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.

This diploma thesis analyzes the information system of FCC Environment CEE and is focused on a detection of risks and other imperfections of the system. The result of the thesis should be a proposal for a change which may lead to an improvement of the entire system and eventually to elimination of the discovered risks.

Developing complex sociotechnical systems often involves integrating new technology into existing systems by applying systems engineering processes. This requires an understanding of the problem space and the possible impact of the new technology. Systems engineering uses modelling to explore the structural, functional, and operational elements of the problem and solution space (Hitchins 2008). Historically, systems engineering has however struggled with complex sociotechnical systems projects, as it cannot cope with the dynamic behaviour of complex sociotechnical systems. The hypothesis of this thesis is that addressing the contribution of humans performing work in a complex, constrained and dynamic environment using modelling will result in a better understanding in the analysis phase; it should also lead to improved requirements, designs, selection of technologies, and implementation strategies, enabling sociotechnical systems to cope with complex operating environments. A sociotechnical system consists of humans applying technology to perform work through processes within a social structure (organisation) aimed at achieving a defined objective (Bostrom & Heinen 1977, Walker et al. 2009). Work can become complex due to non-linear and dynamic interaction among the people themselves, among people and technology, as well as among people and the environment. Complexity may lead to “wicked and messy” problems, as many unintended or unpredicted consequences may be experienced. The new technology may also lead to new task possibilities that evolve user requirements (Carroll & Rosson 1992). Systems engineering, as developed in the 1950s, forms the basis of developing systems, including sociotechnical systems. Classic systems engineering processes assume that problems can be isolated and decomposed, making the development of complex sociotechnical systems difficult. One way to improve the success of systems engineering is to ensure that the problem to be solved is properly understood. Analysis of the problem and solution space involves capturing and modelling the knowledge and mental models of the stakeholders, to support understanding the system’s requirements. A good description of the problem situation through a model is the first step towards designing and developing a solution. The aim of this study is to develop and demonstrate a modelling methodology for complex sociotechnical systems, in support of the systems engineering process. The two approaches used in the modelling methodology are cognitive work analysis and system dynamics. Cognitive work analysis is a framework for analysing the way people perform work in an organisation, while taking the environmental constraints into consideration. The outputs of cognitive work analysis are constructs or models that capture the structure of the problem. Functions provided by different technological elements are linked to the functional requirements of the system, to achieve its purpose (Lintern 2012). However, cognitive work analysis is limited in investigating the dynamic effect of decisions and policies on the system (Cummings 2006). The dynamic behaviour of complex sociotechnical systems can be analysed using system dynamics, which uses the structure of the system in simulation. System dynamics analyse the effect of feedback and delays on operating the system, as a result of decisions based on policies (Sterman 2000). The design science research framework, which also supports the research design of this thesis, is used to implement the modelling and structure the methodology. Design science research aims at creating technology for a human purpose, unlike the natural sciences, which are geared towards attempting to understand and define reality (March & Smith 1995). The proposed methodology is demonstrated in a case study using modelling and analysis of the impact of a new collaboration technology on command and control systems. Command and control is a good example of a complex sociotechnical system, as humans use technology to assemble and analyse information for situation assessment in support of planning operations (Walker et al. 2009). These systems are also used to control the successful implementation of plans in constrained and variable operating environments. The modelling methodology is demonstrated by modelling and assessing the effect of a new command and control technology for border safeguarding operations, anti-poaching operations and community policing forums. The new technology to be implemented in these complex sociotechnical systems is called “Cmore”. It is a web-based collaboration system that uses smartphones to capture information and track users. Even though the three demonstrations constitute similar systems, the different contextual situations result in diverse behaviour and issues to be investigated. The demonstrations centre on the functions of situation awareness and decision support. The different output models for the command and control systems are used in system dynamics simulations to assess the effect of new technology on the operating and effectiveness of a system. The case studies demonstrated that the modelling methodology support learning about the implementation of a new technology in various complex sociotechnical systems. The developed models and constructs also supported developing evaluation templates during the planning of experiments through identifying key issues. The system dynamics simulations used parametric inputs to investigate the behaviour of the system. In most cases, the simulation outputs identified interesting and counter-intuitive behaviour for deeper assessment. The community policing forum case study also gathered qualitative empirical evidence on the system's behaviour, during a field experiment. The outcomes are compared with the models and simulation outputs to improve the system behavioural models. The learning and improved understanding of the complex sociotechnical system behaviour gained through the modelling methodology, demonstrated its utility. / Thesis (PhD)--University of Pretoria, 2014. / tm2015 / Graduate School of Technology Management (GSTM) / PhD / Unrestricted

