A number of studies point out a positive influence of entrepreneurship on economic growth. This is due to the role that entrepreneurs play in the economy by utilizing new knowledge, shaping markets, and pushing out unproductive incumbents. The ambitious One Belt One Road Initiative, which recently includes sixty Asian, African and European countries, aims at stimulating global economic development and prosperity. From the theoretical point of view, entrepreneurship is crucial for achieving the aim. Consequently, the intent of this paper is to analyze entrepreneurial behavior of the countries participated in the One Belt One Road Initiative, using the data from the Global Entrepreneurship Monitor (GEM). Distinct country clusters are identified and their entrepreneurial characteristics are interpreted.
The purpose of the present paper is to find whether the spatial distribution of enterprise support policy funds meet the spatial objectives stated in Czech strategic documents related to enterprise support policy. Are more funds allocated in lagging regions, and does enterprise support policy contribute more to the convergence objective, or are more funds allocated in core regions, and does enterprise support policy contribute more to the competitiveness objective? These questions are answered by evaluating the Structural (and Cohesion) Fund (SF) expenditures that were allocated on operations categorised as part of enterprise support policy (2007-2013). The dependent variable relates to 206 regions, and SF expenditures are calculated for every inhabitant of a region. Moreover, two types of SF operation are distinguished: (a) innovationoriented operations; and (b) other enterprise support operations. Three explanatory variables are defined using Principal Components Analysis (PCA), and these components are understood as: (1) the social disadvantage of regions; (2) the innovation environment of regions; and (3) the quality of regional entrepreneurial environments. The associations between the dependent and explanatory variables are subsequently evaluated by methods of correlation and regression analysis. The findings provide some evidence for both the convergence and competitiveness objectives. Nevertheless, this evidence is rather limited due to a low spatial concentration of SF allocation, and the compensatory effect between the two thematic types of SF operations. Hence, while the quality of their innovation environment has a positive influence on regional SF allocation regardless of the thematic focus of SF operations, socially disadvantaged regions received more funds for SF operations which are not innovation-oriented. The capacity of potential beneficiaries to prepare and submit many project proposals for SF co-financing is the main reason for high or low SF allocation.
The intention of this paper is to provide empirical evidence on how the factors of socio-economic disadvantage and absorption capacity influence the spatial distribution of Structural Fund (SF) payments among the Czech Republic’s micro-regions during the 2007–2013 programming period. The empirical results indicate that agglomeration economies, innovation and entrepreneurship are associated with higher SF absorption capacity and higher SF payments, challenging the tendency for socio-economically disadvantaged regions to converge. SF absorption capacity measured especially by the number of project applications submitted for SF financing and by the average SF budget per project application, is a crucial concept in order to understand the relationship between within-country regional disparities and SF interventions.
Differences between brownfields and redeveloped sites in the Ostrava metropolitan area are subject to analysis in this paper. Environmental burden and former functional use were identified as statistically significant characteristics of such differences. In addition, relations between selected attributes of brownfields and redeveloped sites were analyzed using the “if-then” decision rules of the rough set method. In this way, the research demonstrated the significance of spatial aspects and identified two fundamental types of brownfields in the model area. The first type is represented by agricultural brownfields in the hinterland zone, that are characterized by a complicated ownership structure. Brownfields of the second type are located particularly in the inner city morphogenetic zone, and are characterized by potential problems with environmental burden. In this context, brownfields and redeveloped sites differ respectively in the combination of these characteristics.