The objective of this thesis is to investigate and describe components of pricing system which influence the dynamic performance of a price leader manufacturing firm in an oligopoly capital intensive industry producing an identical intermediate product (s). The synthetic fibre industry is chosen as an illustrative case upon which the discussion is built. However, this work could generally be applied to a wide variety of organizations and situations. After discussing the suitability of system dynamics to the formulation of long-run pricing strategy, a model of the pricing system is constructed by using this technique. The behaviour of this system is examined in terms of feedback loops. That is to illustrate how the characteristics of these loops and the interaction among them affect the dynamic behaviour of the system, and how this behaviour can be improved via changing the components of these loops and/or their structures. The improved system is simulated under different external disturbances, certain parameter changes, and different pricing control policies. The simulation shows that the design of a set of robust pricing policies makes the system insensitive to external disturbance and error in parameters. It also shows that the ability of the firm to attain its growth and profitability objectives is affected by the chosen control pricing policies. Some potential applications of the model, particularly, as planning and training tools are highlighted. It is concluded that System Dynamics is an appropriate approach to the formulation of the long-run pricing strategies.

In this work, we investigate the active vibration isolation and damping of sensitive equipment. Several single-axis isolation techniques are analyzed and tested. A comparison between the sky-hook damper, integral force feedback, inertial velocity feedback and LagLead control techniques is conducted using several practical examples. The study of single-axis systems has been developed and used to build a six-axis isolator. A six degrees of freedom active isolator based on Stewart platform has been designed manufactured and tested for the purpose of active vibration isolation of sensitive payloads in space applications. This six-axis hexapod is designed according to the cubic configuration; it consists of two triangular parallel plates connected to each other by six active legs orthogonal to each other; each leg consists of a voice coil actuator, a force sensor and two flexible joints. Two different control techniques have been tested to control this isolator : integral force feedback and Lag-Lead compensator, the two techniques are based on force feedback and are applied in a decentralized manner. A micro-gravity parabolic flight test has been clone to test the isolator in micro-gravity environment. ln the context of this research, another hexapod has been produced ; a generic active damping and precision painting interface based on Stewart platform. This hexapod consists of two parallel plates connected to each other by six active legs configured according to the cubic architecture. Each leg consists of an amplified piezoelectric actuator, a force sensor and two flexible joints. This Stewart platform is addressed to space applications where it aims at controlling the vibrations of space structures while connecting them rigidly. The control technique used here is the decentralized integral force feedback.

Providing care services across several departments and care givers creates the complexity of the patient pathways, as it deals with different departments, policies, professionals, regulations and many more. One example of complex patient pathways (CPP) is one that exists in integrated care, which most literature relates to health and social care integration. The world population and demand for care services have increased. Therefore, necessary actions need to be taken in order to improve the services given to patients in maintaining their quality of life. As the complexity arises due to different needs of stakeholders, it creates many problems especially when it involves complex patient pathways (CPP). To reduce the problems, many researchers tried using several decision tools such as Discrete Event Simulation (DES), System Dynamic (SD), Markov Model and Tree Diagram. This also includes Direct Experimentation, one of techniques in Lean Thinking/Techniques, in their efforts to help simplify the system complexity and provide decision support tools. However, the CPP models were developed using a single tools which makes the models have some limitations and not capable in covering the entire needs and features of the CPP system. For example, lack of individual analysis, feedback loop as well as lack of experimentation prior to the real implementation. As a result, ineffective and inefficient decision making was made. The researcher also argues that by combining the DES and SD techniques, named the hybrid simulation, the CPP model would be enhanced and in turn will help to provide decision support tools and consequently, will reduce the problems in CPP to the minimum level. As there is no standard framework, a framework of a hybrid simulation for modelling the CPP system is proposed in this research. The researcher is much concerned with the framework development rather than the CPP model itself, as there is no standard model that can represent any type of CPP since it is different in term of its regulations, policies, governance and many more. The framework is developed based on several literatures, selected among developed framework/models that have used combinations of DES and SD techniques simultaneously, applied in a large system or in healthcare sectors. This is due to the condition of the CPP system which is a large healthcare system. The proposed framework is divided into three phases, which are Conceptual, Modelling and Models Communication Phase, and each phase is decomposed into several steps. To validate the suitability of the proposed framework that provides guidance in developing CPP models using hybrid simulation, the inductive research methodology will be used with the help of case studies as a research strategy. Two approaches are used to test the suitability of the framework – practical and theoretical. The practical approach involves developing a CPP model (within health and social care settings) assisted by the SD and DES simulation software which was based on several case studies in health and social care systems that used single modelling techniques. The theoretical approach involves applying several case studies within different care settings without developing the model. Four case studies with different areas and care settings have been selected and applied towards the framework. Based on suitability tests, the framework will be modified accordingly. As this framework provides guidance on how to develop CPP models using hybrid simulation, it is argued that it will be a benchmark to researchers and academicians, as well as decision and policy makers to develop a CPP model using hybrid simulation.

