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- One of the biggest problems of the last decade is hardly defined economic activities, objects and subjects in cyber space. Through cyberspaces, such as social networking platforms, e-commerce, e-business systems or cyber computer games, real money circulates but in most cases these transactions are not accounted and do not generate the taxes to the state budget. For this reason, a deeper insight in the phenomenon of digital shadow economy is purposeful. The performed analysis of various scientific sources leads to the conclusion that the previous research on the topic of digital shadow economy is mostly limited with the studies in cybercriminal activities, e-fraud and the motives of the consumers to get involved in digital piracy. However, the complex scientific research in the field of digital shadow economy has not been performed, which determined the aim of this research – to systematize the scientific literature on digital shadow economy and perform the critical analysis of the researched phenomenon. The methods used in the research include systematic and comparative analysis of the scientific literature. The research has enabled to specify the concept of digital shadow economy, identify its forms and activity channels in digital black markets and define the differences between traditional and digital shadow economy.
Evaluation of the factors that influence the EU automobile industry during the period of financial crisisPublicationSince EU automobile industry has not completely recovered after the recent financial crisis, it is purposeful to identify what factors could have determined the recession of the EU automobile industry. The article is aimed at the evaluation of the factors that influence the automobile industry in the EU during the period of financial crisis. The methods of the research include correlation analysis and multifaceted regression analysis. The research has enabled to establish the impact of macroeconomic factors on the EU automobile production whereas the factors that influence the EU automobile demand have been researched only partly due to non-stationarity of the statistical data. Although the data was differentiated to make it stationary, the differentiation too significantly changed data values and correlation coefficients to make reliable conclusions. For the comprehensive analysis, the Vector Error Correlation Model (VECM) should be applied.