The COVID-19 pandemic caused a drastic reduction in air traffic passengers, especially during the period when the EU countries introduced a lockdown. Even after the relaunch of airline operators, passenger traffic did not return to the pre-pandemic trend. The aim of the study was to estimate the difference between the demand that was observed during the pandemic, and the demand that was forecast based on the pre-pandemic trend. The calculations were made for airports in selected EU countries. The first method was seasonality indicators, using quarterly data for 2015–2021. In the multiplicative model of seasonal fluctuations, the method of determining the seasonality indicators was used, based on the quotient of empirical values and the value of the trend. The one-name period trend method was used in the next step, then Fourier spectral analysis was applied. In the context of forecasts for the individual quarters of 2020 and 2021, all models indicate a further growing trend in the demand for passenger transport, which could have been observed if the COVID-19 pandemic had not occurred. As a result of the pandemic, the number of passengers handled at airports has significantly decreased. In the third quarter of 2021, freight growth was already noticeable, with the exception of Netherland, where a marked decline was recorded.

Remuneration policy is an element of company management. Remuneration systems should be flexible and evolutionary. They must consider not only the changes in the external environment but, most of all, the changing needs of the internal environment. In practice, this means aligning the company’s strategy and goals with the remuneration system. What is more, the remuneration policy must be consistent with all personnel substrategies, which should systematically create integrated human capital management. The aim of our research was to determine how employees perceive the appropriate structure of remuneration and how the relationships between the elements that make up the structure of remuneration are perceived. Energy sector employees were selected for the study, dividing the group of respondents by gender, age and level of education. The obtained data were submitted to multivariate correspondence analysis. The analysis of the perception map for the variables of gender, age and education, as well as the subjective assessment of the components of remuneration, allows the general assertion that both men and women believe that the amount of the fixed part of remuneration should be influenced by such elements as: work efficiency, education, seniority in the current place of employment, position in the hierarchy of the position held, as well as the level of salaries in the labor market. But people aged 60 and over with a vocational education tend to believe that the amount of the fixed part of remuneration should be influenced by collective agreements. Moreover, people aged 25–34 with higher education believe that the granting of additional benefits should not be affected by collective labor agreements.

Finding a fair system of rewarding employees in energy companies and its influence on their motivation to perform their duties is a problem faced by many economic entities. Therefore, the aim of the article is to initially direct further research, taking into account the basic characteristics of employees such as age, gender and level of education, in order to verify whether and to what extent it is necessary to dedicate the communication of the remuneration system to the needs of selected groups. Multiple correspondence analysis was used to analyse the data obtained from the questionnaires, examining the subjective evaluation of professional remuneration with regard to age, gender and level of education of the respondents in energy companies. The results obtained indicate that all enumerated features have an impact on the perception of work remuneration systems. It is also possible to adjust the applied remuneration solutions and the methods and content of messages to particular groups of employees of energy companies.

The stability of clustering methods is the issue that has attracted a considerable amount of attention of researchers in recent years. In this respect, the major question that needs to be answered seems to be to what extent the structure discovered by a particular method is actually present in the data. The literature proposes a number of different ways of measuring stability. The theoretical considerations have led to the development of computer tools for the practical implementation of the proposed ways to study stability. The practical tools are available within several R packages, for example, clv, clValid, fpc, ClusterStability, and pvclust. Due to the hypothesis that cluster stability can be the answer to the question about the right number of groups in clustering, the main aim of this article is to compare the results of the studies on clustering stability conducted with three R packages, i.e.: clv, clValid, and fpc.

Research background: Recently in the context of taxonomy methods a lot of attention has been paid to the issue of stability of these methods, i.e. the answer to the question: do the groups that were created as a result of clustering really occur (the structure is stable), or did they appear accidentally. Purpose: The article is inspired by the Reviewers of the author’s previous publications on this subject and will be a summary of research to date which has followed two paths. On one hand, they recognize ways of measuring cluster stability proposed in the literature (e.g. Rozmus, 2017). On the other, they use these measures to cluster Poland among the EU members in terms of sustainable development level (e.g. Rozmus, 2019). Research methodology: The literature proposes a number of different ways for measuring stability. Theoretical considerations have also led to the development of computer tools for the practical implementation of the proposed ways to study stability. The practical tools are available within several R packages, e.g.: clv, clValid, fpc, which are used in this research Results: The results, however, showed that different measures of stability lead to different results. Novelty: The innovation of this approach is the use of stability measures to such a problem (i.e. clustering EU members in terms of the sustainable development level). In addition, the article will report a synthesis and comparative analysis of the results obtained using various stability measures.

High accuracy of results is a very important aspect in any clustering problem t determines the effectiveness of decisions based on them. Therefore, literature proposes methods and solutions that aim to give more accurate and stable results than traditional clustering algorithms (e.g. k-means or hierarchical methods). Cluster ensembles (Leisch 1999; Dudoit, Fridlyand 2003; Hornik 2006; Fred, Jain 2002) or the distance clustering method (Ben-Israel, Iyigun 2008) are the examples of such solutions. Here, we carry out an experimental study to compare the accuracy of these two approaches.