L'expérience montre que les technologies de l'information et des communications (TIC), et services de télécommunications mobiles en particulier, peuvent stimuler une croissance économique soutenue et contribuer au développement humain. Au coeur du secteur des TIC, les technologies mobiles sont de plus en plus utilisées comme un outil transformationnel pour favoriser la croissance économique, accélérer le transfert des connaissances, développer les capacités locales, améliorer la productivité et réduire la pauvreté dans de nombreux secteurs. À cet égard, au cours de la dernière décennie, le développement des TIC est devenu un domaine stratégique d'engagement politique dans les économies émergentes. Afin d'accompagner les décideurs politiques et les marketeurs dans la conception des stratégies optimales de développement du secteur des télécommunications, les chercheurs s’intéressent de plus en plus aux obstacles entravant le déploiement des solutions TIC dans le monde en voie de développement. En tant que contribution à ce domaine de recherche, cette étude vise à (i) identifier les déterminants économiques et socioculturels affectant la capacité des pays émergents à adopter les nouvelles technologies et innovations, et à (ii) proposer des principes d’actions et de politiques susceptibles de favoriser la diffusion des solutions TIC dans les pays émergents qui sont caractérisés par une forte inégalité des revenus et par l'aversion au risque. / Evidence shows that information and communications technologies (ICT), especially mobile telecommunications services, can lead to sustained economic growth and human development. Mobile technologies are increasingly used as a transformational tool to foster economic growth, accelerate knowledge transfer, develop local capacities, raise productivity, and alleviate poverty in a variety of sectors. In that respect, in the last decade, ICT development has become a key strategic area for policy engagement in emerging economies. To support policy-makers and marketing practitioners in designing optimal telecommunications sector development strategies, an increasing research focus is now being placed on the impediments to implementing ICT solutions in the developing world. As a contribution to this field of research, this study aims at (i) identifying the economic and socio-cultural determinants affecting the capacity of developing countries to adopt new technologies and innovations, and at (ii) defining relevant policy principles likely to foster the diffusion of ICT solutions in emerging economies that are characterized by strong income inequality and uncertainty avoidance.

The main goal of this thesis is to create management flight simulator for inventory management in selected company. The proposed management simulator is developed in the context of the taxonomy of decision support systems. It is a model-oriented system based on the models proposed by me and created a user interface. In this particular situation the application is realized on company Dynavix, that is a manufacturer of navigations. After opening theoretic information about models, computer technologies for systems modeling and individual phases of simulation process, there follows a case study. It is trying to find and recommend appropriate solutions of fluctuations in the need for planning the purchase of navigation Dynavix by using a system dynamics approach (developed model and its testing). The recommended solution is verified by testing hypotheses according to a predefined test scenarios.

The paper examines the behavior of the supply chain through a system dynamic model. The theoretical part presents system dynamics, the Beer game and the simulation environment in which the model was created. In the practical part, the response of five surveyed decision-making order rules on the 4 patterns of demand is analyzed.

