Squares Regression (iPLS), and Support Vector Machines Regression (SVM) with variable selection by Genetic Algorithm (GA) methods were used to model the aforementioned properties. The biodiesel samples were synthesized from different sources such as canola, sunflower, corn, and soybean. Additional biodiesel samples were purchased from a Brazil South Region supplier. Firstly, the preprocessing baseline correction was used to normalize the NIR spectral data, following others preprocessing types were applied in such as the mean center, the first derivative and standard normal variate. The best result for predicting the cold filter plugging point was using Mid-IR spectra and GA-SVM regression method, with high coefficient determination of prediction, R2Pred = 0.94 and low value of the Root Mean Square Error of Prediction, RMSEP (C) = 0.7. For the specific mass prediction model, the best result was obtained using the Mid-IR spectrums and PLS regression, with the R2Pred = 0.98 and RMSEP (g/cm3) = 0.0002. As for a prediction model for the refractive index, the best result was obtained using the Mid-IR spectrums and PLS regression, with the R2Pred = 0.98 and RMSEP = 0.0001. For these datasets, the PLS and SVM models demonstrated theirs robustness, presenting themselves as useful tools for the biodiesel properties prediction studied

Made available in DSpace on 2016-03-15T19:26:30Z (GMT). No. of bitstreams: 1 Anderson Luis Saber Campos.pdf: 1013366 bytes, checksum: 2e9d466c92f8d404ca44d38a91e676e8 (MD5) Previous issue date: 2007-09-11 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / From the theory on structure of capital and the application of structural equations a model was considered to evaluate the indebtedness of the public companies in Brazil. The effect of direct and indirect costs of bankruptcy, tax benefits, agency costs of free cash flow and the agency costs of borrowing. Computed the results, which was opted to analyzing an alternative model that indicates the relevance of the capital demand and offers effects in the level of companies indebtedness. One met evidences on the relevance of direct and indirect costs of bankruptcy and agency costs of borrowing in the determination of the capital structure in analyzed companies. / A partir da teoria sobre estrutura de capital e da aplicação de equações estruturais foi proposto um modelo para avaliar o endividamento das companhias abertas no Brasil. Foram considerados os efeitos das dificuldades financeiras, benefícios fiscais, agency de capital próprio e de capital de terceiros. Computado os resultados optou-se por analisar um modelo alternativo segundo o qual encontramos indícios e relevância dos efeitos da demanda e oferta de capital no nível de endividamento das empresas. Encontrou-se evidências que dificuldades financeiras e agency de capital de terceiros influem na determinação da estrutura de capital das empresas analisadas.

O objetivo deste estudo é investigar, de forma comparativa entre as categorias alimento e limpeza doméstica, os antecedentes da intenção do consumidor comprar marcas próprias, bem como analisar os efeitos da diferença nos níveis de risco percebido entre essas duas categorias de produtos na formação da intenção de compra. Para o alcance desse objetivo construiu-se um modelo com base em revisões da literatura sobre marcas próprias, bem como sobre risco percebido, imagem da loja, imagem da marca própria e atitudes, construtos identificados como os principais preditores da intenção de compra. O marco teórico permitiu a construção de hipóteses acerca dos principais relacionamentos existentes entre esses construtos no contexto de marcas próprias. A seguir foi realizada uma pesquisa empírica com o objetivo de testar tais hipóteses, utilizando um questionário auto-administrado elaborado com escalas já validadas na literatura. Esse levantamento de campo (survey) coletou opiniões de uma amostra não probabilística de 1.938 clientes de supermercados, composta por pessoas de ambos os gêneros e provenientes de 26 Estados do Brasil e do Distrito Federal, com predominância do Estado de São Paulo. Os resultados obtidos por meio de modelagem de equações estruturais utilizando a ferramenta Smart PLS demonstram que há relacionamentos significativos entre o risco percebido e a imagem da marca própria; entre a imagem da loja e imagem da marca própria; entre a imagem da marca própria e a atitude; e entre a atitude e a intenção de compra, validando as hipóteses de trabalho. O estudo também conclui que o risco percebido e a imagem da loja são fortes preditores da imagem da marca própria e da atitude a qual, por sua vez, é uma forte preditora da intenção de compra. Por fim, os resultados sugerem que a imagem da loja exerce