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Technology entrepreneurship is one of key research areas in the modern economy as fast-growing companies significantly contribute to the economic growth of the regions and Russia in general. Identifying factors influencing the emergence and success of start-ups could give the tools to support and stimulate entrepreneurship in this field. In this research, we collected and analysed data on technological start-ups founded in the past decade. We focused on identifying global start-ups, in which at least one of the founders was educated in Russia. The final sample includes more than 1000 start-ups of Russian origin. During the study, we discovered the main trends in the educational, geographical and sectorial paths of start-up founders. We hypothesise that the promotion of technical education in the regions, and the use of information technologies in business play a significant role in the development of technology entrepreneurship. The econometric analysis allowed us to determine regional factors influencing the emergence of successful start-ups in the region, as well as regional factors affecting the intention to establish a technology start-up in a country or a region differing from the place where they had obtained education. In the regions close to Moscow and relatively developed regions, the level of salaries for programmers is of significance. An entrepreneur’s desire to change a region or a country can be affected by the level of inventive activity in a region, the number of students of mathematical specialties, the distance to Moscow. Future studies can focus on a country analysis of the success factors of technology start-ups, an analysis of the world’s most attractive entrepreneurial start-up ecosystems, and the place of Russian technology entrepreneurs on the map of successful global start-ups.

This paper empirically analyses the determinants of foreign direct investment inflows into the Russian regions. This problem has become highly relevant for the necessary modernization of the Russian economy after the recent economic slowdown and sharp decrease in budget revenues. The authors model foreign direct investment flows with the use of the gravity approach according to which investment flows are positively correlated with the size of the investor’s country as well as the size of the recipient region and are negatively correlated with the distance between investor and recipient. The empirical analysis is based on a constructed database consisting of the foreign direct investment flows from 179 investor countries into 78 Russian regions for the period 2006–2013. The authors apply the Poisson Pseudo Maximum Likelihood method and identify the following factors determining foreign direct investment inflows into the Russian economy: the gross domestic product of the investor’s country, the gross domestic product per capita in the recipient region, the distance from the investor to Moscow, the openness of the region, the economic situation in the region, the innovative capacity of the region and the foreign direct investment of the previous period. Interestingly, the distance from the recipient region to Moscow matters for the regions in the western part of Russia (relatively close to Moscow) but is not significant for the regions in the eastern part (remote regions).