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There is a significant and supported trend toward the achievement of ensuring continuous door-to-door travel in the pan-European transport network. Many innovative programs are dedicated to this topic through assigned projects. This paper is based on the concrete partial results of the H2020 project Shift2Rail IP4 to support the deployment of mobility as a service (IP4MaaS). Attitudes towards travel for demonstration sites were assessed based on the outputs of a sample of respondents from two countries. Cooperation in working on the IP4MaaS project was also provided by a partner from Slovakia (UNIZA) and the Czech Republic (OLTIS). Mathematical statistical tools were used to evaluate the available data to find a connection with promoting mobility as a service. This paper aims to identify differences in travelers' needs with a focus on using applications using two-step cluster analysis. The research resulted in the identification of differences in traffic behavior within MaaS activities when comparing different clusters reflecting preferences for using a website or mobile application. [ABSTRACT FROM AUTHOR]

Industry 4.0 integrates smart and connected production systems that are pivotal in predicting and supporting production in real-time, leading to sustainable organizational performance. In manufacturing, it may increase productivity, sustainability, and energy efficiency, while optimizing competitiveness. The main purpose of this paper is to determine the impact of Industry 4.0 on the Slovak economy through a secondary data analysis in the automotive industry, which is the leading sector in the country. The paper aims to provide a comprehensive analysis of the various opportunities that are available in the value-added growth of car exports in Slovakia. It also explores the case study of PSA Group Slovakia, which highlights the importance of the Industry 4.0 concept in boosting the country's export growth. The paper proposes a series of recommendations and steps to improve Slovakia's innovation environment. [ABSTRACT FROM AUTHOR]

The paper focuses on analysing the current tax behaviour of Slovak citizens and their inclination to tax evasion. Inclination to tax evasion is defined in this research based on respondents' answers to questions focused on their tax morale. The data processed in this research was obtained from a questionnaire survey on a sample of 1067 respondents. Intentional sampling was used to ensure the same structure of respondents. In terms of tax evasion acceptance, we identified three groups of people: honest, dishonest, and unconscious. The research confirmed that 78% of the population is prone to tax evasion, and only 22% have never evaded paying taxes and would not do so knowingly or unconsciously. By applying the statistical hypothesis testing, we also found out that except for sex (women are less prone to tax evasion), inclination to tax evasion also depends on education, age, main source of income and experience. Finally, three types of logistic regression models to predict the inclination of a specific tax behaviour were constructed and evaluated based on the total accuracy metric and validated on the ex-post set. [ABSTRACT FROM AUTHOR]

Capital structure plays an important role in corporate finance, especially in the period of restrictive monetary policy in many developed countries. This paper aims to estimate the debt ratio based on five selected financial indicators: tangibility, return on assets, size of total assets, current ratio, and size of total sales using multiple linear regression for four countries, such as the Czech Republic, Hungary, Poland, and Slovakia, as well as the V4 region. The total sample consists of 3828 small- and medium-sized enterprises from the transport sector in the Central European area. These data are drawn from Amadeus by Bureau van Dijk from 2019. The results show that three of the five variables are statistically significant in all models. These findings indicate that transport companies prefer the pecking order theory. We find that the increase in tangibility, return on assets, as well as current ratio, reduce the debt ratio. The outputs provide new theoretical and empirical knowledge regarding transport companies in V4. [ABSTRACT FROM AUTHOR]

The objectives of this paper, and the novelty brought to the topic of the Industry 4.0 manufacturing systems, are related to the integration of computer vision algorithms, remote sensing data fusion techniques, and mapping and navigation tools in the Slovak automotive sector. We conducted a thorough examination of Industry 4.0-based value and supply chains, clarifying how cyber-physical production systems operate in relation to collision avoidance technologies, environment mapping algorithms, and mobility simulation tools in network connectivity systems through vehicle navigation data. The Citroen C3 and Peugeot 208 automobiles are two examples of high-tech products whose worldwide value and supply chain development trends were examined in this study by determining countries and their contributions to production. The fundamental components of the research—statistical analysis and visual analysis—were utilized in conjunction with a variety of syntheses, comparisons, and analytical methodologies. A case study was developed using PSA Group SVK data. The graphical analysis revealed that Slovakia offers the second-highest added value to the chosen items, but it also highlighted the country's slow-growing research and development (R&D) infrastructure, which could lead to a subsequent loss of investment and business as usual. Slovakia can generate better export added value by optimizing Industry 4.0-based manufacturing systems in the automotive sector. [ABSTRACT FROM AUTHOR]