maior influência na imagem da marca própria quando se trata da categoria alimentos, identificada como de menor risco percebido. Já na categoria limpeza doméstica, a cadeia mais relevante de antecedentes à intenção de compra por parte dos consumidores passa pelas relações entre risco percebido, imagem da marca e atitude frente a marcas próprias. Essas conclusões sugerem diferenças de intensidade, senão em natureza, nas relações entre os antecedentes psicológicos à intenção de compra do consumidor quando são consideradas categorias que se diferenciam no risco percebido pelo cliente, contribuindo para uma melhor compreensão teórica do fenômeno e sugerindo implicações gerenciais na adoção de estratégias de marketing por parte dos varejistas detentores de marcas próprias. / This study aims to investigate the antecedents of consumer´s intention to purchase private brands and analyze the effects of different perceived risk levels in intention formation by comparing food and house cleaning product categories. To attain to such goal a model was developed based on literature reviews about private brands, as well as perceived risk, store image, brand image, and attitudes, constructs identified as the main predictors for purchase intention. The theoretical framework allowed the construction of hypotheses about the key relationships among the constructs in the context of private brands. A survey was then designed and executed in order to test the hypotheses. A self-administered questionnaire was build with validated scales found in marketing literature. The empirical study collected opinions from a non-probabilistic sample of 1,938 private brands supermarket shoppers, comprising persons of both genders and from all 26 Brazilian states and the Federal District, predominating residents in the state of São Paulo. Results obtained by Structural Equation Modeling using Smart PLS suggest there are significant relationships between perceived risk and private brand image; between store image and brand image; between private brand image and attitude; and between attitude and purchase intention, validating the proposed hypotheses. The study also concluded that perceived risk and store image are strong predictors for private brand image and attitude which, in turn, is a strong predictor for purchase intention. Finally, results suggest that store image has more influence on private brand image when food products are the focused category as consumers present lower perceived risk toward it. For house cleaning products, the most relevant antecedents for consumer´s purchase intention form a chain of relations from perceived risk, brand image and attitude towards private labels. These findings suggest differences in intensity, if not in nature, on the relations among consumer´s psychological antecedents for purchase intention when categories that differ on perceived risk are considered. Such findings contribute to a better theoretical understanding of the phenomenon and suggest managerial implications for marketing strategies to retailers who hold private brands.

Lake volume and lake depth are important variables that defines a lake and its ecosystem. Sweden has around 100 000 lakes, but only around 8000 lakes has measured data for volume, max- and mean-depth. To collect data for the rest of the lakes is presently too time consuming and expensive, therefore a predictive method is needed. Previous studies by Sobek et al. (2011) have found a model predicting lake volume from map-derived parameters with high degrees of explanation for mean volume of 15 lakes or more. However, the predictions for one individual lake, as well as max- and mean-depth, were not accurate enough. The purpose with this study was to derive better models based on new map material with higher resolution. Variables used was derived using GIS-based calculations and then analyzed with multivariate statistical analysis with PCA, PLS-regression and multiple linear regression. A model predicting lake volume for one individual lake with better accuracy than previous studies was found. The variables best explaining the variations in lake volume was lake area and the median slope of an individual zone around each lake (R2=0.87, p<0.00001). Also, the model predicting max-depth from lake area, median slope of an individual zone around each lake and height differences in the closest area surrounding each lake, had higher degrees of explanation than in previous studies (R2=0.42). The mean-depth had no significant correlation with map-derived parameters, but showed strong correlation with max-depth. Reference Sobek, S., Nisell, J. & Fölster J. (2011). Predicting the volume and depths of lakes from map-derived parameters. Inland Waters, vol. 1, ss. 177-184.