Biomethan aus lignin-reicher Biomasse (Holz, Stroh) wird durch thermochemische Vergasung hergestellt (Bio-SNG (biogenic synthetic natural gas)), während Biomethan aus lignin-armer (Energiepflanzen, tierische Exkremente, organischer Abfall,etc.) Biomasse durch anaerobe Vergärung hergestellt wird (Biomethan). Es kann zur Strom- und Wärmeversorgung beitragen, sowie als Kraftstoff im Verkehrssektor eingesetzt werden. In den genannten Sektoren kann Biomethan aufgrund der chemischen und physikalischen Äquivalenz zu fossilem Erdgas dieses substituieren und zum Klimaschutz beitragen. Die Anwendung von Erneuerbarem Methan als Option im Rahmen der Umgestaltung des auf fossilen Brennstoffen basierenden Energiesystems wird seit 2004 durch legislative Unterstützungsprogramme wie das Erneuerbare Energie Gesetz gefördert. Dies führte zur Entwicklung des weltweit größten Marktes für Biomethan. Bio-SNG ist bis heute nicht markt-relevant. Im Laufe des Überganges zu einem konsolidierten Markt für Erneuerbare-Energie-Produkte (bspw. Strom) wurden seit 2014 die Förderhöhen für diese reduziert. Als Folge stehen Produkte aus Erneuerbaren Energiequellen, wie bspw. Biomethan, in Deutschland vor einer ungewissen Zukunft, da die aktuellen Förderhöhen weder für einen weiteren Ausbau der Produktionskapazität ausreichen noch eine Erneuerung der Anlagen (nach Beendigung des Produktlebenszyklus) ermöglichen. Daher soll im Rahmen dieser Dissertation folgende Kernfrage beantwortet werden: • Unter welchen Randbedingungen kann sich Biomethan im Wettbewerb mit Erdgas auf dem deutschen Markt etablieren und welche Mengen an Biomethan werden dann produziert? Zur Beantwortung der Kernfrage wurde ein dynamisches Simulationsmodell anhand der Methode System Dynamics entwickelt. Auf Grundlage des Simulationsmodells wurden anschließend Szenarien definiert und simuliert. Als Untersuchungsraum wurde Deutschland im Zeitraum 2000 – 2035 gewählt. Die Simulationsergebnisse zeigen, dass eine Kombination aus Erhöhung des CO2-Preises des Europäischen Emissionshandelssystems und einer Förderung der Produktion von biogenem Flüssigerdgas potentiell in der Lage wäre, einen großen Anteil der aktuellen Biomethanproduktion unabhängig von staatlichen Fördersystemen aufrecht zu erhalten.

