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Machine Learning and Data Balancing Methods for Bankruptcy Prediction
Full text linkThe paper examines the use of various machine learning algorithms for the task of forecasting the company’s bankruptcy based on financial indicators. Different approaches to the formation of the data set on which the models are trained are compared, in particular, data balancing methods. Nine machine learning algorithms are implemented, in addition five data balancing methods (random oversampling, SMOTE, ADASYN, random undersampling, and near miss) were applied to classification tasks. It was found that bagging and random forest together with Near-Miss and Random under-sampling showed the best results in terms of the possibility of identifying bankrupt companies in small samples, while artificial neural networks and decision tree methods, together with SMOTE and random resampling, worked better on large samples. With highly unbalanced data accumulation, both small and large training samples can be used to distinguish between bankrupt companies
Optimization of Media Strategy via Marketing Mix Modeling in Retailing
Full text link The paper describes the marketing mix modeling results for companies in nonfood retailing. The main objectives of the research are to demonstrate the viable way of making effective recommendations for optimizing the media strategy by modeling offline and online traffic to the stores based on econometric modeling and to develop a decision support system, which enhance the effective growth of business KPIs and an effective decision-making process. Econometric modeling, deeper data analysis, decision support were implemented on the data of one of the main retailers in Ukraine in a period before the full-scale Russian invasion. Estimating the impact of different communication channels on business results made basis for ROI calculations and optimization of media investments allocation among media channels by periods, video durations, type of advertising and with optimal weekly media pressure. ROMI calculation was based on the results of regression modeling, which estimate the level of traffic and sales generated by each media channel. The information-analytical decision support system based on an interactive dashboard has been developed for improvement of day-by-day business planning and management. The developed framework of regional strategy selection facilitates to the formation of a strategic vision on a regional scale and improves the quality of a regional media strategy
SOE Corporate Governance Reform in Lithuania - Explained & Еmpirically Tested
Full text linkFollowing previous research on management efficiency of state-owned enterprises (SOEs) in Lithuania, this paper continues previous discussion via extension of the observed time period seeking to continuously analyze the impact of corporate governance principles to the management effectiveness of Lithuanian SOEs.For the purpose of this study, elements of corporate governance principles established in the initial reform of the SOEs in Lithuania are used as key dependent variables to measure and quantify the dynamics of corporate governance culture and its impact to the management efficiency of SOEs. Analysis performed is of a special importance as it covers the 10-year period (2010–2020) and could serve as a case study in analyzing practical implications of managerialism principles in public sector and SOEs specifically.New public management paradigm (Politt, 1993) combined with policy learning theory (Bennett, Howlett, 1992) are used as the theoretical background to explain the initiation and logical framework of SOE reform as well as the selection of variables used in this study. Additionally, principles of corporate governance established by OECD and other international organizations (OECD, 2015) are also used to enrich the analytical framework.The results of the analysis do not only prove that the implementation of corporate governance principles has a positive influence on the efficiency of management of SOEs, but also reveals additional factors that were not identified in the previous research – this impact is not static, but rather dynamic changing in accordance with the maturity of managerial practices within SOEs. The revealed dynamic nature of effects of the SOE policy should lead to the continuation of research seeking to expand it both geographically and vertically including other governmental organizations into the scope of future research
Development of Energy Supply Infrastructure Based on Industry 4.0 (on the Example of Ukraine and Turkey)
Full text linkThe object of research was to identify the field of renewable energy for ensuring the process of gradual transition from traditional energy to carbon-free technologies. The article compares the opportunities for energy development, taking into account current trends in sustainable development. The conducted analysis of energy resources in the section of renewable energy is based on the processing of available sources of analytical and statistical information. The study investigates the structure and features of the functioning of the energy sector of Ukraine and Turkey. There have been revealed several common problems of functioning of energy spheres in Ukraine and Turkey. The article investigates the possibilities of using technological solutions and principles of Industry 4.0 in ensuring energy security through the development of the electric car market. The analysis consists of calculations of the efficient functioning of solar and wind energy for Ukraine and Turkey. The article provides recommendations for the development of possible mutually beneficial cooperation between Ukraine and Turkey in the field of renewable energy
The Initial Impact of The Covid-19 Pandemic on Older Workers in Lithuania
