951 resultados para decision make
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Dissertation presented to obtain the Ph.D degree in Biology, Computational Biology.
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Dissertation presented to obtain the Ph.D degree in Biology, Neuroscience
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Forest managers, stakeholders and investors want to be able to evaluate economic, environmental and social benefits in order to improve the outcomes of their decisions and enhance sustainable forest management. This research developed a spatial decision support system that provides: (1) an approach to identify the most beneficial locations for agroforestry projects based on the biophysical properties and evaluate its economic, social and environmental impact; (2) a tool to inform prospective investors and stakeholders of the potential and opportunities for integrated agroforestry management; (3) a simulation environment that enables evaluation via a dashboard with the opportunity to perform interactive sensitivity analysis for key parameters of the project; (4) a 3D interactive geographic visualization of the economic, environmental and social outcomes, which facilitate understanding and eases planning. Although the tool and methodology presented are generic, a case study was performed in East Kalimantan, Indonesia. For the whole study area, it was simulated the most suitable location for three different plantation schemes: monoculture of timber, a specific recipe (cassava, banana and sugar palm) and different recipes per geographic unit. The results indicate that a mixed cropping plantation scheme, with different recipes applied to the most suitable location returns higher economic, environmental and social benefits.
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A influência das práticas do Marketing nas redes sociais é o assunto central desta investigação. Muitos afirmam que o marketing digital afecta diretamente a vida das pessoas e consumidores. Saber em que momentos ou situações essa influência se dá é importante para estabelecer até que ponto os utilizadores permitem que o seu comportamento enquanto consumidor seja moldado. Incidindo sobre a área da cosmética, abordamos a questão da utilização de produtos de cosmética sob uma ótica sociológica que envolve desde a inserção da mulher no mercado de trabalho, os padrões de beleza existentes e o fenómeno da metrossexualidade que acontece desde os anos 2000. A investigação analisou o impacto do marketing nas redes sociais de “O Boticário” e “Kiko Make Up Milano”, duas empresas estrangeiras que actuam no mercado português de forma física e virtual. Do ponto de vista das redes sociais, o Facebook foi escolhido porque é a mais popular actualmente. A pesquisa utilizou como metodologia entrevistas e inquérito, este último alojado online. Após a realização da análise, foi constatado que “O Boticário” está mais adaptado ao mercado português, por meio de uma estratégia diferenciada, do que a “Kiko Make Up Milano”, que aplica a mesma estratégia vigente nas lojas do seu país de origem em Portugal. Foi verificado ainda que o Marketing praticado nas redes sociais aproxima as empresas do seus consumidores e muitas vezes os levam às lojas, seja para conhecer um novo produto ou para uma atitude de compra.
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Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.
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In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.
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A foremost dispute that persists on the contemporary world’s agenda is change. The on-going social/technological/economic changes create a competitive and challenging environment for companies to endure. To benefit from these changes, world economies partially depend on emerging Small and Medium Enterprises (SMEs) and their adaptability skills, and subsequently the development of an integrated capability to innovate has become the prime strategy for most of SMEs to subsist and grow. However, innovation and change are always somewhat bonded to an inherent risk development, which subsequently brings on the necessity of a revision of risk management approaches in innovative processes, whose importance SMEs tend to disregard. Additionally, little efforts have been made to improve and create empirical models, metrics and tools to assist SMEs managing latent risks in their innovative projects. This work seeks to present and discuss a solution to support SMEs in engaging on systematic risk management practices, which consists on an integrated risk assessment and response support web-based tool - Spotrisk® - designed for SMEs. On the other hand, an inherent subjectivity is linked with risk management and identification processes, due to uncertainty trait of its nature, for each individual perceives situations according to his own idiosyncrasy, which brings complications in normalizing risk profiles and procedures. This essay aims to bring insights concerning the support in decision-making processes under uncertainty, by addressing issues related with the risk behavior character among individuals. To address such issues, subjects of neuroscience or psychology are explored and models to identify such character are proposed, as well as models to improve presented tool. This work attempts to go beyond the restrictive aim of endeavoring on technical improvement dissertation, and in embraces an exploratory conceptualization concerning micro, small and medium businesses’ traits regarding risk characters and project risk assessment tools.
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Based on the report for the unit “Foresight Methods Analysis” of the PhD programme on Technology Assessment at the Universidade Nova de Lisboa, under the supervision of Prof. Dr. António B. Moniz
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Double Degree in Economics from the NOVA - School of Business and Economics and Insper
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In this paper, we investigate whether being part of the euro area influences the conditional probability of going through a sudden stop or a bonanza of capital flows. Our sample period is from 1995 until 2014. We identify these two phenomena and we evaluate which push and pull factors help predict the conditional probability of experiencing one of them. We find that most countries had significant capital inflows until 2008 and that there were more sudden stops during the recent financial crisis than in any other moment in our sample. The factors that better help forecast the conditional probability of a sudden stop are global uncertainty (represented by the push factor “Volatility Index”), and the domestic economic activity (pull factors “GDP growth” and “consumer confidence”). An indicator of country risk (pull factor “change in credit rating”) is the most significant one for predicting bonanzas. Ultimately, we find no evidence that being part of the euro area influences the conditional probability of going through a sudden stop or a bonanza.
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Field lab: Consumer insights
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This work project has the objective of exploring the importance of making good decisions on supplier selection, so that the purchasing department can contribute to the success of a company. For that it is presented a short bibliography review of the latest insights that were found relevant, on the subjects of purchasing, technology, outsourcing, supplier selection and decision-making techniques. For a better understating on how to deal with a decision-making situation, a case study is also presented: Digital Printing Solutions (DPS) is a Portuguese company that provides complete and integrated printing solutions and has been planning to contract a software supplier. DPS has no formal supplier-selection model and it has to choose between 2 suppliers. The case study was solved using the M-MACBETH software. I have found that complex decisions-making situations can be easily overcome by using the M-MACBETH decision model. Moreover, the usage of a model, instead of decision that follows no formal procedure, provides the decision maker with insights that can be useful to negotiate with the supplier.
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The aim of this study is to assess the institutionalized children’s skills as consumers but also to assess how we can improve their knowledge through an intervention. The sample was composed of two subgroups (38 institutionalized children and 36 non-institutionalized children). In order to assess children’s knowledge, a questionnaire and an interview were used. The method used as intervention was a 30-minute class. Results suggested that institutionalized children have lower levels of knowledge regarding consumption-related practices and lower levels of accuracy at estimating prices than non-institutionalized children. However, results also showed that the attitudes of institutionalized children towards advertising and making decisions based on price/quantity evaluation or based on the use of the same strategy in different situations are not significantly different from the non-institutionalized children. Regarding the intervention, it was possible to conclude that one class is not the best method to improve children’s knowledge. Institutionalized children need a longer and more practical intervention.