The corona crisis has affected not only the economic sphere, but also the sphere of health, health care, employment, safety, and health protection in the workplace, shopping habits, and future expectations, to which people adapt their decisions in various areas of daily life. The COVID-19 pandemic, called a global health crisis, was an unpredictable risk of global proportions that paralyzed the entire world. The main aim of this paper is to quantify the impacts of the COVID-19 pandemic on the construction sector, which is considered a crucial sector of the Slovak economy, to evaluate changes in the development of key indicators using adequate quantitative methods. First, a sample of 2000 businesses were analyzed using the 12 financial indicators that were chosen. Second, using the non-parametric Friedman test, a more thorough study was carried out with a focus on analyzing the existence of statistically significant variations in the values of computed indicators as a result of changes in the development of key financial ratios. The Bonferroni adjustments were employed to pinpoint the areas of stochastic dominance at the conclusion of the study. A detailed analysis of the calculated financial indicators showed that the arrival of the pandemic had a negative impact on many aspects of business in the construction sector and affected the financial and economic situation of companies in the construction sector of the Slovak Republic. However, due to the fact that this sector is characterized by slower reactions to changes in the economy, the most significant impacts will be even more noticeable in the future. [ABSTRACT FROM AUTHOR]

The paper deals with the application of concept mapping in teaching mathematics at the primary level of education (ISCED 1), as well as the experimental verification of its qualitative contribution to the process of education. The authors present results obtained in a sample survey aimed at monitoring possibilities of influencing pupils' relationship to teaching and mastery of mathematics using digital concept maps within the process of pedagogical intervention. The authors tested the degree to which digital concept maps influence changes in the pupils' opinions and attitudes to mathematics (subject popularity, interest in the subject, easiness of understanding, fear and apprehension of mathematics) while explaining and fixating the curriculum of selected mathematics topics in the third grade of a primary school. The results of the experiment did not confirm that teaching supported by concept maps contributes to reducing pupils' negative attitudes towards subjects, particularly in mathematics at the primary level (ISCED 1). Due to the pedagogical intervention of concept mapping, no statistically significant changes occurred in the pupils' attitudes to the observed factors of mathematics. However, the authors have come up with research findings that may be notable in the field of branch didactics of mathematics and digital technologies. [ABSTRACT FROM AUTHOR]

Quality of life can be expressed as a highly subjective measure of happiness, which is an important part of many financial and non-financial decisions. The issue of quality of life, namely its quantification, is a current topic, evidenced by a number of literary sources in both foreign and domestic literature. The paper deals with this issue in the conditions of the Slovak Republic and studies the quality of life for each region of Slovakia with respect to the given indicators. In this paper, we deal with the use of the methods of multi-criteria analysis in evaluating the quality of life in Slovakia. The aim of this paper is to highlight that it is important to monitor the level of quality of life at the regional level and that one of the indicators influencing the quality of life in the region may be its location in relation to neighboring countries. [ABSTRACT FROM AUTHOR]

The presented paper is devoted to an innovative way of teaching mathematics, specifically the subject combinatorics in high schools. This is because combinatorics is closely connected with the beginnings of informatics and several other scientific disciplines such as graph theory and complexity theory. It is important in solving many practical tasks that require the compilation of an object with certain properties, proves the existence or non-existence of some properties, or specifies the number of objects of certain properties. This paper examines the basic combinatorial structures and presents their use and learning using relations through the Placemat method in teaching process. The effectiveness of the presented innovative way of teaching combinatorics was also verified experimentally at a selected high school in the Slovak Republic. Our experiment has confirmed that teaching combinatorics through relationships among talented children in mathematics is more effective than teaching by a standard algorithmic approach. [ABSTRACT FROM AUTHOR]