Full text link The Covid-19 pandemic that began in 2020 presented a new challenge for the labor market participants. This paper discusses the Covid-19 pandemic, highlighting the key challenges that older people can face trying to stay in the labor market for longer in the future, especially if such pandemics continue. Binary response models are used to identify the push-and-pull factors determining the impact of the Covid-19 pandemic on the employment of people aged 55–64 during the pandemic in Lithuania. As the Covid-19 pandemic still continues, most of researchers prefer statistical analysis, comparing employment rates with those of the 2009 economic crisis, to determine the potential impact of the pandemic on employment or by only theoretically discussing the potential impact of the pandemic on the elderly. This paper models the impact of the pandemic on the employment of older people in Lithuania using unique administrative micro-data of State social insurance fund (SSIF). This allows to draw deeper conclusions about how the pandemic affects workers aged 55–64 in Lithuania. The results show that the employment of older people has not been disproportionately impacted by the Covid-19 pandemic, and if such pandemics occur in the future, they may present both limitations and opportunities from the point of view of older people
Evaluation of the Symmetrical and Asymmetrical Causality Relationship Between Bitcoin Energy Consumption and Stock Values of Technology Companies
Full text linkEnergy production is a phenomenon that has always preserved its importance for the history of humanity, as well as where the energy is spent and its consumption are also important. This study examined the causality relationship between Bitcoin energy consumption and Apple, Dell Technologies, Lenova Group, HP, Quanta Computer, Compal Electronics, Canon, Wistron and Hewlett Packard Enterprise has been taken into account to represent technology companies’ stock market. In the analysis, daily price data for the period 12.02.2017-07.02.2021 were used. Toda-Yamamoto (1995) symmetric causality test and Hatemi-J (2012) asymmetric causality test were used for used to determine the relationship between Bitcoin energy consumption and technology companies’ stock values. According to the results of the Toda-Yamamoto (1995) causality test, it has been found that there is a causality from Bitcoin energy consumption to Apple\u27s stock value; according to the Hatemi-J (2012) asymmetric causality test results, it has been determined that there is a causality from Bitcoin energy consumption positive shocks to Apple, Dell Technologies, Lenova Group, HP, Quanta Computer, Compal Electronics, Canon, Wistron and Hewlett Packard Enterprise stock values negative shocks and from Bitcoin energy expenditure negative shocks to Hewlett Packard Enterprise negative shocks. According to the results of the study in general, it is seen that the change in Bitcoin energy consumption has an effect on the firm returns of the companies that sell the necessary tools for bitcoin energy production. From this, it can be commented that bitcoin mining is also effective on the stock returns of technology companies as well as many financial factors
The Impact of Income Inequality, Renewable Energy Consumption, Non-Renewable Energy Consumption and Per Capita Income on Poverty: Evidence from BRICS Economies
Full text linkThe main purpose of this study is to investigate the role of income inequality, per capita renewable and per capita non-renewable energy consumption, per capita income on poverty reduction in BRICS (Brazil, Russia, India, China, South Africa) countries over the period between 1991–2019. This study used second-generation panel data methodologies taking into account cross-dependence between countries, which gives more accurate results. The outcomes of the panel ARDL unveiled that while an increase in income inequality and per capita non-renewable energy consumption increases poverty, an increase in growth and per capita renewable energy consumption decreases poverty. Based on the findings, policymakers should focus their efforts on developing an appropriate energy strategy that highlights the necessity of a renewable energy-driven economy powered by energy-saving technologies
Determinants of Bilateral Trade Balance Between Georgia and China
Full text linkThis paper aims to empirically examine the drivers of the bilateral balance of the trade model for the Georgian-Chinese economy from 2000 to 2020 and the influence of the Georgia-China free trade agreement on the Georgian-Chinese balance of trade. The Error Correction Model (ECM) of the ARDL was used to see if the balance of trade and its predictors have a long-term relationship. One of the ARDL’s defining properties is that it may be utilized in circumstances when there is minimal data, regardless of the level of variable integration. According to the findings, a perceived effective exchange rate has a statistically significant positive impact on the balance of trade in the long run and a statistically significant negative impact on the balance of trade in the short run. The output is shaped to favor the presence of the elasticity attitude’s J-Curve impact. The study also found that the comparative supply of money (MS) and GDP have only a minor impact on the trade balance in the medium and long run. The sponging and monetary methods are ineffective in characterizing the bilateral trade deficit between Georgia and China
Overcoming the Inadequacy of Economic Dynamics Models
Full text linkKnown models of economic dynamics are too aggregate, so inadequate to the real economy. The analyst will not be able to identify the real dynamics of the economy among the big mistakes. They have no connection between investments, their efficiency, and the rate of economic growth. There is no transition from the optimal share of savings in the country to the agents’ optimal shares, managing investment sources.To link investment and the pace of economic growth, the author introduced the concept of technical productivity of investments, which measures their ability to change the rate of material or labor costs.Based on the technical productivity of investment, the author has derived the equation (not identity) of economic dynamics.Instead of the highly aggregated models, the author developed an adequate causal simulation model, reflecting the economy as a closed system with positive feedback of the investment from incomes and economic growth from investment. The author determined the dynamics of the Ukrainian economy with different technical productivity of investment on this model