Major changes with regards to digitalization and new customer behaviours have transformed the retail industry in many ways. One of the latest trends in retail is the focus on omnichannel, in order to stay competitive in today's changing market conditions. Omnichannel is about creating a seamless distribution and experience for the customers between channels. These changes that come with digitalization come with strategical and developmental challenges. As well as an increased pressure to work more efficiently and at an accelerated speed to cope with new trends. This can be hard to accomplish, to embark into unknown territory since no organization truly has reached omnichannel. Whilst speed and innovation play a vital part in adapting to new rules of conduct within retail, risk management is still a part of their project management tasks. The purpose of this thesis is to explore how management is working with handling risks that can occur in the transition processes to omnichannel. This thesis is based on a qualitative research design where seven semi-structured interviews have been conducted with managers from various large Swedish retail organizations. The conclusion shows three main themes from the empirical findings, which are the following: Operational risks are more common and manageable than strategical, Depending on project scope; risk assessment and mitigation differs and the diversity and roles of employees.

Orientador: Denis José Schiozer / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-19T21:21:13Z (GMT). No. of bitstreams: 1 Silva_LucianadosSantos_M.pdf: 12675920 bytes, checksum: 63532a17aa12aa538936a8b7e2f0b435 (MD5) Previous issue date: 2011 / Resumo: A grande quantidade de incertezas presente na modelagem de reservatórios gera riscos na previsão de comportamento de um campo de petróleo. Assim, torna-se imprescindível o ajuste de histórico, que é a calibração do modelo de simulação do reservatório com os dados dinâmicos observados, aproximando o modelo da realidade e gerando previsões mais confiáveis. Diversas metodologias surgiram para integrar a análise de incertezas com o ajuste de histórico, mas devido à complexidade do processo, algumas delas só se aplicam a casos simples. A proposta deste trabalho é aplicar os métodos desenvolvidos por Moura Filho (2006), Becerra (2007) e Maschio et al. (2010) em um caso complexo sintético, similar a um modelo real de um reservatório de petróleo e avaliá-los para propor melhorias na metodologia. A técnica consiste em utilizar as diferenças entre os dados de produção observados e os simulados para reduzir as incertezas do reservatório, calculando as probabilidades dos níveis dos parâmetros incertos. Para isso, os atributos incertos são discretizados em três níveis e é feita uma análise de sensibilidade para escolher os atributos críticos, os quais são combinados através da árvore de derivação para gerar os diferentes modelos de simulação. Com os dados históricos (medidos) e simulados destes modelos, é feita a redistribuição das probabilidades dos níveis utilizando e comparando dois métodos: o de Moura Filho e Becerra (Método 1) e o de Maschio et al. (Método 2). Os resultados deles não mostraram boa eficiência na redução das incertezas para o caso estudado, pois as curvas continuaram muito espalhadas com relação ao histórico. Sendo assim, foram criados o Método 3, utilizando as melhores práticas da formulação dos dois estudados com o objetivo de tornar a metodologia mais robusta para uso em casos reais, e o Método 4, que é uma reaplicação do Método 3 após a redefinição dos valores dos níveis dos atributos. Uma comparação dos resultados dos quatro métodos mostra a evolução da redução das incertezas. Além disso, consegue-se diminuir a dispersão dos modelos representativos, centralizando-os com relação ao histórico de produção, o que permite uma melhor previsão de produção e maior confiabilidade na análise de risco de projetos futuros / Abstract: The large amount of uncertainties in reservoir modeling increases petroleum production forecast risks. Therefore, the history matching, which refines the simulation model to closely reproduce production data, is a vital procedure once it approximates numerical models to reality providing reliable predictions. Many methodologies were developed to integrate uncertainty analysis and history matching in order to mitigate the reservoir uncertainties by using the observed data, but due to the process complexity, some of them are applicable only in simple cases. In this context, the present work aims to evaluate the application of existing methods, developed by Moura Filho (2006), Becerra (2007) and Maschio et al. (2010), in a synthetic complex model (i.e. similar to a real field) and propose new methods with some improvements to be applied in real cases of the petroleum industry. The main characteristic of these methods is the use of differences between observed and simulated data to recalculate the probabilities distribution of uncertain parameters with the purpose of reducing reservoir uncertainties. To apply the methods, the uncertainty attributes are discretized in three levels and a sensibility analysis is done to select the critical attributes, which are combined by a derivative tree generating different simulation models. With history and simulated data of these models, the redistribution of occurrence probabilities is made with different formulas: Moura Filho e Becerra (Method 1) and Maschio et al. (Method 2). These two methods are compared and their results don't show good efficiency in uncertainty reduction of the studied case, because the final curves remain widely scattered around history data. Then, two methods are proposed, Method 3, which combines the best practices of the two reviewed ones, making it robust to be used in real cases with a great number of wells and production functions to be adjusted such as water production and pressure. The second proposed one, Method 4, is a reapplication of the third method with a redefinition of attribute values in order to refine the results. A comparison of the results of the four methods shows an evolution in the uncertainty reduction. Besides that, there is a decrease in the dispersion of the representative curves, which are centralized around the history data, providing a better production forecast and greater reliability in risk analysis of future projects / Mestrado / Reservatórios e Gestão / Mestre em Ciências e Engenharia de Petróleo

Chronic seismic hazards and resulting secondary impacts as natural conditions of the country, and loss of robust building and prudent settlement practices as aggravated by rapid population growth make cities the most vulnerable geographical and social entities in Turkey. In contrast, Turkish disaster policy is solely focused on post-disaster issues and no incentives or provision exist to encourage risk analysis or risk mitigation approaches, despite current international efforts. For the development of risk reduction policies an essential step is to prioritize settlements according to their vulnerability levels. This could be determined by hazard probabilities and attributes of the building stock of each settlement. Measurement of vulnerability levels allows the ordering of settlements into risk categories. Vulnerability levels of settlements are then assumed to depend on a number of attributes of cities to explore if vulnerability could be related to a set of urban properties. Results of statistical analyses indicate that total building loss is related to the ratio of population over the total number of buildings in mid-range settlements, and directly related to population in metropolitan cities. Relative loss on the other hand is related with rate of agglomeration and development index in almost every size category of settlements. Observations provide guiding principles for effective mitigation practices in Turkey by ordering settlements and offer means of differential implementation. These could contribute to improved safety measures in urban standards, building codes, building supervision procedures, insurance systems, investment priorities, and Law (6306) on Redevelopment of Areas under Disaster Risk.

Shire of Murray has concerns regarding the negative impact that a 100 year flood could have on existing structures built before 1997. The increase cost in construction due to landfill has an adverse effect on development in Pinjarra. Feasibility of constructing a diversion channel at upstream of Murray River to attenuate the flood level from 1 in 100 year ARI to 1 in 50 year ARI, was investigated by Kiong (2003). The Murray River Water Surface Profile along three kilometres south of Greenlands Road was modelled. Flood damages on each flood occurrence were assessed and Average Annual Damage (AAD) was calculated. The AAD is used to estimate the monetary benefit against the construction cost of the diversion channel. Groundwater along Greenlands and Fauntleroy Drains was also modelled to determine the viable depth of the designed channel, as well as the analysis of backwater. The proposed channel is designed at different scenarios (invert level at breakout point, culvert or causeway design, and diversion channel variations). The benefit cost ratio of the proposed diversion channel is calculated. Other mitigation options are suggested including detention basins for structural measure, or building a new flood-proof township for non-structural measure.