The current transportation infrastructure in most cities and municipalities is not designed to cope with the continually increasing volume of traffic, especially during rush hours. Furthermore, in many cases, the increasing pressure has not yet been adequately compensated by sufficient expansion. The dynamic nature of this problem makes it very challenging to solve. Therefore, the purpose of this work is to investigate the causes and effects and their dynamics of the increasing strain on transportation infrastructure in suburban municipalities. This research is necessary in order to determine what needs to be changed to reduce traffic congestion effectively. Moreover, this study assesses the expectations of commuters regarding mobility. It is essential to take their opinions into account, as they are a significant cause of traffic congestion. Therefore, they need to accept any implemented solution in order to ensure a high adoption rate. In the process, the dynamics of the system and the opinions of commuters result in conceptual solutions aimed at improving the traffic situation in the long term.   The research involved conducting a single case study in a suburban municipality of the German city of Munich. In the course of this research, primary data was collected by means of a commuter survey and secondary data was also provided from an existing household survey. Moreover, empirical data was collected through a literature review as well as from numerous recognised online sources. The causes and effects of traffic dynamics were analysed by considering traffic as a system using Systems Thinking and System Dynamics methodology. The interrelated variables were visualised by creating a Causal Loop Diagram and drawing conclusions from it. In addition, conceptual solutions were developed by reviewing the works of previous researchers and taking into account the results from the System Dynamics analysis. The results of the commuter survey also played a crucial role in ascertaining the commuting habits and expectations of commuters regarding the transportation infrastructure.   The analysis of the Causal Loop Diagram revealed that in order to reduce traffic congestion, road expansion alone is not a viable solution due to rebound effects, which eventually result in increased car use and hence more traffic congestion. Therefore, in order to solve the problem in the long term, car use needs to be reduced to a significant degree. This can be achieved by implementing various solutions to nudge people towards using alternative modes of transport. Various pricing techniques such as free public transport are a possible method of approaching this topic. Furthermore, improving public transportation services and infrastructure using digitalisation and centralising various alternative modes of transport are among a number of appropriate ways of effectively reducing the traffic congestion problematic studied in this project. Hereby, the method of Change Management, usually used within organisations, can be applied to change the behaviour of society.

<p>In the U.S., bioenergy accounts for about 50% of the total renewable energy that is generated. Every stage in the life cycle of using bioenergy (e.g., growing biomass, harvesting biomass, transporting biomass, and converting to fuels or materials) has consequences in terms of the three dimensions of sustainability: economy, environment, and society. An integrated sustainability model (ISM) using system dynamics is developed for a bioenergy system to understand how changes in a bioenergy system influence environmental measures, economic development, and social impacts.<br></p><p><br></p><p>Biomass may be used as a source of energy in a variety of ways. The U.S. corn ethanol system forest residue system for electricity generation, and cellulosic ethanol system have been investigated. Predictions, such as greenhouse gas (GHG) savings, soil carbon sequestration, monetary gain, employment, and social cost of carbon are made for a given temporal scale. For the corn ethanol system, the annual tax revenue created by the ethanol industry can offer a significant benefit to society. For the forest residue system for electricity generation, different policy scenarios varying the bioenergy share of the total electricity generation were identified and examined via the ISM. The results of the scenario analysis indicate that an increase in the bioenergy contribution toward meeting the total electricity demand will stimulate the bioenergy market for electricity generation. For the cellulosic ethanol system, the compliance of cellulosic ethanol can be achieved under the advanced bioconversion technologies and the expansion of energy crops. However, nitrate leaching and biodiversity change should be considered when expanding energy crops on marginal land, pasture, and cropland. Moreover, three bioenergy systems reduce GHG emissions significantly, relative to fossil fuel sources that are displaced, and create economic benefits (e.g., GDP and employment). Additionally, a spatial agent-based modeling is developed to understand farmers’ behaviors of energy crop adoption and the viability of cellulosic biofuel commercialization.<br></p>

