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This paper studies what factors influence European citizens in their e-government adoption and use, and whether there are differences within the European Union. A binary logistic regression model has been used to determine the profile of e-government users. The article highlights especially the influence of digital skills, as an increasingly influential factor, and opens up new areas of research such as the uses of e-government depending on the population density or sociodemographic factors. Given a certain lack of e-government studies at a pan-European level, this article provides an empirical comparative analysis in the EU and provides insights into the factors influencing the behaviour of European e-citizens.

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In order to analyse, manage, and compare social projects we need, among other things, to be able to measure their impact. One of the methodologies currently used to measure and manage social impact is Social Return on Investment (SROI). However, not all the results calculated by the SROI method are directly attributable to the project, and, therefore, to determine the real impact it is necessary to filter out the changes that the project has not produced. Filter coefficients perform this function. However, the theoretical logic on which the chain is constructed that converts the outputs into impacts is ambiguous. In this study, we will analyse twenty-five real cases where SROI was used to measure social projects. We will identify the difficulties of isolating and measuring impacts by performing a comparative study of the procedures that entities develop to calculate the filters. This allows us to calculate the impacts from the outputs. We will then propose the improvements needed to overcome these shortcomings.