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Abstract

Research background: Crime is a complex social phenomenon studied by scientists from various disciplines, as well as being of interest to politicians and the general public. Although the decrease in the level of crime has been observed in Poland in recent years, there is still a need to search for effective methods of investigating the phenomenon of crime in a multidimensional perspective.

Purpose: The aim of the paper is to assess the spatial and temporal diversity of the chosen criminal offences categories in Poland from 2000 to 2017.

Research methodology: The analyzed dataset constitutes a data cube: objects x variables x time. This type of data requires the use of methods dealing with three-way data structures, therefore the Partial Triadic Analysis, belonging to the STATIS family methods, was successfully applied.

Results: The structure of crime by voivodeship was fairly stable during the analyzed years. Three clusters of voivodeships similar in terms of the criminal crime rate were determined. The Podkarpackie Voivodeship was characterized by the most stable structure of criminal crime in the considered period. In contrast, noticeable changes in the crime structure over time were observed in the Opolskie, Dolnośląskie, Mazowieckie and Małopolskie Voivodeships. The highest variability was observed for crimes under The Act on Counteracting Drug Addiction.

Novelty: To the best knowledge of the author, there are no papers on the level of crime using the PTA method for analysis.

Redundancy analysis (RDA) is a canonical form of principal components analysis (PCA) and is one of, so‑called, linear ordination techniques. The goal of ordination is to represent objects and response variables relationships as faithfully as possible in a low‑dimensional space. Redundancy analysis is also a technique of exploratory data analysis. Graphical presentation of the results using the ordination biplots or triplots can facilitate the analysis of the relationship between the variation in the set of the response variables and the variation of the explanatory variables. In the paper, redundancy analysis was applied to assess the relationships between the selected socio‑economic factors and the intensity of the crime against property in Poland.

Ordination techniques such as CCA (Canonical Correspondence Analysis) or RDA (Redundancy Analysis) are very popular in ecological research but almost completely unknown in, for example, socio-economic research. The goal of this paper is to concisely organize the concepts and terminology associated with ordination and to present the possibilities of its application in social research with an example of the analysis of the 2015 parliamentary elections results.

The problem of incomplete data and its implications for drawing valid conclusions from statistical analyses is not related to any particular scientific domain, it arises in economics, sociology, education, behavioural sciences or medicine. Almost all standard statistical methods presume that every object has information on every variable to be included in the analysis and the typical approach to missing data is simply to delete them. However, this leads to ineffective and biased analysis results and is not recommended in the literature. The state of the art technique for handling missing data is multiple imputation. In the paper, some selected multiple imputation methods were taken into account. Special attention was paid to using principal components analysis (PCA) as an imputation method. The goal of the study was to assess the quality of PCA‑based imputations as compared to two other multiple imputation techniques: multivariate imputation by chained equations (MICE) and missForest. The comparison was made by artificially simulating different proportions (10–50%) and mechanisms of missing data using 10 complete data sets from the UCI repository of machine learning databases. Then, missing values were imputed with the use of MICE, missForest and the PCA‑based method (MIPCA). The normalised root mean square error (NRMSE) was calculated as a measure of imputation accuracy. On the basis of the conducted analyses, missForest can be recommended as a multiple imputation method providing the lowest rates of imputation errors for all types of missingness. PCA‑based imputation does not perform well in terms of accuracy.

As Eurostat's glossary explains, the term Information and Communication Technologies (ICT): 'covers all technical means used to handle information and aid communication. This includes both computer and network hardware, as well as their software.' In both local and global perspective, the ICT impact on modern economies and societies is undeniable. Moreover, it is growing, as the usability and technical capabilities are expanding. The researchers recognised that the ICT expansion in enterprises is a stimulant for economic development, as it strengthens competitiveness and innovation. Its impact on labour markets is significant, and constantly increasing demand for digital competences and ICT specialists can be observed. In both global and local perspective, the ICT sector is growing dynamically along with its value share in GDP. Monitoring the development of ICT usage as well as analysing how it stimulates socio‑economic transformations and growth are crucial for global leaders, governments and local authorities all over the world in order to formulate policy at all levels. Also, it plays a significant role in modern businesses expansion, as it strengthens innovativeness and competitiveness.
The main objective of the paper is to study the ICT usage development in Poland against other EU countries from the enterprises' perspective in the years 2010–2019 (before the COVID–19 pandemic and Brexit). The research presented was based on Eurostat data. The variables were selected on the basis of the literature review on ICT usage, as well as the criterion of data availability and comprehensiveness. The exploratory data analysis methods dealing with three‑way data structures, i.e. the between and within‑class principal component analysis, were used, and the presentation of the results was supported by factorial maps (scatterplots and biplots).
In the analysed period, enterprises in all the European Union Member States intensified their ICT usage. Despite the positive trend from 2010 to 2019, Poland remained far behind the leading countries, and more precisely, was in the group of the least developed ones.