938 resultados para Open Business Model


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RESUMO: Em 2011, a Associação Psiquiátrica Mundial lançou um programa de bolsas de investigação para psiquiatras em início de carreira a partir de países de renda baixa ou média-baixa, no âmbito deste programa, o autor foi selecionado para uma bolsa de pesquisa no Centre for Youth Mental Health/Orygen Youth Health Research Centre da Universidade de Melbourne. Orygen, é a principal organização de pesquisa e tradução do conhecimento do mundo com foco em problemas de saúde mental em pessoas jovens. O estágio foi baseado em Prevenção e Intervenção Precoce Psychosis Centre (EPPIC), que faz parte do Orygen. EPPIC fornece programa de tratamento abrangente e integrada, baseada na comunidade para o primeiro episódio de psicose. Esta dissertação descreve o modelo EPPIC, e seus componentes essenciais e fatores que são necessários para uma implementação de serviço direito. Além disso, uma proposta de criação de um programa-piloto de intervenção psicose precoce é discutido. Este programa inclui um programa de extensão inovadora que combina princípios comerciais sólidos, com metas sociais, a fim de combater especificamente a maior barreira para o tratamento da psicose precoce na Bolívia: o estigma da doença mental. Ao utilizar uma equipe de tratamento móvel, multidisciplinar, que enfatiza os papéis dos gerentes do caso treinados focada em fornecer indivíduo intensiva e apoio familiar no lar, este programa irá prestar cuidados culturalmente apropriados que irá alavancar contribuições de um suprimento limitado de psiquiatras e mudar longe da dependência um sistema médico fragmentado. ---------------------------- ABSTRACT: In 2011, the World Psychiatric Association launched a programme of research fellowships for early-career psychiatrists from low- or lower-middle income countries, within this programme, the author was selected to a research fellowship at the Centre for Youth Mental Health/Orygen Youth Health Research Centre at University of Melbourne. Orygen, is the world’s leading research and knowledge translation organization focusing on mental ill-health in young people. The traineeship was based on Early Psychosis Prevention and Intervention Centre (EPPIC), which is part of Orygen. EPPIC provides comprehensive, integrated, community-based treatment program for first-episode psychosis. This dissertation describes the EPPIC model, and its core components and factors which are necessary to a right service implementation. Additionally, a proposal to establish a pilot early psychosis intervention programme is discussed. This programme includes an innovative outreach programme that combines sound business principals with social goals in order to specifically target the largest barrier to early psychosis treatment in Bolivia: the stigma of mental illness. By utilizing a mobile, multidisciplinary treatment team that emphasizes the roles of trained case managers focused on providing intensive individual and family support in the home, this programme will provide culturally appropriate care that will leverage contributions from a limited supply of psychiatrists and shift dependence away from a fragmented medical system.

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This thesis proposes a methodology for modelling business interoperability in a context of cooperative industrial networks. The purpose is to develop a methodology that enables the design of cooperative industrial network platforms that are able to deliver business interoperability and the analysis of its impact on the performance of these platforms. To achieve the proposed objective, two modelling tools have been employed: the Axiomatic Design Theory for the design of interoperable platforms; and Agent-Based Simulation for the analysis of the impact of business interoperability. The sequence of the application of the two modelling tools depends on the scenario under analysis, i.e. whether the cooperative industrial network platform exists or not. If the cooperative industrial network platform does not exist, the methodology suggests first the application of the Axiomatic Design Theory to design different configurations of interoperable cooperative industrial network platforms, and then the use of Agent-Based Simulation to analyse or predict the business interoperability and operational performance of the designed configurations. Otherwise, one should start by analysing the performance of the existing platform and based on the achieved results, decide whether it is necessary to redesign it or not. If the redesign is needed, simulation is once again used to predict the performance of the redesigned platform. To explain how those two modelling tools can be applied in practice, a theoretical modelling framework, a theoretical Axiomatic Design model and a theoretical Agent-Based Simulation model are proposed. To demonstrate the applicability of the proposed methodology and/or to validate the proposed theoretical models, a case study regarding a Portuguese Reverse Logistics cooperative network (Valorpneu network) and a case study regarding a Portuguese construction project (Dam Baixo Sabor network) are presented. The findings of the application of the proposed methodology to these two case studies suggest that indeed the Axiomatic Design Theory can effectively contribute in the design of interoperable cooperative industrial network platforms and that Agent-Based Simulation provides an effective set of tools for analysing the impact of business interoperability on the performance of those platforms. However, these conclusions cannot be generalised as only two case studies have been carried out. In terms of relevance to theory, this is the first time that the network effect is addressed in the analysis of the impact of business interoperability on the performance of networked companies and also the first time that a holistic approach is proposed to design interoperable cooperative industrial network platforms. Regarding the practical implications, the proposed methodology is intended to provide industrial managers a management tool that can guide them easily, and in practical and systematic way, in the design of configurations of interoperable cooperative industrial network platforms and/or in the analysis of the impact of business interoperability on the performance of their companies and the networks where their companies operate.

