The purpose of this paper is to assess the impact of the COVID-19 pandemic on rural e-customers’ preferences in terms of last mile delivery and products purchased via the Internet. This paper is based on the theory of last mile delivery (with a strong focus on the methods of delivery) and customers’ preferences. It combines both theories to fulfil the paper’s goal. In the paper, the literature review and multivariate data analysis of rural e-customers in Poland were used. The hypothesis states that there is a requirement for different last mile delivery solutions in rural areas than in urban areas in Poland. The research was carried out on a sample of 1071 adult Poles, who are residents of rural areas, using the standardized and structured computer-assisted interview (CAWI). The authors used the chi-square independence test, the Student t-test, one-way analysis of variance (ANOVA), regression models, and logistic models. The research shows that more than 60% of respondents living in rural areas order goods purchased online with a home delivery method and that online shopping preferences’ changes are not so significant after the occurrence of COVID-19. Both before and after the pandemic, rural e-customers made online purchases most often 2–3 times a month. Nevertheless, some differences in the preferences of rural e-customers in terms of last mile delivery and purchasing preference can be seen considering their age, gender, or family size. The survey found that smaller families were more likely to choose free home delivery with a free return after the pandemic. The research presented in this paper provides essential information for courier companies, stores, and online platforms alike. Knowledge of preferences and their changes after the occurrence of COVID-19 can support the reorganization of last mile delivery to meet the needs of e-customers and to adapt to the increasing demands for sustainable transportation.

Residents of rural areas buy products in the e-commerce market that are delivered to their homes (home deliveries) or to collection points (out-of-home deliveries). This poses last mile delivery challenges, which are of increasing interest to researchers. While urban research is widespread, a smaller number of rural studies are noticeable. The study aims to assess the factors differentiating the inhabitants of rural areas as to the familiarity and use of various methods of delivery of products purchased via the Internet and the reasons for choosing the preferred delivery methods. The paper uses the simplified SLR method in the literature section and multivariate data analysis in the empirical section. It contributes to the existing research in the form of the analysis of rural e-customers’ preferences for choosing a particular delivery method or parcel collection method when out-of-home delivery is conducted. It indirectly focuses on the environmental attitudes that may lead to the sustainable transition through reducing CO₂ emissions while last mile delivery is performed. Regardless of choosing price or convenience over sustainable behavior for Polish rural e-customers, their preferences in last mile deliveries are focused on more eco-friendly methods of delivery. Such behavior is a good beginning for a more sustainable transition towards energy saving in Polish rural areas.

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The study presents the results of grouping EU NUTS 2 regions based on the share of employment in particular sectors (knowledge‑intensive high‑technology services, knowledge‑intensive market services and other knowledge‑intensive services), as well as GDP per capita, in 2008 and 2018. The grouping of regions was done by clustering methods (for structure data), including Ward’s method to determine the number of groups and the k‑means for the final partition. GDP groups were defined using a sample mean and one standard deviation. To assess the similarity of the classifications and, consequently, to evaluate correlations between the employment structures and the level and pace of economic development, the similarity measure for partitions proposed by Sokołowski was used.

This paper aims to identify the differences in the employment rate dynamics in economy sections, considering gender, in the European Union countries in 2020, compared to the 2008–2019 period. Two methods were used. The first method compares forecasts from models describing employment changes in the pre-pandemic periods with information concerning the actual employment rate in 2020, using three indices measuring the significance of the observed discrepancies. The second method uses dynamic cluster analysis for the 2008–2020 period, and evaluates the changes in composition of groups that occured in 2020. The proposed methods were applied separately to the data concerning the employment of females and males (employment rates) in the EU countries, always divided into economy sections and section groups (A, B-E, F, G-I, J, K, L, M and N, O-Q, R). The application of the “Triple 2 Rule” helped to identify the changes in the previous employment trends (“Interventions”). The evaluation of changes in the dynamics of the employment rate in total and in section groups and according to gender in the EU countries in 2020 – compared to the forecasts from the 2013–2019 trends – revealed that the EU labour market responded differently to the COVID-19 pandemic situation.