This paper focuses on the statistical evaluation of two independent research tools in the field of traffic psychology. Our research focuses on young drivers in the Slovak Republic and conducts an international comparison. At present, these young drivers make up only about 7% of the total number of drivers, but they cause about 20% of accidents. The paper analyzes the traffic accident rate of young as well as inexperienced drivers. All drivers in the survey had a short period of driving experience. The traffic-psychological survey obtained detailed data via two independent tools. We aimed to find relations between the factors and subfactors of the tools used, namely the BIS-11 (Barratt Impulsiveness Scale) and DAQ (Driver Attitude Questionnaire). The researchers also used these tools in other countries, so it was possible to compare the results obtained. The results from these tools should reveal the psychological causes of as many traffic accidents as possible. Our paper shows the possibilities for the evaluation of the tools used with correlation analysis. The results of our research are shown in symmetrical matrixes of correlation coefficients. Our study also compares its values with the results of foreign authors. Such research has revealed some facts about young drivers' violations connected with drunk driving, speeding, and other traffic offenses. Our aim was to find connections between the driver's history (skills, traffic accidents, age, etc.) and psychological characteristics, and we have answered several research questions. In conclusion, we have highlighted the most significant relationships between the factors of driver psychology. [ABSTRACT FROM AUTHOR]

Math trail is a type of outdoor activity conducted in groups. Group members work together, communicate, and find common and best strategies for solving problems. Thus, it combines the use of mathematics in real life with a pleasant walk. Pupils have the opportunity to explore mathematics linked to real objects, solving standard and non-standard problems. Teachers, in turn, can use mathematics in this way as a tool to connect it to other STEM disciplines. This article first describes the results of research aimed at assessing spatial ability and mental rotation in students at technical vocational schools in Slovakia. A stereometry test was solved by 455 students. We then created a mathematical walk aimed at developing students' spatial ability. The experiences presented in the article may be helpful as other mathematics' popularization stimuli. We believe that when students are engaged in problem-based learning activities that are related to STEM disciplines, in particular, by connecting with the subjects in the problem context of the real world, STEM disciplines may become more important for students. Interdisciplinary STEM learning imitates authentic real-world problem-solving. [ABSTRACT FROM AUTHOR]

The capital structure and its indicators play a significant role in corporate finance. The aim is to estimate business performance using selected indicators describing primarily the capital structure, asset structure, or liquidity of transport companies in Central Europe. The total sample consists of almost 4000 small and medium-sized enterprises in the transport sector. This data is collected from Amadeus Bureau van Dijk. The results show that six out of ten variables are statistically significant predictors affecting business performance; two out of the six indicators are categorical variables, such as the company size classified into small and medium enterprises and the country divided into the Czech Republic, Hungary, Poland, or Slovakia. We find that Hungarian medium-sized enterprises show higher profitability than other enterprises, assuming other factors are unchanged. Finally, the results demonstrate that a high debt ratio and a high share of non-current assets in total assets have a negative impact on corporate performance in contrast to the current ratio and the share of cash and cash equivalents in total assets. In other words, liquidity and cash and its equivalents have a significant role in increasing business performance. These findings are specific because, generally, high liquidity does not positively impact performance. [ABSTRACT FROM AUTHOR]

The pension landscape is changing due to the market situation, and technological change has enabled financial innovations. Pension savers usually seek financial advice to make a personalised decision in selecting the right pension fund for them. As such, decision rules based on the assumed risk profile of the decision maker could be generated by making use of stochastic dominance (SD). In the paper, the second-pillar pension funds operating in Lithuania and Slovakia are analysed according to SD rules. The importance of the distributional assumption is explored while comparing the results of empirical, student-t, Hyperbolic and Normal Inverse Gaussian distributions to generate SD-based rules that could be integrated into an advisory solution. Moreover, due to the differences in SD results under different distributional assumptions, a new SD ratio is proposed that condenses the dominance-based relations for all considered dominance orders and probability distributions. The empirical results indicate that this new SD ratio efficiently characterises not only the preference of each fund individually but also of a group of funds with the same attributes, thus enabling multi-risk and multi-country comparisons. [ABSTRACT FROM AUTHOR]