Submitted by Nadir Basilio (nadirsb@uninove.br) on 2017-08-04T15:30:37Z No. of bitstreams: 1 Daniel de Lima Pires.pdf: 2531713 bytes, checksum: a3a021ded760a9272ed689161eec2e85 (MD5) / Made available in DSpace on 2017-08-04T15:30:37Z (GMT). No. of bitstreams: 1 Daniel de Lima Pires.pdf: 2531713 bytes, checksum: a3a021ded760a9272ed689161eec2e85 (MD5) Previous issue date: 2017-02-15 / Software projects are increasingly prominent in today's organizational environment. Its use refers to increased efficiency, improvements in products and services, and also the technological strategy of organizations. They are technically complex, do not have physical limitations and are intangible, nevertheless they are very ambitious and surrounded by uncertainties. Software projects teams must deal with a large amount of information, in addition to making intensive use of knowledge of several areas simultaneously, and also must be skilled in communicating and coordinating their actions. In this dissertation, a quantitative approach research using Structural Equation Modeling with Partial Least Squares (PLS-SEM) was carried out to evaluate the relationship between Teamwork quality and software projects success. The Teamwork quality is a construct that allows measuring the internal collaboration of the team within six dimensions: mutual support, contribution balancing, cohesion, communication, coordination and effort. Software projects success is a widely studied construct in the scientific literature, and in this dissertation was considered as composed of efficiency, impact on the consumer and impact on the team. The result obtained showed that the Teamwork quality exerts considerable influence on the software projects success, corroborating the results of previous academic research, and generating the knowledge that the collaboration should be fostered by the organizations in software development teams. In addition, as a contribution to practice, a model was proposed to evaluate the software project teams teamwork quality, aiming to increase the internal collaboration of the project team and, consequently, the success of the software project. / Projetos de software são cada vez mais expoentes no atual ambiente organizacional. Seu uso remete ao aumento da eficiência, melhorias em produtos e serviços, e também a estratégia tecnológica das organizações. São tecnicamente complexos, sem limitações físicas e intangíveis, não obstante são muito ambiciosos e cercados de incertezas. Assim, as equipes de projetos de software devem lidar com uma grande quantidade de informações, além de fazerem uso intensivo do conhecimento de várias áreas simultaneamente, e por isso devem ser hábeis na comunicação e coordenação de suas ações. Nesta dissertação foi realizada uma pesquisa com abordagem quantitativa utilizando Modelagem de Equações Estruturais com Mínimos Quadrados Parciais (PLS-SEM) para testar a relação da Qualidade do trabalho em equipe com o Sucesso dos projetos de software. A Qualidade do trabalho em equipe é um construto que permite mensurar a colaboração interna da equipe a partir de seis dimensões: apoio mútuo, balanceamento de contribuições, coesão, comunicação, coordenação e esforço. O Sucesso em projetos de software é um construto amplamente estudado na literatura científica, e nesta dissertação foram consideradas as dimensões: eficiência, impacto no consumidor e impacto na equipe do projeto. O resultado obtido mostrou que a Qualidade do trabalho em equipe exerce influência considerável no Sucesso dos projetos de software, corroborando os resultados de pesquisas acadêmicas anteriores, e gerando o conhecimento de que a colaboração deve ser fomentada pelas organizações nas equipes de desenvolvimento de software. Adicionalmente foi proposto, como contribuição para prática, um modelo para avaliação da Qualidade do trabalho em equipe para equipes de Projetos de software, visando o aumento da colaboração interna da equipe do projeto e, consequentemente do Sucesso dos projetos de software.

De nombreux constats contemporains s’alarment du malaise récurrent des ressources humaines hospitalières, particulièrement à l’endroit des médecins et des soignants, et par conséquent du risque de mauvaise qualité de prise en charge des patients. Adoptant une approche plus optimiste, des chercheurs américains en soins infirmiers ont mis en évidence depuis le début des années 1980 l’existence d’hôpitaux dits magnétiques, parce qu’attractifs et fidélisateurs, et où il ferait bon travailler et se faire soigner. Cette thèse vise à approfondir le concept de Magnet Hospital, à éclairer sa définition et sa portée pour la gestion des ressources humaines hospitalières en France. Suivant une démarche hypothético-déductive, la conceptualisation, fondée sur un état de l’art, débute par une appropriation du modèle synthétique du Magnet Hospital. Empruntant une perspective psychosociale, notre modèle original de recherche se focalise sur la perception, à l’échelle des unités de soins, des attributs managériaux du magnétisme hospitalier (leadership transformationnel, empowerment perçu de la participation et climat relationnel collégial entre médecins et soignants) et ses conséquences attitudinales positives (satisfaction, implication, intention de rester, équilibre émotionnel travail/hors travail et efficacité collective perçue). Une méthodologie quantitative interroge au moyen de 8 échelles ad hoc un échantillon représentatif de 133 médecins, 361 infirmières et 362 aides-soignantes de 36 services de médecine polyvalente français. Une série de modélisations par équations structurelles, selon l’algorithme Partial Least Squares, teste la nature et l’intensité des relations