The present paper aims to investigate and compare various modalities of migrant entrepreneurship in European countries in order to design a systematic classification of migrant entrepreneurship and to highlight key factors of migrant entrepreneurship in Europe. The paper is based on a comparative assessment of available quantitative data and qualitative information derived from a broad review of findings from previous studies in the literature. Our quantitative evaluation includes the European OECD countries, while our qualitative investigation addresses migrant entrepreneurship experiences in eight European countries: Denmark, Germany, Greece, Italy, the Netherlands, Portugal, Sweden, and the UK. The results of our comparative analysis show that the general picture of European migrant entrepreneurship is determined by some distinct push factors such as high unemployment rates and low participation rates or low status in the labour market as well as by an accompanying factor, namely mixed embeddedness. The results of our comparative evaluation are summarized in a systematic typological table. These show that, while an informal and labour-intensive sector, an underground economy, and small companies and traditional households prompt migrant entrepreneurship in Southern European countries, an over-representation of non-Western immigrants among the self-employed, as well as relatively lower income levels of self-employed immigrants compared to both self-employed natives and employed immigrants are decisive for migrant entrepreneurship in Northern European countries.

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Green spaces, such as parks, are an essential constituent of urban quality of life. It is noteworthy, however, that some cities have been more successful in implementing a green space policy than others. This article aims to assess the complex and heterogeneous supply of urban green spaces by means of a multidimensional evaluation approach, and to compare the `green performance' of European cities in terms of the present situation, priorities in decision making and planning, and their success level as evaluated by experts in the field. The article examines urban green spaces from the viewpoint of relevant indicators, in particular `quantity and availability of urban green spaces', `changes in green spaces', `planning of urban green spaces',`financing of urban green spaces' and `level of performance', on the basis of a comparison of 24 European cities. It deploys a proper type of multi-criteria analysis for mixed quantitative and qualitative information, coined Regime Analysis.A comparison of urban green spaces in European cities by means of this multi-criteria analysis brings to light the critical elements in green space availability and sets out choice directions based on priorities in decision making and policy evaluation.The results of this Regime Analysis show that when only the indicators on the availability of urban green spaces are used to assess the green performance with a view to a ranking of European cities, the Southern European cities are in the lead. However, when the planning performance indicators are also taken into consideration, the Northern European cities appear to have higher scores.

This study aims to identify the critical factor(s) that determine the embeddedness level (EL) of rural entrepreneurs. In order to achieve this aim, existing applied studies on the embeddedness of entrepreneurs undertaken in different rural areas were systematically collected to create a database in order to provide the material for a systematic comparative analysis. This was done in order to highlight common and contrasting findings from a set of selected studies for different ELs. As many results of these studies were largely qualitative in nature and only partially comparable, a specific tool for analysing categorical data based on artificial intelligence methods, viz. rough set data analysis (RSDA), was employed. This experimental study is the first RSDA approach that compares the results of several rural case studies and infers general induction rules for the different ELs. The results of our analysis show that using and benefiting from local resources are the key factors that explain how entrepreneurs become embedded in rural areas.

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