Working capital management is one of the decisive factors in increasing business performance through the efficient use of current assets such as inventories, receivables, funds, and current liabilities. The primary aim is to identify how working capital management using a wide range of liquidity and activity indicators affects the corporate performance of transport companies broken down by company size into small, medium, large, and very large companies in Slovakia and the Czech Republic using multiple linear regression analysis with achieving competitive R-square as a relevant statistical metric compared to other models from previous research. Our research focuses on a different industry than the traditional production industry. Descriptive statistics show that more than half of the assets are impelled assets in the corporate finances of transport companies. We deal with the impact of working capital management on corporate performance, considering the corporate size. This output delivers specific findings for small, medium, large, and very large businesses separately. All multiple linear regression models for estimating corporate performance are proposed for transport companies in the Czech and Slovak Republics. The results show that liquidity has a negative impact, in contrast to activity indicators except for DPO, on corporate performance in Czech transport companies. On the other hand, Slovak small, medium, and large enterprises must effectively manage free cash and cash equivalents, too. However, activity indicators, except DRO for an aggregated group of large and very large enterprises, also harm business performance. These outputs are beneficial for business management and making relevant decisions to increase business performance, the models identify the strengths and weaknesses of working capital management. In general, this research helps to make specific decisions focused on receivables, inventory management, and cash management as part of working capital management. [ABSTRACT FROM AUTHOR]

The non-profit sector plays an important role in the American and European continents, as non-profit organizations support the development of civil society and help people in need. However, most non-profit organizations (NPO) are financially dependent on various donors from the private sector. Nowadays, non-profit organizations focus on improving their non-profit financial management. This research aims to assess the financial status of Slovak non-profit organizations, using binary logistic regression. The initial sample includes 351 Slovak NPOs, which are divided into a training and test sub-sample. The data were obtained from Amadeus, FinStat, the Ministry of Finance of the Slovak Republic, and the Ministry of Interior of the Slovak Republic. The logit model shows that the significant variables are equity ratio, debt ratio, operating margin, and type of NPO using the statistical–analytical program IBM SPSS 25. The model also implies that non-profit organizations should focus on the revenue structure and revenues from the sale of products. The prediction model correctly classifies 97.03% of NPOs in the training sub-sample and 96.61% of NPOs in the test sub-sample. Moreover, more than 70% of vulnerable NPOs are correctly classified. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the impact of a selected active labour market policy measure that has been applied in Slovakia—Allowance for school graduate practice performance—on the employability of young jobseekers and their sustainability in the labour market, and thus, it will also empirically contribute to the field of relevant literature. The policy targets unemployed school graduates, and it enables them to acquire professional skills and practical experience that corresponds with their level of education, work habits, and possible direct contact with potential employers. At the same time, this measure addresses a long-standing gap in the Slovakian education system, namely, the insufficient linkages between the educational process, the practices in the field, and the requirements of the labour market. Using fiscal resources to finance this policy, it provides a natural and logical platform to investigate the relevance of the outcome of this measure in the context of its proclaimed objectives. In light of this, we employed a counterfactual approach to compare the results of the participants who were affected the measure (recipients; treated group) and non-participants, as their counterparts (comparison/control group), using an instrumental variable to mitigate self-selection and selection-bias problems. Our findings show that this policy intervention has a short- or medium-term impact on the employability of unemployed school graduates and the sustainability of their careers. In addition, a positive impact on their monthly wages was observed. We also came to the conclusion that, assuming the measure is linked to other labour market policy interventions, which is aimed at employers that are willing to hire young unemployed people, it would be possible to improve the functionality and effectiveness of support for the unemployed through indirect measures. [ABSTRACT FROM AUTHOR]

The COVID-19 global pandemic has affected normal human behaviour in day-to-day activities. As a result of various restrictions, people have significantly changed their shopping and mobility to limit the spread of the pandemic. This article aims to determine the association between consumers' shopping preferences and the frequency of selected daily activities during and before the COVID-19 pandemic using correspondence analysis. The total sample consists of 407 respondents from Slovakia. The data are obtained from an online questionnaire divided into several sections such as socio-demographic factors, shopping preferences, and frequency of selected activities per week. The results show that there is an association between consumers' preference for shopping in supermarkets and the frequency of family visits per week during the pandemic, among other factors. These findings follow up on previous studies on the consequences of changing mobility as a result of the global crisis. [ABSTRACT FROM AUTHOR]

