Quantitative assessment of the financial hardship in the euro area countries.

The article examines financial hardship (FH) that appears as one of the essential socio-economic-financial categories reflecting a financial burden on society and therefore having a significant impact on the social and economic development of the country. The purpose of this article is to propose and approve a methodology for the complex quantitative assessment of financial difficulty, which allows comparing countries one another. The novelty of the conducted research is manifested by the formed financial hardship adequately exposing a system of indicators and suggesting the transformation of incomparable indicators into the comparable ones. The paper proposes a methodology for the integrated assessment of financial hardship based on multi-criteria methods, which contributes to solving the problems of the social sustainability and economic development of the countries employing different research methods. The proposed methodology provides a possibility of moving to a higher level of research comparing the countries as a whole, in line to the current status of FH. The actual benefits of the carried out research arise from the opportunity to envisage targeted measures for increasing social sustainability subject to the specific situation of the financial hardship of the countries thus removing the burdens of further economic development.

The role of nuclear energy in low carbon energy transition: evidence from panel data approach in EU.

The aim of this study is to employ panel data approach to investigate determinants of total GHG emissions in all European Union (EU) economies in years 1990-2018 and evaluate the role of nuclear energy in climate change mitigation. It incorporates the following variables potentially affecting the greenhouse gas (GHG) emissions: economic-gross domestic product (GDP) per capita and GDP per capita squared to control for non-linear relationship between economic output and GHG emissions; structural-economic structure reflected in the share of manufacturing in total gross value added (GVA); energy-mix-share of nuclear power and renewable sources in total gross electricity production; environmental policy-the amount of environmental taxes (as a percentage of GDP) and the number of European Union Emission Trading System (EU ETS) allowances auctioned or sold (as a percentage of GDP per capita). The main findings of this study confirm the long-run relationship between GHG emissions, GDP level, and energy-mix variables. It endorses that higher share of nuclear power together with renewables in gross electricity production has significant impact on GHG emissions in the long run. In turn, it also validates the existence of the environmental Kuznets curve for selected countries.

Resources curse hypothesis and COP26 target: Mineral and oil resources economies COVID-19 perspective.

In recent times, industrialized economies have focused more on achieving a sustainable environment while maintaining economic prosperity. However, it is clear from the current research that natural resource exploitation and decentralization substantially affect environmental quality. To experimentally validate such data, the current study examines decentralized economies during the previous three decades (1990-2020). This study discovered the existence of long-term cointegration between carbon emissions, economic growth, revenue decentralization, spending decentralization, natural resources, and human capital using panel data econometric techniques. The findings are based on non-parametric techniques, indicating that economic growth and revenue decentralization are the primary barriers to meeting the COP26 objective. Human capital drives down carbon emissions and contributes to meeting the COP26 objective. On the contrary, decentralization of spending and natural resources has a mixed influence on carbon emissions across quantiles. This report recommends investing in human capital, education, and research & development to speed up COP26's target accomplishment.

The Aspects of Artificial Intelligence in Different Phases of the Food Value and Supply Chain.

The types of artificial intelligence, artificial intelligence integration to the food value and supply chain, other technologies embedded with artificial intelligence, artificial intelligence adoption barriers in the food value and supply chain, and solutions to overcome these barriers were analyzed by the authors. It was demonstrated by the analysis that artificial intelligence can be integrated vertically into the entire food supply and value chain, owing to its wide range of functions. Different phases of the chain are affected by developed technologies such as robotics, drones, and smart machines. Different capabilities are provided for different phases by the interaction of artificial intelligence with other technologies such as big data mining, machine learning, the Internet of services, agribots, industrial robots, sensors and drones, digital platforms, driverless vehicles and machinery, and nanotechnology, as revealed by a systematic literature analysis. However, the application of artificial intelligence is hindered by social, technological, and economic barriers. These barriers can be overcome by developing the financial and digital literacy of farmers and by disseminating good practices among the participants of the food supply and value chain.

Dynamic stability of the financial monitoring system: Intellectual analysis.