Évaluation de la durabilité de la production de biodiesel est un sujet d'importance croissante en raison de l'intérêt des gouvernements à effectuer des stratégies de souveraineté, diversifier leur matrice énergétique et mis en place l'impact de la production de biocarburants. Dans ce contexte, ce travail propose un modèle dynamique du système pour évaluer la production de biodiesel dans un contexte spécifique, basé sur une structure hiérarchique générale d'évaluation de la durabilité qui intègre les dimensions du développement durable avec les principes, critères et indicateurs (PC & I). Le cadre de l'évaluation de la production de biodiesel a été défini d'après un ample état de la technique, ce qui entraîne une sélection et analyse de 113 documents, y compris les lois, directives et autres documents normatifs, les documents de politique, les certificats et documents publiés dans des revues. Pour définir le cadre final, une stratégie de validation basée sur les consultations d'experts enquête et une analyse statistique descriptive a été réalisée. Ainsi, un cadre composé de cinq dimensions (sociales, économiques, environnementale, politiques et technologiques), 13 principes et 31 critères a été proposé. Par la suite, un modèle de dynamique de système (DS) a été développé et appliqué pour évaluer la durabilité de la production du biodiesel en Colombie. Au départ, le modèle DS a été utilisé pour simuler la production du biodiesel, compte tenu des conditions actuelles en Colombie, ce qui permet de déterminer le niveau de référence (années 2008-2014). Par la suite, certains indicateurs exogènes du scénario de référence ont été modifiés afin de générer une analyse de sensibilité pour définir plusieurs conditions fondamentales vers la production de biodiesel durable dans le contexte colombien. Une fois l'analyse de sensibilité a été réalisée, on a déterminé les conditions qui favorisent ou découragent la production de biodiesel et, par conséquent, des scénarios optimistes et pessimistes ont été proposées. Les résultats de l'analyse des scénarios peuvent aider les institutions, les décideurs et les autres parte prenants associés à établir les conditions à réaliser pour promouvoir une production durable du biodiesel / Sustainability assessment of biodiesel production is a topic of increasing importance due to the interest of governments to stablish sovereignty strategies, diversify their energy matrix and set up the impact of biofuels production. In this context, this work proposes a system dynamic model to assess biodiesel production in a specific context, based on a general hierarchical structure of sustainability assessment that integrates dimensions of sustainable development with principles, criteria and indicators (PC&I). The assessment framework of biodiesel production was defined based on a comprehensive state of the art, resulting in a selection and analysis of 113 documents, including laws, directives and other normative documents, policy documents, certificates and papers published in peer-reviewed journals. To define the final framework, a validation strategy based on expert survey consultations and a descriptive statistical analysis was conducted. As a result, a framework composed of five dimensions (social, economic, environmental, political and technological), 13 principles and 31 criteria was proposed. Subsequently, a System Dynamics (SD) model was developed and applied for assess the sustainability biodiesel production in Colombia. Initially, the SD model was used to simulate the biodiesel production considering the current conditions in Colombia, enabling to determine the baseline (years 2008 to 2014). Subsequently, some exogenous indicators of the baseline scenario were modified in order to generate a sensibility analysis to define several fundamental conditions for the sustainable biodiesel production in the Colombian context. Once the sensibility analysis was conducted, the conditions that promote or discourage biodiesel production were determined and, consequently, optimistic and pessimistic scenarios were proposed. The results of the analysis of the scenarios can help institutions, decision-makers and other agents related to establish the conditions to be carried out to promote a sustainable biodiesel production

In this dissertation System Dynamics is used as a modelling approach to model health care systems to gain a better understanding of the system’s behaviour. This improved understanding can be used to better manage the system and in turn will translate to improved health outcomes. The characteristics of complex systems were reviewed to define a health system as a complex system. Four appropriate modelling approaches was studied that could be used to model complex systems. These modelling approaches included: Monte Carlo Simulation, Discrete Event Simulation, System Dynamics and Agent Based Modelling. System Dynamics was identified as being the most appropriate modelling methodology to be used for the framework. Before the framework was developed health system performance measurement was reviewed to further the understanding of health system measurement. The framework was developed according to the insights gained from the previous reviews. Specifically the elements identification was customised to the health care environment based on available health indicators. The framework was applied in a case study where a section of the South Africa health care system was modelled to focus interventions for human immunodeficiency virus (HIV). The outcomes of the case studies delivered an increased understanding of the system behaviour and also showed appropriates of the framework. / Dissertation (MEng)--University of Pretoria, 2012. / Industrial and Systems Engineering / unrestricted

The question of resource scarcity and emerging pressure of environmentallegislations have put the manufacturing industry with a new challenge. On theone side, there is a huge population that demands a large quantity ofcommodities, on the other side, these demands have to be met by minimumresources and with permissible pollution that the earth’s ecosystem can handle.In this situation, technologic breakthrough that can offer alternative resourceshas become essential. Unfortunately, breakthroughs do not follow any rule ofthumb and while waiting for a miracle, the manufacturing industry has to findways to conserve resources. Within this research the anatomy of a large body ofknowledge has been performed to find the best available practices for resourceconservation. Critical review of the research revealed that none of the availablesolutions are compatible with the level of resource conservation desired by themanufacturing industry or by society. It has also been discovered that a largegap exists between the solutions perceived by the scientists and theapplicability of those solutions. Through careful evaluation of the state-of-theart,the research presented in this thesis introduced a solution of maximizingresource conservation i.e., material, energy and value added, as used inmanufacturing. The solutions emerged from the novel concept named asResource Conservative Manufacturing, which is built upon the concept ofMultiple Lifecycle of product. Unlike other research work, the researchdocumented in this thesis started with the identification of the problem andfrom which a ‘wish to do’ list was drawn. The seriousness of the problem andpotential of adopting the proposed concept has been justified with concreteinformation. A great number of arguments have been presented to show theexisting gaps in the research and from that, a set of solutions to conserveresources has been proposed. Finally, one of the prime hypotheses concerningclosed loop supply chain has been validated through the system dynamicsmodeling and simulation. / QC 20111004