directes et indirectes du magnétisme managérial perçu. Les résultats statistiques indiquent une bonne qualité des construits et d’ajustement des modèles. Un contexte managérial magnétique produit son principal effet positif sur l’efficacité collective perçue. Des différences catégorielles existent quant à la perception de sa composition et à la transmission de ses effets par la médiation de l’efficacité collective perçue, signalant le caractère contingent du magnétisme. Ces résultats ouvrent des perspectives managériales et scientifiques, en soulignant l’intérêt des approches positives de l’organisation hospitalière. / Many contemporary findings are alarmed of the recurring discomfort of hospital human resources, especially against doctors and nurses, and consequently against risk of poor quality of care for patients. Adopting a more optimistic approach, American nursing scholars have highlighted since the 1980s, some magnet hospitals, able to attract and retain, and with good working and care conditions. This thesis aims to explore Magnet Hospital concept, to inform its definition and scope for hospital human resource management in France. According to a hypothetico-deductive approach, based on a review of the literature, the conceptualization begins with appropriation of synthetic Magnet Hospital model. Under a psychosocial perspective, our original research model focuses on perception of managerial magnetic attributes (transformational leadership, perceived empowerment of participation, collegial climate between doctors and nurses) and their consequences on positive job attitudes (satisfaction, commitment, intent to rest, emotional equilibrium work/family, perceived collective efficacy), at wards level. A quantitative methodology proceeds by a questionnaire of 8 ad hoc scales and interviews 133 doctors, 361 nurses, 362, auxiliary nurses, in 36 French medicine units. A set of structural equations modeling, according to Partial Least Squares, tests nature and intensity of direct and indirect relationships of perceived managerial magnetism. The statistical results show a good validity of constructs and a good fit of models. The major positive effect of magnetic managerial context is on perceived collective efficacy. Some professional differences exist about perceptions of composition and transmission of magnetic effects (via mediation of perceived collective efficacy), indicating the contingency of magnetism. These findings open managerial and scientific opportunities, emphasizing the interest for positive organizational approach of hospital.

The more digital the healthcare sector gets, the more considerable is the need for good information security within the sector. A group that, already during its education, gets in contact with sensitive information is medical students. Previous studies show that medical students run a significant risk of mishandling sensitive information during their medicinal internship. The goal of this study is to investigate what level of knowledge the medicinal students possess about information security and to see to what extent that affects their attitude towards information security and behavior in information security contexts. A survey based research method is used with an online questionnaire and the study has its theoretical base in the knowledge-attitude-behavior model and in prior studies performed within the same area of research. The questionnaire is created with inspiration from the HAIS-Q, which is an already tested questionnaire that is used to examine information security awareness. The result shows that the medicinal students have a higher level of knowledge about information security compared to their attitude towards information security and behavior in information security contexts. The result also indicates that higher levels of knowledge lead to better attitudes and behaviors. A recommendation for further studies within the topic is suggested, preferably on a larger sample where researchers can look at differences between universities in order to get a more holistic picture of the situation. The HAIS-Q should be evaluated more thoroughly as a research method since this study identifies shortcomings associated with the method. / Med ökad digitalisering inom vården ökar behovet av god informationssäkerhet inom hälso- och sjukvård. Läkarstudenter är en grupp som redan under sin utbildning kommer i kontakt med mycket känslig information och studier visar på att studenter inom hälso- och sjukvård löper stor risk att hantera känslig information felaktigt under sin praktik. Syftet med den här studien är att mäta hur bra kunskap läkarstudenter har om informationssäkerhet och hur stor inverkan detta har på deras attityd och beteende i informationssäkerhetsfrågor. För att testa detta utförs en enkätundersökning online med teoretisk utgångspunkt i kunskap-attityd-beteende-modellen samt tidigare studier gjorda inom samma område. Enkäten utformas med stor inspiration från HAIS-Q, vilket är en beprövad enkätmetod för att mäta informationssäkerhetsmedvetenhet. Resultatet visar på att läkarstudenterna uppvisar bättre kunskap än attityd och beteende i informationssäkerhetsfrågor. Genom studien identifieras även att kunskap har en positiv inverkan på attityd och beteende, där det går att se att ökad kunskap leder till bättre attityd och beteende. Slutsatserna innefattar bland annat rekommendationer om fortsatta undersökningar inom området med större urvalsgrupp där jämförelser mellan olika lärosäten bör göras för att få en med holistisk bild av situationen. En mer noggrann utvärdering av HAIS-Q som enkätmetod bör också genomföras då denna undersökning identifierar brister med metoden.