As sociedades de capital de risco em Portugal: Critérios adoptados no processo de tomada de decisão de investimento

Este estudo procura compreender a importância atribuída aos critérios utilizados pelas SCR portuguesas, na seleção e avaliação de projetos do tipo early-stage. Os dados utilizados foram recolhidos com recurso a questionário aplicado a 22 SCR portuguesas. Foram utilizadas técnicas de estatística descritiva, testes não paramétricos e análise de clusters. Concluiu-se que a personalidade e experiência do empreendedor e equipa de gestão são os critérios mais valorizados. As SCR com capital maioritariamente privado consideram mais importante o grupo de critérios relativo à personalidade do empreendedor e equipa de gestão do que as de capital maioritariamente público; e, as SCR que ainda não se internacionalizaram, consideram mais importantes o grupo de critérios relativos à personalidade do empreendedor e equipa de gestão e o grupo de critérios relativo aos aspetos financeiros, do que as SCR que se internacionalizaram. Na análise de clusters identificaram-se três grupos de SCR: Criadores de riqueza de forma sustentada; Monopolistas Impacientes; e, Ciumento. ABSTRACT: This study seeks to understand the relevance of the criteria used by the Portuguese VCs to select and assess early stage type projects. The data used for the study was collected through a questionnaire answered by 22 Portuguese VCs. We employed descriptive statistic techniques, non-parametric tests and cluster analysis. The conclusion of the study was that the personality and experience of an entrepreneur and of the management team are the most valued criteria. VCs with a majority of private share capital found the group of criteria related to the personality of the entrepreneur and of the management team to be more important than the companies with a majority of public share capital; additionally, the VCs that have not yet expanded internationally, consider the personality of the entrepreneur and management team and the group of criteria associated to financial aspects, to be more important than the VCs that have already expanded abroad. Throughout the study of the clusters we were able to identify three VCs groups: Creators of sustained wealth; Impatient Monopolists and Jealous.

Umbrella pine above ground biomass estimation with very high spatial resolution satellite images

Above ground biomass is frequently estimated with forest inventory data and an extrapolation method for the per unit area evaluations. This procedure is labour demanding and costly. In this study above ground biomass functions, whose independent variable is crown horizontal projection, were developed. Multi-resolution segmentation method and object-oriented classification, based on very high spatial resolution satellite images, were used to obtain the area of tree crown horizontal projection for umbrella pine (Pinus pinea L.). A set of inventory plots were measured and with existing allometric functions for this species above ground biomass per tree and per plot were calculated. The two data sets were used to fit linear functions both for individual plot and their cumulative values. The results show a good performance of the models. Errors smaller than 10% are obtained for stand areas greater than 1.4 ha. These functions have the advantages of estimating above ground biomass for all the area under study or surveillance, not requiring forest inventory; allow monitoring in short time periods; and are easily implemented in a geographical information system environment.

Above ground biomass estimation in Mediterranean multiple use systems with high spatial resolution satellite images

Forest biomass has been having an increasing importance in the world economy and in the evaluation of the forests development and monitoring. It was identified as a global strategic reserve, due to its applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. The estimation of above ground biomass is frequently done with allometric functions per species with plot inventory data. An adequate sampling design and intensity for an error threshold is required. The estimation per unit area is done using an extrapolation method. This procedure is labour demanding and costly. The mail goal of this study is the development of allometric functions for the estimation of above ground biomass with ground cover as independent variable, for forest areas of holm aok (Quercus rotundifolia), cork oak (Quercus suber) and umbrella pine (Pinus pinea) in multiple use systems. Ground cover per species was derived from crown horizontal projection obtained by processing high resolution satellite images, orthorectified, geometrically and atmospheric corrected, with multi-resolution segmentation method and object oriented classification. Forest inventory data were used to estimate plot above ground biomass with published allometric functions at tree level. The developed functions were fitted for monospecies stands and for multispecies stands of Quercus rotundifolia and Quercus suber, and Quercus suber and Pinus pinea. The stand composition was considered adding dummy variables to distinguish monospecies from multispecies stands. The models showed a good performance. Noteworthy is that the dummy variables, reflecting the differences between species, originated improvements in the models. Significant differences were found for above ground biomass estimation with the functions with and without the dummy variables. An error threshold of 10% corresponds to stand areas of about 40 ha. This method enables the overall area evaluation, not requiring extrapolation procedures, for the three species, which occur frequently in multispecies stands.

Clustering of Territorial Areas: A Multicriteria Districting problem

The success of regional development policies depends on the homogeneity of the territorial units. This paper aims to propose a framework for obtaining homogenous territorial clusters based on a Pareto frontier considering multiple criteria related to territories’ endogenous resources, economic profile and socio-cultural features. This framework is developed in two phases. First, the criteria correlated with development at the territorial unit level are determined through statistical and econometric methods. Then, a multi-criteria approach is developed to allocate each territorial unit (parishes) to a territorial agglomerate, according to the Pareto frontier established.