The research aims to assess the cultural diversity of international students studying in higher education institutions. The results of the research provide an overview of the attitude of students studying in institutions of higher education to learning, the factors influencing their studies, and their expectations for their studies abroad. One type of quantitative research method, the questionnaire, was chosen for the primary research. The research results reflect the perspectives of students from different cultural backgrounds in institutions of higher education and focus on the phenomena and situations they experience. Following the hypothesis test results, an outcome can be seen that students believe that their studies in higher education provide a good foundation for their personal development. The results also confirmed that learning in a multicultural environment could positively affect students’ working abilities.

This article was inspired by current events. The shopping craze generated by the coronavirus pandemic raised some questions that this article aims to answer by analysing a variety of suppositions. The coronavirus pandemic caused panic shopping amongst consumers, whose motivation for increasing the volumes of shopping revolved around ensuring a safety margin of groceries while also reducing the number of shopping trips. The consumers did most of their shopping in hyper, and supermarkets, as well as in bigger ABCs and grocery stores (Lidl), where there’s a wider range of products and larger stock. The average consumer bought much more than the basic groceries during this period. Our research started in March 2020 and ended in May 2020. To validate our assumptions, primary information is derived from the statistical processing of a large number of data from a representative questionnaire survey of 724 respondents. The results show that for many people this period was about stockpiling storages of groceries. Flour saw the biggest increase in purchase volumes, but chicken and pastas were also amongst the more popular items. Stores with the biggest range of selection were able to satisfy this demand. As evidenced by data, consumers also purchased items, which are needed for any household during an emergency and are easy to store in higher volumes. These items include different oils and fats, which are required for cooking, and non-perishables, such as salamis, canned foods, rice and mineral water.

Background/Objectives: Eating behaviour patterns are fundamental determinants of chronic disease risk and public health. Hungary faces among the highest rates of obesity, cardiovascular disease, and diet-related mortality in Europe. Despite this, population-level consumer profiling based on validated multi-scale instruments remains limited. This study used nationally representative samples to assess eating motivations, health and taste attitudes, and eating styles among Hungarian adults, and grouped adults into consumer segments for each measure. Methods: Two independent nationally representative cross-sectional surveys were conducted: (1) eating attitudes (TFEQ-R21) and health/taste attitude scales (HTAS) were assessed in 2021 (n = 1000); (2) eating motivations (TEMS) were assessed in late 2019 (n = 1000). Exploratory factor analysis (EFA) was applied to each instrument, and confirmatory factor analysis (CFA) to the TFEQ-R21 and to both HTAS subscales. Consumer segmentation was performed using hierarchical and K-means cluster analysis. Sociodemographic differences across segments were explored via chi-square tests and one-way analysis of variance (ANOVA). The perceived palatability and healthiness of functional food categories were examined across TFEQ-R21 segments. Results: The TEMS yielded eight eating motivation factors and five consumer segments: Traditional Simplifiers (17.9%), Frugal Social and Emotional Eaters (19.9%), Balanced Self-Rewarders (27.5%), Health-Conscious (18.3%), and Indifferent (16.4%). The HTAS health subscale produced four clusters, with Health-Conscious Metropolitans (19.8%) as the primary functional food target. The HTAS taste subscale identified taste-oriented consumers (26.9%) alongside three further groups. The TFEQ-R21 confirmed a three-factor eating attitude structure (emotional eating, uncontrolled eating, cognitive restriction; explained variance 57.2%) and yielded five behavioural clusters. Controlled Dieters represented 20.6% of the sample; the other TFEQ-R21 segments showed average, uncontrolled, or emotionally driven eating profiles. Perceived palatability and healthiness of functional foods differed across TFEQ-R21 segments (one-way ANOVA, unadjusted p < 0.05 in six of ten categories for palatability and eight of ten for healthiness), and Controlled Dieters gave the highest mean rating in eight of ten categories on each measure. Conclusions: The parallel application of three validated eating behaviour scales describes eating attitudes, motivations and consumer segments among Hungarian adults. Habitual, taste-oriented and average-profile segments were common, and each instrument also yielded a smaller health-oriented segment (about 18–21%). These cross-sectional findings on attitudes and self-reported motivations may inform segment-specific communication, which should be tested in future intervention studies.

In the context of digital transformation and accelerated technological development, employees' competitiveness is increasingly determined not only by professional knowledge but also by the ability to master new technologies, adapt to change, and continuously develop their competencies. This study aimed to explore how technological competencies, openness to learning, adaptability, and willingness to retrain are interrelated and how these factors influence employees’ organizational commitment. The methodological basis of the study was exploratory factor analysis, evaluation of scale reliability using Cronbach's alpha, Pearson correlation analysis, and linear regression analysis. The empirical basis of the study was an online survey of 281 employees of small and medium-sized enterprises in Hungary conducted in January 2026. The results empirically supported the hypothesis that technological competence, learning orientation, adaptability, and willingness to retrain are integrated into a single adaptive technological human capital (hereinafter ATHC) index (Cronbach’s alpha = 0.837). ATHC showed a strong, positive relationship with affective organizational commitment (r = 0.758; p < 0.001) and explained 57.4% of its variance. However, a weak but significant positive relationship was found for continuance organizational commitment (r = 0.220; p < 0.001), which did not support the theoretically hypothesized negative relationship. The results indicate that developing adaptive technological human capital can not only enhance employees’ employability and adaptability but also contribute to organizational competitiveness by increasing organizational commitment. Thus, in the digital economy, adaptive technological human capital is an important resource for enhancing employee resilience, strengthening organizational commitment, and ensuring long-term organizational competitiveness.