Profundas transformações na política energética brasileira têm motivado a revitalização da indústria naval no Brasil. Novos estaleiros estão surgindo em diferentes regiões do país e todos, sem exceção, terão o desafio de aprender com a experiência e, paulatinamente, formar sua força de trabalho. Neste início, que além de árduo é decisivo para o futuro dos estaleiros, é fundamental que se comece a partir das diretrizes corretas, respeitando as mesmas regras básicas que selecionaram os estaleiros que hoje se encontram em posição de destaque no mundo. Os estaleiros japoneses, por exemplo, ergueram as suas bases em um ambiente econômico pós-guerra extremamente restritivo e cheio de dificuldades, mas que os obrigou a desenvolverem um novo paradigma industrial que eliminou desperdícios e possibilitou um salto no desenvolvimento tecnológico e na produtividade na construção naval. Desde então, especialmente após as duas crises do petróleo, a busca pela produtividade em um estaleiro, não é apenas uma questão de competitividade e diferenciação perante os concorrentes, mas um fator de sobrevivência, uma vez que a indústria de construção naval é global e extremamente competitiva em preço, prazo, qualidade, tecnologia e produtividade. Normalmente a produtividade na construção naval é expressa na forma inversa da produtividade parcial da mão de obra (HH/CGT), não por acaso, pois, além da influência de melhores práticas produtivas, sabe-se que o desempenho da força de trabalho representa importante parcela na produtividade de um estaleiro. Neste sentido, esta pesquisa propõe-se a desenvolver um modelo simplificado através da Dinâmica de Sistemas que possibilite simular o comportamento dinâmico da produção, da força de trabalho e da produtividade em um estaleiro para avaliar, através da experiência de modelagem e dos resultados das simulações, cenários que permitam mostrar direções que favoreçam seu aprendizado em produtividade e garantam sua sustentabilidade em função de seu desempenho no longo prazo. A razão desta proposta é explorar algumas das causas que determinam o comportamento dinâmico das curvas de aprendizado dos estaleiros, para então traçar algumas diretrizes que indiquem o caminho para o aprendizado sistêmico. A partir de uma seleção das alavancas para a aprendizagem em produtividade, foram selecionadas cinco diretrizes para estaleiros que tenham o objetivo da aprendizagem, todas relacionadas de alguma maneira com algum aspecto da força de trabalho que são: respeitar os limites do crescimento da força de trabalho, reter experiência e aumentar o seu aproveitamento, criar condições para alavancar o aprendizado da força de trabalho, facilitar a transferência do aprendizado da força de trabalho para o aprendizado da produção e que o aprendizado através de rotinas e processos de produção seja realizado em conjunto com o aprendizado das pessoas. A principal contribuição deste trabalho é a demonstração, através do processo de modelagem e dos resultados da simulação, de um conceito amplamente divulgado pelas teorias de aprendizagem organizacional, de que a origem do aprendizado está nas pessoas e, portanto, são estas os elementos mais importantes do estaleiro. O modelo também ajuda a replicar o paradoxo de que o estaleiro não depende de uma pessoa em específico, mas depende completamente do conjunto formado por todas as pessoas que lá trabalham. Portanto, conforme o pensamento sistêmico define as organizações de aprendizagem, o estaleiro deve ser pensado como um sistema de aprendizagem, em que o desenvolvimento das pessoas é realizado em todos os níveis e o aprendizado ocorre junto com o processo produtivo. / Profound changes in Brazil\'s energy policy have motivated the revitalization of the shipbuilding industry in Brazil. New shipyards are springing up in different regions of the country and all, without exception, have the challenge of learning from experience and gradually train their workforce. At this moment, that is decisive for the shipyards future, it is essential to start from the correct guidelines, respecting the same basic rules that selected established yards which are now in a prominent position in the world shipbuilding market. The Japanese shipyards, for instance, raised its bases in a post-war economic environment extremely restrictive and full of difficulties, but they were compelled to develop a new industrial paradigm that eliminated waste and enabled a leap in technological development and productivity in the shipbuilding process. Since then, especially after the two oil crises, the race for productivity in world yards, is not just a matter of competitiveness and differentiation against competitors, but a survival factor in the shipbuilding industry, now a global industry and extremely competitive in price, time, quality, technology and performance. In the shipbuilding industry, productivity is usually expressed as the inverse ratio of partial labor productivity (or MH/CGT), not only by the influence of best production practices, but also by workforce performance that plays an important share in a shipyard productivity indexes. Therefore, this research proposes to develop a simplified model using System Dynamics practices that allows to simulate the dynamic behavior of production, labor and productivity in a shipyard to assess, through the experience of modeling and simulating, a set of scenarios and show directions to promote learning in productivity and ensure shipyard sustainability in terms of its performance in the long run. The reason for this proposal is to explore some of the causes that determine the dynamic behavior shipyard learning curves, and then draw some guidelines that indicate the path to the systemic learning. From a selection of leverage points for learning productivity, we selected five guidelines for shipyards that have the learning goal, all related in some way with some aspect of the workforce which are: respect the limits of growth of the labor force, retain and increase workforce experience used by learning process, create conditions to empower the learning of the workforce, facilitate the transfer of learning from the workforce to the production learning through frameworks, routines and ensure that production learning is conducted in the same time of individuals learning once they have make concepts and implement new production process. The main contribution of this study is to demonstrate, through the process of modeling and simulation results, a concept widely publicized by the theories of learning organizations, that the source of learning is in people and, therefore, they are the most important elements in the shipyard. The model also helps to replicate the paradox that the shipyard does not depend on any specific person, but depends completely on all shipyard people. Therefore, as defined by systems thinking theories about learning organizations, the shipyard should be thought of as a learning system, where people at all levels are developed and learning occurs in the same time as the production process.

