Generolo Jono Žemaičio Lietuvos karo akademija

The multidimensional comparative analyzes of transportation of people by rail were used in the article. The time series was analyzed and evaluated in order to detect the following phenomena: trend, seasonality and random factor. The initial time series was divided into parts in order to remove data that, due to the impact of a random phenomenon such as the COVID-19 pandemic, lost trends visible in the past (from January 2012 to December 2019). The Winters’ exponential smoothing method was used for the forecasting. The obtained forecast for 2024 is 390 380 000 passengers transported by rail in Poland. The mean absolute forecast error is 2,18.

The article presents a multidimensional comparative analysis of the number of passengers transported by air in Europe between 2019-2022 in terms of economic security. Data for the study was taken from Eurostat and categorized line and bar graphs were used. The conducted research shows that in 2021, in each of the considered European countries, an average of 138% of the number of passengers of 2020 were transported by air. In 2022, an increase to 230% of the number of passengers of 2021 was observed. The forecasting of the number of passengers conducted by air transport for 2023 in 29 European countries under consideration was made. A naive method was used for the forecasting. In 2023, the largest number of passengers will be transported in Spain, followed by Germany in the second place and France as third. The sum of the forecast of the number of passengers transported for 2023 in 29 European countries under consideration will equal 1 401 839 218 people and will be higher than in 2022 by 296 222 604 people.

The study attempts to forecast the total costs of a company in Poland. The first stage of the research was analyzing and evaluating the time series of total costs. It detected: trends, seasonality and a random factor. This became a premise for the application of two methods for forecasting: Holt-Winters’ multiplicative and additive. The research shows that the Holt-Winters’ multiplicative model proved to be better in forecasting total costs in the research subject. The forecasted total costs from July to December 2022 will reach PLN 45 395 685, while from January to December 2023, their value will amount to PLN 85 948 927.

The research includes a multidimensional comparative analysis of electricity prices in 28 European countries for non-household consumers. The highest energy prices in the first half of 2022 were also ranked in the respective analyzed countries. Increases in electricity prices for non-household consumers were examined in terms of percentage and value from the second half of 2019 to the first half of 2022 and the increases were ranked. Their leader in terms of percentage and value was Greece with the result of 353,50% which constitutes EUR 0,288 of the price increase per 1 KWh in the considered time period. A multiple regression model was also built and showed that the time series of natural gas price quotations had an impact on the increase in electricity prices for non-household consumers.

The study comprises a multidimensional comparative analysis of the number of passengers transported by rail in twelve European countries between 2019-2021; the considered data were grouped and analyzed. The dynamics indices with a constant base were used in the study. The aim of the article was a comparative analysis of the number of passengers transported by rail in the European countries under consideration between 2019-2021. The result of the research is the observation of an increase in the number of passengers transported by rail in twelve European countries in 2021 compared to 2020 by 374 965 people. It was visible in nine out of the twelve countries considered. The largest one was observed in France, with around 170 544 passengers. Considering the percentage increase between 2020 and 2021 in respective countries in rail passenger transport, it was observed that the most significant increase was in Italy, which amounted to 25,61%.

The study presents a multidimensional comparative analysis of two dependent variables: the number of passengers transported by air in 28 European countries and the price of one barrel of crude oil in dollars. The conducted analysis shows that in the historical data concerning the identical periods (months) in both tested series, dependencies can be found. This allowed for the construction of a zero-one multiple regression model in order to confirm the impact of the number of passengers travelling by air on the price of one barrel of crude oil and describe this phenomenon with an analytical function.

The multidimensional comparative analysis and the forecasting of minimum salaries in 21 European countries were conducted in the study. The research began with the ranking of the data, the amount of salary rates taken as a basis, the rise expressed in euro and the values of dynamics indices on a constant base. Then the data was aggregated. The time series of the lowest salaries in 21 European countries was analyzed and evaluated. Thus, regularities were observed that were used to select the Holt-Winters’ exponential smoothing method for the forecasting of these salaries. The obtained forecasts were analyzed and evaluated with the use of indices, such as forecasting errors.

The study includes an analysis of the functioning of micro, small and medium-sized enterprises during the COVID-19 pandemic from the perspective of financial security management of these entities. The article covers the identification of threats in the area of finances of the discussed enterprises that arose during the pandemic, as well as the assessment and approach to financial risk management in these entities. As a result, the key categories of threats to the financial security of enterprises, arising during the COVID-19 pandemic, were presented, as well as the assessment of the effectiveness of state services responsible for ensuring financial security. The study focuses on multidimensional data analysis in terms of their grouping and unraveling in terms of comparing the considered variables in terms of dynamics. Initial studies were performed by comparing several variables, and the data were analyzed not only during the COVID-19 pandemic, but also in the pre-pandemic period in terms of observing their fluctuations in dynamic terms, and the relationships between them were also examined.

Forecasting of monetary policy tools, including reserve money of the Central Bank of Poland, in order to optimise economic decisions made by business entities operating on this market, becomes a basic canon of knowledge, in order to minimise a risk of undertaken economic operations – is currently the area of our investigation. The article raises a problem of forecasting the reserve money of the Central Bank of Poland on the basis of initial information received from the National Bank of Poland. The studies started with analysis and evaluation of time series of reserve money of the Central Bank in Poland. Then the analysed series were divided into two parts. Based on obtained results, the researchers performed forecasting of the first part of separated time series of reserve money of the Central Bank in Poland with the use of different methods. The above mentioned time series consists of 132 elements. Later on, the researches chose the best forecasting method and that was the basis for initial time series forecasting of reserve money of the Central Bank in Poland in mil PLN in retrospective terms during 2010-2021 for the next 2021-2022 years.

The article presents a multidimensional comparative analysis of the exchange rates of five currencies: dollar, euro, franc, pound and ruble in zlotys and crude oil in dollars per barrel from 2005 to 2022. The research was conducted in terms of the identification of contemporary challenges for the economic security of enterprises in Poland. Grouping was used as part of multidimensional comparative analyzes. In the categorized line charts, in order to observe the trends in dynamic terms as a decrease and an increase in the rates of the analyzed data, a separate Y-axis scale was assigned to each of the analyzed dependent variables.