The efficient operation of emergency medical services is critical for any society. Typically, optimisation and simulation models support decisions on emergency ambulance stations' locations and ambulance management strategies. Essential inputs for such models are the spatiotemporal characteristics of ambulance trips. Access to data on the movements of ambulances is limited, and therefore modelling efforts often rely on assumptions (e.g., the Euclidean distance is used as a surrogate of the ambulance travel time; the closest available ambulance is dispatched to a call; or the travel time estimates, offered by application programming interfaces for ordinary vehicles, are applied to ambulances). These simplifying assumptions are often based on incomplete data or common sense without being fully supported by the evidence. Thus, data-driven research to model ambulance trips is required. We investigated a unique dataset of global positioning system-based measurements collected from seventeen emergency ambulances over three years. We enriched the data by exploring external sources and designed a rule-based procedure to extract ambulance trips for emergency cases. Trips were split into training and test sets. The training set was used to develop a series of statistical models that capture the spatiotemporal characteristics of emergency ambulance trips. The models were used to generate synthetic ambulance trips, and those were compared with the test set to decide which models are the most suitable and to evaluate degrees to which they fit the statistical properties of real-world trips. As confirmed by the low values of the Kullback–Leibler divergence ( 0.004 – 0.229 ) and by the Kolmogorov–Smirnov test at the significance level of 0.05 , we found a very good fit between the probability distributions of spatiotemporal properties of synthetic and real trips. A reasonable modelling choice is a model where the exponential dependency on the population density is used to locate emergency cases, emergency cases are allocated to hospitals following empirical probabilities, and ambulances are routed using the fastest paths. The models we developed can be used in optimisations and simulations to improve their validity. [ABSTRACT FROM AUTHOR]

Prediction of electricity energy consumption plays a crucial role in the electric power industry. Accurate forecasting is essential for electricity supply policies. A characteristic feature of electrical energy is the need to ensure a constant balance between consumption and electricity production, whereas electricity cannot be stored in significant quantities, nor is it easy to transport. Electricity consumption generally has a stochastic behavior that makes it hard to predict. The main goal of this study is to propose the forecasting models to predict the maximum hourly electricity consumption per day that is more accurate than the official load prediction of the Slovak Distribution Company. Different models are proposed and compared. The first model group is based on the transverse set of Grey models and Nonlinear Grey Bernoulli models and the second approach is based on a multi-layer feed-forward back-propagation network. Moreover, a new potential hybrid model combining these different approaches is used to forecast the maximum hourly electricity consumption per day. Various performance metrics are adopted to evaluate the performance and effectiveness of models. All the proposed models achieved more accurate predictions than the official load prediction, while the hybrid model offered the best results according to performance metrics and supported the legitimacy of this research. [ABSTRACT FROM AUTHOR]

Various studies show that the level of knowledge achieved by pupils is influenced by the level of knowledge of their teachers. In this article, we focus on geometric thinking and the solutions for geometric tasks through a study of future teachers of primary education. The research sample consisted of 59 master's students from the Teacher Training for Primary Education (TTPE) program. To determine the level of geometric thinking of TTPE students, the van Hiele geometric test was used. Two geometric multi-item tasks were proposed and the students' solutions to these tasks were quantitatively and qualitatively evaluated. The main goal was to analyze students' misconceptions while solving tasks and to compare and reveal the connections between their solutions and their achieved level of geometric thinking. A statistical implicative analysis was used for a deeper analysis, namely the statistical software C.H.I.C. The research findings show that more than 40% of TTPE students in the research sample did not reach the required level of geometric thinking. The achieved level of the geometric thinking of students is also influenced by the type of high school education. We observed problems with understanding the concept of the triangle and square in TTPE students. The connections between the solutions of two geometric tasks and the achieved level of geometric thinking were also revealed. [ABSTRACT FROM AUTHOR]