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A Work Project, presented as part of the requirements for the Award of a Masters Double Degree in Economics and International Business from the NOVA – School of Business and Economics and Insper Instituto de Ensino e Pesquisa

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The following project introduces a model of Growth Hacking strategies for business-tobusiness Software-as-a-Service startups that was developed in collaboration with and applied to a Portuguese startup called Liquid. The work addresses digital marketing channels such as content marketing, email marketing, social marketing and selling. Further, the company’s product, pricing strategy, partnerships and website communication are examined. Applying best case practices, competitor benchmarks and interview insights from numerous industry influencers and experts, areas for improvement are deduced and procedures for each of those channels recommended.

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Today recovering urban waste requires effective management services, which usually imply sophisticated monitoring and analysis mechanisms. This is essential for the smooth running of the entire recycling process as well as for planning and control urban waste recovering. In this paper we present a business intelligence system especially designed and im- plemented to support regular decision-making tasks on urban waste management processes. The system provides a set of domain-oriented analytical tools for studying and characterizing poten- tial scenarios of collection processes of urban waste, as well as for supporting waste manage- ment in urban areas, allowing for the organization and optimization of collection services. In or- der to clarify the way the system was developed and the how it operates, particularly in process visualization and data analysis, we also present the organization model of the system, the ser- vices it disposes, and the interface platforms for exploring data.

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Business Intelligence (BI) can be seen as a method that gathers information and data from information systems in order to help companies to be more accurate in their decision-making process. Traditionally BI systems were associated with the use of Data Warehouses (DW). The prime purpose of DW is to serve as a repository that stores all the relevant information required for making the correct decision. The necessity to integrate streaming data became crucial with the need to improve the efficiency and effectiveness of the decision process. In primary and secondary education, there is a lack of BI solutions. Due to the schools reality the main purpose of this study is to provide a Pervasive BI solution able to monitoring the schools and student data anywhere and anytime in real-time as well as disseminating the information through ubiquitous devices. The first task consisted in gathering data regarding the different choices made by the student since his enrolment in a certain school year until the end of it. Thereafter a dimensional model was developed in order to be possible building a BI platform. This paper presents the dimensional model, a set of pre-defined indicators, the Pervasive Business Intelligence characteristics and the prototype designed. The main contribution of this study was to offer to the schools a tool that could help them to make accurate decisions in real-time. Data dissemination was achieved through a localized application that can be accessed anywhere and anytime.

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Tese de Doutoramento em Engenharia Têxtil

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Doctoral Thesis in Information Systems and Technologies Area of Information Systems and Technology

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Drosophila Fallen, 1823 (Diptera, Drosophilidae) is for long a well-established model organism for genetics and evolutionary research. The ecology of these flies, however, has only recently been better studied. Recent papers show that Drosophila assemblies can be used as bioindicators of forested environment degradation. In this work the bioindicator potential of drosophilids was evaluated in a naturally opened environment, a coastal strand-forest (restinga). Data from nine consecutive seasonal collections revealed strong temporal fluctuation pattern of the majority of Drosophila species groups. Drosophila willistoni group was more abundant at autumns, whereas D. cardini and D. tripunctata groups were, respectively, expressive at winters and springs, and D. repleta group at both seasons. The exotic species D. simulans Sturtevant, 1919 (from D. melanogaster group) and Zaprionus indianus Gupta, 1970 were most abundant at summers. Overall, the assemblage structure did not show the same characteristics of forested or urban environments, but was similar to the forests at winters and to cities at summers. This raises the question that this locality may already been under urbanization impact. Also, this can be interpreted as an easily invaded site for exotic species, what might lead to biotic homogenization and therefore can put in check the usage of drosophilid assemblages as bioindicators at open environments.

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Two claims pervade the literature on the political economy of market reforms: that economic crises cause reforms; and that crises matter because they bring into question the validity of the economic model held to be responsible for them. Economic crises are said to spur a process of learning that is conducive to the abandonment of failing models and to the adoption of successful models. But although these claims have become the conventional wisdom, they have been hardly tested empirically due to the lack of agreement on what constitutes a crisis and to difficulties in measuring learning from them. I propose a model of rational learning from experience and apply it to the decision to open the economy. Using data from 1964 through 1990, I show that learning from the 1982 debt crisis was relevant to the first wave of adoption of an export promotion strategy, but learning was conditional on the high variability of economic outcomes in countries that opened up to trade. Learning was also symbolic in that the sheer number of other countries that liberalized was a more important driver of others’ decisions to follow suit.

