The Energy of Finance in Refining of Medical Surge Capacity

The Trait of Extraversion as an Energy-Based Determinant of Entrepreneur’s Success—The Case of Poland

The fact that personality traits play an important role when it comes to predicting people’s entrepreneurial behavior is currently indisputable. However, so far, the majority of subject literature has focused on employee characteristics in developed countries. To address this gap, research was conducted, including 188 entrepreneurs of small and medium enterprises (SME) and 21 highest-level employees in Poland—one of the countries with the most hostile and turbulent environment for entrepreneurial operations in the world. The five personality traits (Big Five) were evaluated using the 60-item scale. There were three objectives of this study: to identify the differences between entrepreneurs and the most effective, highest-level employees, in the context of personality trait intensities, to determine the level of specific trait(s) intensities (OCEAN) of an effective entrepreneur. Finally, to determine whether it is possible to construct a model based on BIG5 to estimate the probability of success as an entrepreneur. The research results imply there are significant differences between successful entrepreneurs and highly effective employees and their personality trait intensities, described in the BIG5 model. Moreover, it is possible to distinguish trait intensity ranges, determining the success as an entrepreneur. Finally, we constructed the empirically based model, which allows us to estimate the chances of an individual succeeding as an entrepreneur with only a 5% error rate. The main factor and common denominator of entrepreneurial effectiveness is the trait of extraversion. The findings of our study are particularly important for the renewable energy sector in Poland, as the last part of green energy implementing blockchain (e.g., the installation and maintenance of wind turbines and solar panels) is being undertaken, in vast majority, by independent contractors and SME owners (entrepreneurs).

Examining Statistical Methods in Forecasting Financial Energy of Households in Poland and Taiwan

This paper examines the usefulness of statistical methods in forecasting the financial energy of households. The study’s objective is to create the innovative ratios that combine both financial and demographic information of households and implement them in the forecasting models. To conduct this objective, six forecasting models are developed using three different methods—discriminant analysis, logit analysis, and decision trees separately for households in Poland and Taiwan. Such a research approach will answer the question whether the implementation of constructed ratios can increase effectiveness of the forecasting model and its’ versatility between different economic regions. The research relies on four samples of households—two learning samples and two testing samples (one for each country) consisting of 2400 households from both countries. This study is one of the first attempts in the literature globally to develop forecasting models based on ratios constructed with a combination of two different types of variables—one financial with one demographic variable. Findings confirm the high usability of the proposed innovative approach for forecasting the financial energy of households by taking into account a wide spectrum of diagnostic variables representing the financial strength of consumers.

COVID-19 Response and Prospects of Clean/Sustainable Energy Transition in Industrial Nations: New Environmental Assessment

Coronavirus Disease 2019 (COVID-19) became a pandemic around the world and has huge impacts on our economic and social systems, particularly on the healthcare system and the transportation and energy sectors. To examine a relationship between healthcare and energy sectors in the COVID-19 era, we propose a holistic application of Data Envelopment Analysis for Environmental Assessment (DEA-EA) to assess the COVID-19 response performance of 33 OECD (Organization for Economic Co-operation and Development) nations and investigate whether health insurance systems contribute to the performance. We also associate the performance with mobility, which is an energy consumption measure, to test the relationship through statistical analyses. In the DEA-EA, particularly, this study incorporates undesirable outputs (i.e., the number of confirmed cases and that of deaths) as well as desirable outputs (i.e., the number of total recovered people and that of total tested people) during April 2020 as the initial stage of COVID-19. While the former outputs need to be maximized, the latter ones need to be minimized in the assessment of healthcare system performance. This study finds that (a) the COVID-19 response performance of countries is varying and those with higher public health coverage have outperformed others with lower public coverage in terms of combating the COVID-19 outbreak, and (b) the healthcare system performance is significantly associated with mobility. Particularly, the second finding indicates that outperforming nations in the healthcare system are returning to the normal (with less volatility) while underperforming ones are still stagnating in terms of mobility. It implies that outperforming countries need to prepare for continuous commitment to clean/sustainable energy transition.

