Digital Economy & Innovations

Today, there is growing interest in studying the level of economic complexity, which is considered one of the factors capable of influencing economic growth. The economic complexity index is calculated based on export data, which allows analyzing the diversity of exported goods, determining the complexity of the production process, and reflecting the level of knowledge and skills required in the production of exported goods. The purpose of the research is to determine the level of economic complexity of regions and to identify the relationship between this indicator and the Gross Regional Product (GRP). A modified method of the Economic Complexity Index (ECI) is used. Based on the Revealed Comparative Advantage (RCA) index, a binary matrix is constructed, reflecting the structure of regional commodity specialization and enabling an assessment of the level of economic diversification. A correlation analysis between the complexity index and regional GRP was conducted. The empirical basis of the study consisted of official data from the Federal Customs Service of Russia on exports by commodity groups for 2021, covering 84 Russian regions. The results showed a weak negative correlation between the complexity index and GRP (r=−0.129). Excluding oil and gas regions changed the nature of the relationship to weakly positive (r=0.067), indicating a strong influence of the extractive sector on the analysis results. Thus, the study did not reveal a stable relationship between economic complexity and GRP, but it identified goods with high prevalence and unique products, as well as determined the most diversified regions. The identified patterns require further additional research. The obtained results can be applied in management practice for formulating more evidence-based socio-economic policies, taking into account the structural characteristics of regions.

In the modern era of globalized financial markets, the investment process has reached a qualitatively new level, transcending national borders and transforming into a complex ecosystem of international capital. Within this context, global investment funds play a key role, having evolved from simple financial intermediaries into powerful and flexible forms of international business organization. By accumulating resources from millions of investors and using advanced analytical and technological tools, they both follow global trends and actively shape them, determining the direction of financial flows and becoming the architects of a new investment reality. This paper attempts to describe the business models used by global investment funds, reducing them to a certain uniformity by identifying strategic patterns of action during crises and taking into account unfolding contemporary trends (geographic diversification, ESG standards, and technological transformation). The discovered patterns formed the basis of strategic models: Conservative Giants, Aggressive Innovators, and Balanced Generalists. These models reveal the underlying business models of funds and serve as a practical tool for management companies and regulators, enabling them to forecast trajectories of the global investment landscape and optimize business models in the face of increasing volatility and technological change. The obtained results can be used by regulators to develop more balanced approaches to supervising cross-border capital movements, as well as by asset managers to select optimal development strategies.