Modelos preditivos de mercado são ferramentas importantes para tomadores de decisões no âmbito público e privado. Devido à complexidade dinâmica do mercado imobiliário, composta pela interação de dois submercados distintos (mercado de ativos imobiliários e mercado de consumo de espaço) e pela limitação de dados disponíveis, o estudo analítico de mercados imobiliários requer a modelagem paramétrica de um sistema de equações que os descrevam, seguido pela identificação dos parâmetros deste sistema utilizando dados reais de uma região. Neste trabalho, estudamos o modelo dinâmico de mercado imobiliário proposto por Wheaton (1999), criado a partir do popular modelo de quatro quadrantes de autoria de DiPasquale e Wheaton (1996). Utilizamos técnicas de identificação de sistemas para elaborar um modelo de aprendizado para o estoque imobiliário, e o implementamos em Matlab. Aplicamos o método elaborado em dados simulados, para validá-lo, e então aplicamos o mesmo método, com adaptações, em dados reais do mercado imobiliário canadense. Os resultados obtidos validam o método de identificação de sistema dinâmico quando testado em dados simulados, e corroboram o modelo de Wheaton (1999) como modelo preditivo em dados reais. Ademais, os resultados indicam que um modelo que seja capaz de entender a evolução dinâmica dos parâmetros estáticos do modelo de Wheaton (1999), poderia melhorar os resultados deste como ferramenta preditiva. / Predictive market models are important tools for decision-makers in the public and private spheres. Due to the dynamic complexity of the real estate market, consisting of the interaction of two distinct submarkets (real estate asset market and space consumption market) and the lack of real estate data, the analytical study of real estate markets requires the parametric modeling of a system of equations describing them, followed by the identification of the parameters of this system using real data from a region. In this work, we study the dynamic real estate market model proposed by Wheaton (1999), created from the popular four-quadrant model of DiPasquale e Wheaton (1996). We use system identification techniques to develop a learning model for real estate inventory data, and implement it in Matlab. We apply the method devised in simulated data to validate it, and then apply the same method with adaptations in real data of the Canadian real estate market. The results validate the dynamic system identification method when tested in simulated data, and corroborate the Wheaton (1999) model as a predictive model in real data. In addition, the results indicate that a model that is able to understand the dynamic evolution of the static parameters of the Wheaton (1999) model, could improve its results as a predictive tool.