Education for sustainable development – How are Portuguese children being educated in order to become responsible consumers

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

A closer look at brazilwood and its lake pigments

Dissertação para obtenção do Grau de Mestre em Mestrado em Conservação e Restauro, especialização em Ciências da Conservação

Análise e melhoria do processo de order-picking num sistema produtivo: caso de estudo

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

Influence of Lean and Green on supply chain performance: an interpretive structural modelling model

This work aims to identify and rank a set of Lean and Green practices and supply chain performance measures on which managers should focus to achieve competitiveness and improve the performance of automotive supply chains. The identification of the contextual relationships among the suggested practices and measures, was performed through literature review. Their ranking was done by interviews with professionals from the automotive industry and academics with wide knowledge on the subject. The methodology of interpretive structural modelling (ISM) is a useful methodology to identify inter relationships among Lean and Green practices and supply chain performance measures and to support the evaluation of automotive supply chain performance. Using the ISM methodology, the variables under study were clustered according to their driving power and dependence power. The ISM methodology was proposed to be used in this work. The model intends to provide a better understanding of the variables that have more influence (driving variables), the others and those which are most influenced (dependent variables) by others. The information provided by this model is strategic for managers who can use it to identify which variables they should focus on in order to have competitive supply chains.

Analysis of panoramio photo tags in order to extract land use information

In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.

How to optimize Lipton’s business model in order to stimulate tea consumption in Portugal and increase Lipton Leaf tea market share?: The importance of distribution and sales channels management in a B2B2C market

Field Lab Entrepreneurial Innovative Ventures

Development and application of NMR techniques to study water-in-CO2 microemulsions

Self-assembly is a phenomenon that occurs frequently throughout the universe. In this work, two self-assembling systems were studied: the formation of reverse micelles in isooctane and in supercritical CO2 (scCO2), and the formation of gels in organic solvents. The goal was the physicochemical study of these systems and the development of an NMR methodology to study them. In this work, AOT was used as a model molecule both to comprehensively study a widely researched system water/AOT/isooctane at different water concentrations and to assess its aggregation in supercritical carbon dioxide at different pressures. In order to do so an NMR methodology was devised, in which it was possible to accurately determine hydrodynamic radius of the micelle (in agreement with DLS measurements) using diffusion ordered spectroscopy (DOSY), the micellar stability and its dynamics. This was mostly assessed by 1H NMR relaxation studies, which allowed to determine correlation times and size of correlating water molecules, which are in agreement with the size of the shell that interacts with the micellar layer. The encapsulation of differently-sized carbohydrates was also studied and allowed to understand the dynamics and stability of the aggregates in such conditions. A W/CO2 microemulsion was prepared using AOT and water in scCO2, with ethanol as cosurfactant. The behaviour of the components of the system at different pressures was assessed and it is likely that above 130 bar reverse microemulsions were achieved. The homogeneity of the system was also determined by NMR. The formation of the gel network by two small molecular organogelators in toluene-d8 was studied by DOSY. A methodology using One-shot DOSY to perform the spectra was designed and applied with success. This yielded an understanding about the role of the solvent and gelator in the aggregation process, as an estimation of the time of gelation.

Historical reconstructions of raw materials based on a blue smalt coating applied to a seventeenth-century altarpiece

Based on samples cross-sections from the Main Altarpiece of the Coimbra Old Cathedral, where a blue coating performed in 1685 is observed (that was partly covered with a Prussian blue-containing overpaint), the raw materials present in this coating were reproduced and studied. Blue areas were painted with smalt in oil, according to the contract signed by Manoel da Costa Pereira in 1684 and the analysis by Le Gac in 2009. Based on these, three batches of cobalt-based glasses (S1, S2 and S3) were heated and melted in alumina crucibles in the kiln. S1 contained 6.03 % of cobalt oxide, S2 contained 2.10 %, with the addition of 1.49 % of magnesium oxide, and S3 contained 6.82 % of cobalt oxide, with the addition of 4.63% of antimony trioxide. These batches were ground mechanically with water and manually with different vehicles stated in recipes. The results were studied by means of OM, SEM-EDS, X-Ray CT, Colorimetry and Vickers HT. Different binders were also produced and analyzed by means of μ-FTIR, in order to perform their characterization and obtain Standard Spectra. Since anhydrite was identified in the ground layers, gypsum from Óbidos was also characterized by XRD. The main goal of this thesis was to study all the raw materials present in the 1685-blue coating, in order to allow the historically accurate reconstruction of the layers build-up in the next future.

Quadratic programming versus second order con programming in portfolio optimization

Despite the extensive literature in finding new models to replace the Markowitz model or trying to increase the accuracy of its input estimations, there is less studies about the impact on the results of using different optimization algorithms. This paper aims to add some research to this field by comparing the performance of two optimization algorithms in drawing the Markowitz Efficient Frontier and in real world investment strategies. Second order cone programming is a faster algorithm, appears to be more efficient, but is impossible to assert which algorithm is better. Quadratic Programming often shows superior performance in real investment strategies.

What should Fundação Calouste Gulbenkian do in order to attract the National Millennials?

Branding Lab

Which communication strategy should a male luxury (fashion) brand – associated with a luxury car brand – develop, in order to increase its awareness in Europe

This work project explores how a male luxury (fashion) brand (subsidiary) that is associated with a luxury car brand (parent company) should develop its communication strategy in order to increase awareness in Europe. For this purpose a quantitative research was conducted. The aim was to find out whether the company in question had low brand awareness among European luxury consumers. Hereafter, a qualitative research revealed important insights in regard to luxury communication among male luxury consumers. Both the results of the research and the recommendations of luxury experts laid the foundation for the development of a solution-oriented communication strategy. The result of the analysis crystallizes the importance of the shared heritage and the synergistic effects, of which the subsidiary should make vast use when communicating.