Healthcare in developing countries is confronted with a shortage of skilled healthcare workforce, medical errors, inequity and inefficient healthcare service delivery. Innovative ways of solving healthcare problems through Information and communication technology (ICT) can improve the efficiency, effectiveness, access and quality of the healthcare system. Despite highly anticipated benefits of eHealth system to improve the efficiency of healthcare delivery, the healthcare had barely begun to take advantage of ICT mainly in a resource-constrained environment. The implementation of eHealth systems in developing countries could not proceed beyond the pilot phase to demonstrate sustainability in a large-scale rollout. The general research problem in this thesis focuses on how factors of eHealth implementation interplay to influence technology and information use to ensure the long-term sustainability of eHealth in resource-constrained settings. Systems thinking and system dynamics modelling method were used to handle complexity in the implementation of eHealth. Moreover, sustainability theory, technology acceptance model (TAM) and IS success models were used to develop a system dynamics model of sustainable eHealth implementation. The socio-technical, techno-organizational and techno-economic factors of sustainable eHealth systems are discussed to address the research objectives. The system dynamics simulation model of sustainable eHealth implementation is developed, verified, validated and tested. This applied research study focused on addressing the problems of sustainable eHealth systems implementation in resource-constrained environments. The model-based theory-building research study followed in this thesis aimed at enhancing the understanding of sustainable eHealth implementation in a resource-constrained environment to maximize the acceptance of eHealth by the end-users. Both the ontological and epistemological assumptions of this research study supported the position of the constructivist research paradigm. Methodologically, this study mainly applies qualitative research methodology which is common in the interpretive approach. Structured and semi-structured questionnaires were used to elicit information from purposefully sampled eHMIS and SmartCare health facilities in Ethiopia. Field notes, document review, interview and focus group discussion data were analysed using ATLAS.ti software. Vensim DSS Version 6.3D was used to model and simulate the system dynamics model. Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) approach was followed in the systematic literature review of techno-economic factors. The simulation results confirmed that the ‘effectiveness of training’ was a dominant factor to improve the ‘acceptance rate’ of eHMIS and SmartCare in the socio-technical dimension of sustainable eHealth implementation. The adequacy of ICT and healthcare workforce within eHealth implementing facility and end-users’ familiarity with digital technology showed a stronger influence on the ‘acceptance rate’ of both eHMIS and SmartCare systems in the techno-organizational dimension. An economic incentive, funding duration, funding amount, funding source and economic benefit are identified as techno-economic factors that influence the long-term sustainability of eHealth projects. / Thesis (PhD)--University of Pretoria, 2019. / Graduate School of Technology Management (GSTM) / PhD / Unrestricted

Software industry is getting very competitive in the wake of recession. In most cases, an organization that quotes a lower price and promises to deliver the product at the earliest walks away with the project. But the factor of quality of the product delivered is also very important because that in turn determines the reputation of an organization, which also plays an important role in getting the next project. Interactions in a software development are dynamic in nature and involve human factors. Models are built taking into account all possible factors so as to present a realistic picture of the development process. System dynamics methodology is used to build these models in Vensim. Three models have been proposed to help manager estimate an approximate time and cost of the project, monitor the project once the timeline is set and monitor the project development to change various factors as the development process goes through various phases of development and testing.

京都大学 / 0048 / 新制・課程博士 / 博士(エネルギー科学) / 甲第18388号 / エネ博第300号 / 新制||エネ||62(附属図書館) / 31246 / 京都大学大学院エネルギー科学研究科エネルギー変換科学専攻 / (主査)教授 小西 哲之, 教授 宇根﨑 博信, 准教授 笠田 竜太 / 学位規則第4条第1項該当 / Doctor of Energy Science / Kyoto University / DFAM