Badanie struktur przemysłowych w Polsce w dobie globalizacji ze szczególnym uwzględnieniem struktury przestrzennej

Globalization as the drive of socio-economic and political transformations shapes the new order of the modern world. The imperative of constant economic growth forces the search for new sources of optimization of industrial activity, e.g. through extensive division of labour, searching for cheap labour, specialization of activity, tightening the bonds between particular sectors of the national economy, using new technological achievements and new organizational solutions (production fragmentation), and political activity (systematic reduction of barriers in goods, services and capital global flow). Globalization also causes far-reaching changes in the functioning of industry. As a consequence, the object of research in industrial geography changes, as well as the theme- and research range of industrial structures (systems). Traditionally the analysis of structural systems was conducted on the planes of: divisions (branches), ownership, size, and space. In the globalization era, as a result of strong influence of science and technology on industry, especially in organizational, technological, but also logistic spheres, individuation of each of the above-mentioned structures becomes highly problematic.In the light of the above, the author of the present paper examines the applicability of the spatial auto-corellation analysis in identification of patterns of spatial dependencies and spatial heterogeneity of industrial activity, on the example of the Kujawsko-pomorskie voivodship. The main assumption of auto-corellation analysis is based on the claim that the intensity of phenomena in a spatial unit depends on their level in neighbouring units. Experimental analysis of auto-corellative dependencies with respect to the industrial activity development and spatial influence of this activity seems to be a helpful method in identifying industrial spatial structures. It enables determination of patterns of spatial heterogeneity and other patterns of spatial dependencies. Using this method enables to diagnose a low degree of spatial dependency of units with respect to industrial development, and to notice the tendency of polarization of the industrial activity distribution.