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Hypersensitivity to Parietaria officinalis (wall pellitory) pollen and other environmental allergens was studied in pollinosis patients allergic to P. officinalis pollen who were born in areas without P. officinalis and later moved to the city of Split, where P. officinalis is responsible for some 65% of pollinosis cases. Highly significant positive correlations were found for both the intensity of skin test reaction and concentration of specific serum IgE with the length of residence in the area. In contrast, the respective data on subjects hypersensitive to P. officinalis pollen allergen, but born and living in the area of Split, revealed a tendency to negative correlation between age and intensity of hypersensitivity to P. officinalis. A number of patients from both groups were tested for presence of serum IgE antibodies specific for 14 common environmental allergens. Hypersensitivity to P. officinalis pollen was associated with hypersensitivity to olive, mugwort, and birch pollen in newcomers; hypersensitivity to birch and, to some extent, olive pollen was significantly more frequent in newcomers than in autochthonous patients who were allergic to P. officinalis pollen. Regardless of whether the patients were autochthons or newcomers to the area with P. officinalis, hypersensitivity to P. officinalis mostly excluded hypersensitivity to Dermatophagoides farinae and D. pteronyssinus, and vice versa.

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The companies that apply the concept of business intelligence in their marketing decisions in some of the following ways were included in this study: at the level of the entire system or specific marketing strategy of companies (e.g. marketing department, research development, commercial, etc.), apply business intelligence only in certain marketing processes or projects, used in business from the technology and platform for data warehouse, data mining, OLAP tools, using advanced analytical techniques of simulation and visualization applications. Variables examined were categorized into four groups: business intelligence, supply chain management, information visibility and integration. Factor analysis was used to facilitate the connection of these groups of variables, i.e. reduction of number of variables. Then, we tested the correlation between the newly formed variables. There was a significant statistical correlation between business intelligence, supply chain management, information visibility and integration among the partners in the production chain. ANOVA was conducted to compare differences in the mean values of variables in relation to the activity, size and legal form. This paper will analyze the relationship between business intelligence and supply chain management for strategic and tactic marketing decisions.