| Abstrakt: |
In the context of increasing economic imbalances, the goals of bank reorganization are being transformed and are acquiring new content, which increases the relevance of macroeconomic factors. The article is aimed at identifying the impact of macroeconomic factors on the choice of reorganization method by building a neural network like the Kohonen map. A cluster analysis method has been applied to build a neural network of the type of self-organization maps of Kohonen. As a result, has allowed four clusters. The first cluster includes developing countries. The most common methods are M&A agreements and buyback operations. Among the priority factors of influence are a high level of GDP per capita, a growing share of the urban population, and significant tax revenues. The second cluster includes developing countries, for which consolidation methods such as partial absorption, and acquisition of fixed assets are a priority. Among the main factors influencing, it is worth highlighting commodity trade, inflation, and the GDP deflator. The third cluster includes highly developed, developing countries, for which the dominance of share buyback agreements, which is primarily related to the share of foreign direct investments, the volume of GDP and the volume of tax revenues. The fourth cluster includes mainly developed countries, that are not included in the third cluster. Due to the determining influence of significant volumes of domestic crediting, foreign direct investments, GDP and a significant share of gross accumulation, practically all methods of reorganization are common in these countries (M&A, buybacks can be singled out among the most common transactions). [ABSTRACT FROM AUTHOR] |
