Development of the integrated quality management model for increasing the strategic performance of enterprises in the automotive industry

The facilitation of economic transactions and friendly investor environment is undertaken through effective performance of financial systems. Mobilization of savings and funding the profitable business opportunities are essential in improving the efficiency of intermediation. The study aims to evaluate the effects of nationalization and privatization on Indian banks. Various factors have been considered to examine the effects of privatization and nationalization, including sources of public sector inefficiency, measures of firm performance, econometric issues, and the mode of privatization. The data was collected for the period of 1998 to 2016 from Indian banks. Data Envelopment Analysis (DEA) was used to evaluate the financial reports of the banks selected to evaluate the efficiency of input and output variables. Positive results were observed, concerning the efficiency and profitability of banking industry after banks’ privatization. Performance of private banks has been observed effective and efficient as compared to the public sector banks. Privatization of banks must be increased and maintained to sustain the efficiency of the banks and implement strategies to maintain the assets. Future studies may recruit more appropriate sample size to evaluate the privatization and nationalization effects of Indian banking industry. Greater number of banks will provide more precise results, using data envelopment analysis.

VUСA is a chaotic and rapidly changing business environment that, based on the variability, uncertainty, complexity and ambiguity of the modern world, transforms the approach of banks to the analysis of financial stability. The aim of the paper is to improve tools for monitoring the impact of VUCA-world conditions on the financial stability of banks, namely a model for studying and analyzing the impact of the modern business space “VUCA” on the financial stability of the country's banks. To test the model, the method of constructing regression equations in multifactor regression analysis is used. For this study, data from some Eastern European countries (Ukraine, Belarus, Latvia, Lithuania, Moldova) were used, and time series data were used for 10 years from 2010 to 2019.
Having considered the definition of “VUCA-world conditions”, the model of modern business space “VUCA” was developed when analyzing the activity of banks in the studied countries. Drivers, consequences, requirements and macroeconomic indicators of the countries’ activities in the VUСA-world conditions are determined. The VUCA-world conditions also consider the study of key macroeconomic indicators that allow building long-term relationships throughout the value chain. The analysis of the studied Eastern European countries showed that with the increase of factors of GDP growth, GNI per capita growth, research and development costs, foreign direct investment, and net inflow of 1%, the effective ratio of bank capital and assets also increases. The assessment, in contrast to the existing ones, makes it possible to consider the impact of the macroeconomic environment of banks on their financial stability.

The paper deals with the assessment of the socio-economic development of Ukrainian regions using Data Science methods and multidimensional analysis, including taxonomy, n-dimensional classification, and ensemble decision trees methods. The methodological bases of economic regions devel¬opment by the economic and mathematical modeling methods were investigated. The necessity of improving and further developing estimation models of the regional economic development using business analytics tools and multidimensional scaling methods was investigated.
The ensemble decision trees methods was applied for the classification model of economic development of the Ukrainian regions according to the conceptual base of the research on regional econom¬ic development. It will increase the quality level of administrative decisions making on regional de¬velopment asymmetry equalization. It is determined that in Ukraine, there is a significant imbalance of regions clusters with high and low economic level. Here was investigated the relationship between the two groups of economic development indicators – the indicators of the economic development regional performance and the group of economic potential. The results of the classification model allow identifying the set of indicators that have significant impact on the overall economic development. The developed ensemble model allows carrying out qualitative recognition and prediction of the state probability of economic development. It will improve the quality of decision making pro¬cesses on equalization of regional development asymmetry.
The further research gives the possibility to develop the system of levers directions of regional development imbalance equalization, to determine priority vectors of sustainable development of both the regions and the country.