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Macroeconomic activity has become less volatile over the past three decades in most G7 economies. Current literature focuses on the characterization of the volatility reduction and explanations for this so called "moderation" in each G7 economy separately. In opposed to individual country analysis and individual variable analysis, this paper focuses on common characteristics of the reduction and common explanations for the moderation in G7 countries. In particular, we study three explanations: structural changes in the economy, changes in common international shocks and changes in domestic shocks. We study these explanations in a unified model structure. To this end, we propose a Bayesian factor structural vector autoregressive model. Using the proposed model, we investigate whether we can find common explanations for all G7 economies when information is pooled from multiple domestic and international sources. Our empirical analysis suggests that volatility reductions can largely be attributed to the decline in the magnitudes of the shocks in most G7 countries while only for the U.K., the U.S. and Italy they can partially be attributed to structural changes in the economy. Analyzing the components of the volatility, we also find that domestic shocks rather than common international shocks can account for a large part of the volatility reduction in most of the G7 countries. Finally, we find that after mid-1980s the structure of the economy changes substantially in five of the G7 countries: Germany, Italy, Japan, the U.K. and the U.S..

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Report for the scientific sojourn at the Simon Fraser University, Canada, from July to September 2007. General context: landscape change during the last years is having significant impacts on biodiversity in many Mediterranean areas. Land abandonment, urbanisation and specially fire are profoundly transforming large areas in the Western Mediterranean basin and we know little on how these changes influence species distribution and in particular how these species will respond to further change in a context of global change including climate. General objectives: integrate landscape and population dynamics models in a platform allowing capturing species distribution responses to landscape changes and assessing impact on species distribution of different scenarios of further change. Specific objective 1: develop a landscape dynamic model capturing fire and forest succession dynamics in Catalonia and linked to a stochastic landscape occupancy (SLOM) (or spatially explicit population, SEPM) model for the Ortolan bunting, a species strongly linked to fire related habitat in the region. Predictions from the occupancy or spatially explicit population Ortolan bunting model (SEPM) should be evaluated using data from the DINDIS database. This database tracks bird colonisation of recently burnt big areas (&50 ha). Through a number of different SEPM scenarios with different values for a number of parameter, we should be able to assess different hypothesis in factors driving bird colonisation in new burnt patches. These factors to be mainly, landscape context (i.e. difficulty to reach the patch, and potential presence of coloniser sources), dispersal constraints, type of regenerating vegetation after fire, and species characteristics (niche breadth, etc).

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Employing the financial accelerator (FA) model of Bernanke, Gertler and Gilchrist (1999) enhanced to include a shock to the FA mechanism, we construct and study shocks to the efficiency of the financial sector in post-war US business cycles. We find that financial shocks are very tightly linked with the onset of recessions, more so than TFP or monetary shocks. The financial shock invariably remains contractionary for sometime after recessions have ended. The shock accounts for a large part of the variance of GDP and is strongly negatively correlated with the external finance premium. Second-moments comparisons across variants of the model with and without a (stochastic) FA mechanism suggests the stochastic FA model helps us understand the data.

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This paper contributes to the on-going empirical debate regarding the role of the RBC model and in particular of technology shocks in explaining aggregate fluctuations. To this end we estimate the model’s posterior density using Markov-Chain Monte-Carlo (MCMC) methods. Within this framework we extend Ireland’s (2001, 2004) hybrid estimation approach to allow for a vector autoregressive moving average (VARMA) process to describe the movements and co-movements of the model’s errors not explained by the basic RBC model. The results of marginal likelihood ratio tests reveal that the more general model of the errors significantly improves the model’s fit relative to the VAR and AR alternatives. Moreover, despite setting the RBC model a more difficult task under the VARMA specification, our analysis, based on forecast error and spectral decompositions, suggests that the RBC model is still capable of explaining a significant fraction of the observed variation in macroeconomic aggregates in the post-war U.S. economy.

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Using a standard open economy DSGE model, it is shown that the timing of asset trade relative to policy decisions has a potentially important impact on the welfare evaluation of monetary policy at the individual country level. If asset trade in the initial period takes place before the announcement of policy, a national policymaker can choose a policy rule which reduces the work effort of households in the policymaker’s country in the knowledge that consumption is fully insured by optimally chosen international portfolio positions. But if asset trade takes place after the policy announcement, this insurance is absent and households in the policymaker’s country bear the full consumption consequences of the chosen policy rule. The welfare incentives faced by national policymakers are very different between the two cases. Numerical examples confirm that asset market timing has a significant impact on the optimal policy rule.