RESUMO
The main goal of this study is to evaluate the impact of population mobility on electricity generation in Russian cities in the conditions of the spread of COVID-19, and identify hotspots. Furthermore, the evaluation is also conducted using hybrid fuzzy decision-making modelling. In this context, q-ROF DEMATEL and TOPSIS methods are taken into consideration. Additionally, a comparative evaluation is also performed with the help of Intuitionistic and Pythagorean fuzzy sets. The results are quite similar that allows to conclude that the findings are reliable and coherent. The study proves the hypothesis that human behavior changed during the COVID-19 pandemic, and electricity consumption is declining in major cities around the world. The biggest fall in energy generation was in Moscow and Yekaterinburg. In St. Petersburg and Nizhny Novgorod, the fall in energy generation is no so crucial because these cities have low building density. The study uses Long Short-Term Memory models with many different parameters. The Q-Rung Orthopair Fuzzy Sets model forecasts new COVID-19 using ten parameters. This study identifies factors influencing the spread of COVID-19 based on the theory of "broken windows" and outlines directions in limiting population mobility, which can form the basis of state policy. According to the analysis the air temperature is the variable that most affects this process.
RESUMO
The US government proposes to impose tariffs on up to $50 billion of Chinese imports leading to significant concerns over the Trade War between the US and China. The article evaluates and examines the market responses of companies in both countries, depending on their direct and indirect exposures to US-China trade. Moreover, this paper fills the gap in literature about deglobalization in Energy and Resources Sectors in Africa. This paper proves the idea that US companies that are more dependent on exports and imports from China have lower stock and bond returns, and, at the same time, higher default risks in the short time aspect. The article found Trade War effects in energy and resources companies in Africa in the last years: on ownership rank, on credit country rank, on default risks and on their profitability. The paper also demonstrates that companies' indirect exposure to US-China trade through domestic input-output links affects their responses to news on the subject matter. These findings suggest that the state of US-China trade of energy and resources is much more complex than the simplistic view of global trade that was in the beginning of Trade War with China. As a result of the Trade War, the real changes in stock prices of China companies (-0.07%) in energy and resource sectors is less than the same changes in US companies in Africa (-0.32%) in 2019. Also, the probability of default of Chinese companies (average default probability changed in -0.08%) in energy and resource sectors changed less than the same rank of US companies in Africa (average default probability changed by -0.84%).