INTRODUCTION: Although there is a growing number of scientific publications on financial monitoring, combating money laundering, the shadow economy, and the impact of corruption on economic development, further research needs to determine the stability of the national financial system in dynamics. The dynamic stability of the national financial monitoring system subjects will allow to adequately assess the effectiveness of the existing national financial monitoring system in each country and determine the influential factors. MATERIALS AND METHODS: The article investigates an approach to identifying the dynamic stability of the national financial monitoring system subjects based on the calculation of the integrated indicator of the country's financial system propensity to ALM, vector autoregression (VAR) model taking into account time lag. The proposed integrated indicator allowed to adequately assess the existing financial monitoring systems of the countries (15 countries of the European Union for 2000-2020: Austria, Belgium, Cyprus, Estonia, Finland, France, Greece, Ireland, Italy, Latvia, Malta, Netherlands, Portugal, Slovak Republic, Spain). In addition, vector autoregression models (VAR) of the dependence of the country's financial system propensity to ALM on the regressors Government Integrity, Index of economic freedom, Monetary Sector credit to the private sector (% GDP), were built, taking into account time lags in general and for each studied country. RESULTS: According to the modeling results, the national financial monitoring systems in Austria, Belgium, Estonia, Finland, France, Ireland, Netherlands, Slovak Republic, Spain were resistant to money laundering. It is vice versa in Malta, Greece, Cyprus, Portugal, Italy, Latvia. These conclusions are also confirmed based on a binary approach. Such exogenous variables as Government Integrity (with a lag of 2 years) and the Index of economic freedom (taking into account the time delays of the regression reflection under the influence of this regressor for 1 and 2 years) have a statistically significant effect on the country's financial system. CONCLUSION: The general vector autoregression (VAR) model shows that the current value of the country's financial system propensity to ALM by 92.78% is determined by its previous value. With an increase of Government Integrity by 1%, the country's financial system's propensity to ALM will decrease by 0.000616 units with a lag of two years. The nature of the impact made by the Index of economic freedom on the performance feature was specific-when this indicator increases by 1% for a lag delay in one year, the PFSALM value will decrease by 0.001997 units, and for a lag delay of two years it will change the trend and increase by 0.003076 units per unit, respectively.

Multiplexing efficiency of environmental taxes in ensuring environmental, energy, and economic security.

This paper assesses the multiplexing efficiency of environmental taxes in ensuring environmental, energy, and economic security which is an integral part of sustainability in six European countries that are leaders in the Environmental Performance Index. This study aims to confirm the hypothesis that environmental taxes and payments could simultaneously affect changes in important environmental, energy, and economic security as well as sustainability parameters. Not all the previously selected taxes, which affect the parameters of all three areas of environmental, energy, and economic sustainability and security can ensure their simultaneous growth. Calculations made for the period 1994-2019 showed that in the system of environmental taxation of Denmark, five environmental taxes and fees provide an increase in the integrated level of environmental, economic, and energy security and sustainability; in Belgium, two environmental taxes are characterized by multiplex efficiency; in France, seven environmental taxes and payments; in Austria, four; in Finland, one; and in the UK, four. The paper's findings could create the basis for improving environmental taxation systems in the countries to increase comprehensive national security growth and ensure sustainable development path of the countries.

The impact of COVID-19 outbreak on hotels' value compared to previous diseases: the role of ALFO strategy.

By using the Event Study Method (ESM), this paper aims to examine the effect of new coronavirus (SARS-CoV-2) disease (COVID-19) outbreak on the market performance of the hotel industry in the U.S. We also compare the impact of COVID-19 outbreak with three previous diseases outbreaks. The results show that there is a negative influence of the diseases outbreaks on stock returns of hotels in the U.S. However, the impact of COVID-19 is incomparably higher in magnitude compared to previous diseases. Furthermore, given the importance of following flexible corporate strategies to adapt to new and unpredicted situations, it is found that the ALFO (assets-light, fee-orientated) strategy acts as a mitigator for the predicted market value drop due to the pandemic.

Modeling the mediating roles of self-directed learning and knowledge management processes between emotional intelligence and learning outcomes in higher education.

OBJECTIVE: Drawing on the knowledge-based view and ability-based theories of emotional intelligence (EI), in this study, we investigate the effects of EI on learning outcomes related to academics and administrators in Chinese research universities and we also test the direct association between learning outcomes and creative performance. In addition, we examine the mediating role of self-directed learning (SDL) and knowledge management processes (KMPs) on the relationship between EI and learning outcomes. METHODS: The sample, for this study, consisted of 547 academic and administrative personnel at Chinese higher educational institutions (HEIs), and the hypothesized associations were examined through partial least squares structural equation modeling. RESULTS: Our results indicated that EI has no significant influence on learning outcomes. However, an indirect relationship between EI and learning outcomes is established through SDL and KMPs. CONCLUSIONS: This study strengthens the professional understanding of EI and supports that the personnel at HEIs should value SDL and KMPs, which in turn enhances their learning outcomes. Although EI has received increased importance in higher education institutions, there are few studies that have investigated the relationship of EI, SDL, KMP, and learning outcomes. This is one of the initial studies that has empirically examined the interface of EI and learning outcomes in HEIs and also provides timely insights into the understanding of the mediating role of SDL and KMP.