Meta-analysis in management and quality sciences

This study on the methodology of conducting the research process indicates the scarcity of an empirical approach to a problem of quality of the research process. In this paper, the determinants of the quality of the research process in the management sciences were examined. The authors employed the commonly used principal component analysis (PCA), also known as factor analysis. Furthermore, the article presents a holistic, structured and configurable framework that would result in the construction of an appropriate research methodology. The research work carried out within the discipline of management sciences must be embedded both in terms of theory and practice. Although the management sciences are most often treated as applied or practical sciences, they also undertake theoretical research in their scope, because no science can develop without theoretical research. This paper aims to identify the factors influencing the quality of the research process as the complementary elements to the contemporary methodological approaches. The analysis of the domestic and foreign scientific background, as well as the drawn conclusions, turned on the modifications introduced over the years in the management methods. The management methodology is constantly expanding by new methods, the latter being of diverse cognitive and practical effectiveness. The constant growth of diagnostic instruments has been dependent, mainly, on changes occurring in the environment. Moreover, it is connected to the need to make use of more sophisticated and effective tools. The article focused on meta-analysis as a research process and qualitative approach to the research process on the example of research results. Empirical research confirms the existence of factors that constitute a criterion supporting the assessment of the quality of the conducted research process. In the management sciences, the quality of the research process is defined as verifying the degree of implementation and consistency of the objectives of the work following the research problem and conclusions.

Innovation technology and cyber frauds risks of neobanks: gravity model analysis

In the system of global information space, it is important to adequately calculate and assess the factors of successful functioning of the banking system, which are directly the engines of the country's development, economic stability, especially from the standpoint of qualitative measurement of innovative technology and human capital in rapid cyber fraud. The work is devoted to studying factors that describe the components of efficiency and potential use of innovative technologies in neo-banking in 90 countries to determine the level of risk of their use for money laundering based on gravitational modeling methodology. The authors substantiated that using four factors consisting of 13 components of digital evolution is expedient. Three indicators (access infrastructure, transaction infrastructure, and fulfillment infrastructure) allowed forming the supply condition factor. It provides a score on developing digital and physical infrastructure to ensure the digital economic system's quality. The «demand conditions» factor consists of 4 indicators (human quality level, device absorption level and digital broadband level, digital payment absorption), which show how much consumers are willing and able to participate in the digital economic system and whether they have the tools and skills needed to connect to the digital economy. Three indicators (institutional effectiveness and trust, institutions and the business environment, institutions and the digital ecosystem) shaped the «institutional environment» factor. It relates to research on countries' support for digital legislation, governments' investment in digitalization, and regulations. Regulate the quality of storage and access to digital data. The fourth factor of «innovation and change» consists of three features that characterize the state of key innovative economic system inputs (talents and capital), processes (i.e., cooperation between universities and industry), and outputs (i.e., new scalable digital products and services). The generalized indicator was formed based on these indicators. It characterizes the degree of risk of using the services of neobanks of the studied countries by economic agents or individuals to legalize criminal proceeds. At the first stage of the proposed method, the authors substantiated the statistical significance and possibility of using the studied indicators. The procedure of logarithmic normalization was carried out. The toolkit of descriptive statistics of the Statgaphics Centurion package provided the normalization parameters. In the second stage, the indicators were collapsed using a geometric weighted average, which provides meaningful information about the average dynamics rate. The third stage provided calculating the value of the integrated rating assessment of the degree of risk of using innovative technologies, services, and neobanking services for money laundering based on gravity modeling methods. The findings showed that 12.22% of the studied countries had a high degree of risk, 25.56% – a medium level of risk, 25.56% – a risk below the average level, for 36.66% of countries – the risk was almost absent.