In modern conditions of increasing trends of globalization, growth of interstate trade and information exchange, as well as other forms of interaction between countries, issues of territory development in terms of competitiveness and stability of its business environment, including in the aspect of increasing its attractiveness for investment flows, are becoming more and more relevant. Taking into account the importance of business environment quality for the development of border areas, this article analyzes the influence of many factors on the investment attractiveness of the Dnipro-Dvina region (hereinafter DDR). The analysis was carried out in two stages. First, the article presents the main theses of Russian and foreign scientists researches, identifies the key factors of border territories development in their opinion. At the second stage, the factors identified in the framework of the theoretical study were analyzed on the basis of studying the dynamics of Russian-Belarusian border regions development. The results show that the level of innovative and industrial development of border regiong, which determines its ability to generate added value, depends on the degree of investment risk, the conditions for opening and running a business, and border territory investment prospects. The article analyzes methodological and methodological approaches to the analysis of socio-economic factors that affect the regional investment attractiveness development. Constructed factor model allowe us to assess the impact of generalized factors that characterize various aspects of socio-economic region development on the level of business environment investment attractiveness of the border territory. The factors identified in the study will contribute to the implementation of a well-founded regionally differentiated policy for the border regions development in the context of interstate Russian-Belarusian integration.
factor analysis, regional development, Analysis of business environment, Countries integration, Border region, Principal component analysis