In this paper advanced Sentiment Analysis techniques were applied to evaluate public opinions reported by rail users with respect to four major European railway companies, i.e., Trenitalia and Italo in Italy, SNCF in France and Renfe in Spain. Two powerful language models were used, RoBERTa and BERT, to analyze big amount of text data collected from a social platform dedicated to customers reviews, i.e., TrustPilot. Data concerning the four European railway companies were first collected and classified into subcategories related to different aspects of the railway sector, such as train punctuality, quality of on-board services, safety, etc. Then, the RoBERTa and BERT models were developed to understand context and nuances of natural language. This study provides a useful support for railways companies to promote strategies for improving their service.

The presented article focusses on the analysis of perception of the university social responsibility through the eyes of Slovak university students. The aim is to compare how the values, efficiency of the organisation (university), and the educational process influence the perception of social responsibility among university students themselves. The research is based on the application of quantitative methodology towards the evaluation of differences and similarities in perceptions using two types of tests for statistical analysis, comparative (Mann-Whitney U test) and correlational (bivariate correlation matrix of Spearman’s rho).The results of the research provide a deeper understanding of how universities can shape students’ approach to social responsibility through their values and educational processes, which has important implications for the development of university policies and practices.

This study analyzes the social and individual stigmatization toward Venezuelan immigrants in Peru within the context of the largest migratory movement in Latin America, driven by the political, economic, and humanitarian crisis in Venezuela. The study employs a qualitative approach, using semi-structured in-depth interviews with a diverse sample of 24 participants from major Peruvian cities, including Lima, Arequipa, Cusco, and Trujillo. These in-depth interviews provide insights into the complexity of perceptions toward Venezuelan migrants, ranging from stigmatizing views driven by associations with economic threats and criminality to more positive perceptions that acknowledge the migrants’ adaptability and economic contributions. The findings reveal that while negative stereotypes perpetuate social exclusion and pressures for cultural assimilation threaten the preservation of migrant identities, there are also narratives highlighting resilience and successful integration. The study emphasizes the importance of implementing intercultural education programs, promoting labor integration policies, and collaborating with the media to combat stigma. It concludes that addressing these challenges through a multidimensional, human-rights-based approach can foster greater social cohesion and better integration of migrants, benefiting both the migrant population and Peruvian society.

This study looked at how adding augmented reality (AR) to Jordanian fast-food apps during the pandemic impacts brand identity, consumer views, and interactions. It wanted to see if AR strengthens brand connections or leads to brand dilution concerns in the industry. The research utilized a qualitative approach, employing semi-structured interviews with 52 marketing managers from diverse fast-food establishments across Jordan. The study highlighted how mobile apps, especially AR, changed brand interactions in Jordan’s fast-food market. They boosted convenience and engagement but raised worries about food quality and brand dilution due to heavy app use. It stressed the need to balance tech innovation, preserve brand identity, offer personalized experiences, understand user behavior, and tackle app development challenges for better brand loyalty. The research offers practical implications for stakeholders, recommending strategic AR integration, a user-centric approach, cultural sensitivity in tech adoption, and the preservation of emotional connections. It emphasizes the significance of maintaining a delicate balance between leveraging technological advancements and safeguarding the distinctiveness of individual brand identities within an increasingly app-centric landscape. This study uncovers AR’s influence in Jordan’s fast-food scene, highlighting its transformative power and possible drawbacks. It offers practical advice for industry players, guiding them on how to navigate the digital shift without compromising brand integrity or customer connections.

Extensive research on pro-environmental behaviour (PEB) reveals a significant knowledge gap in understanding the influence of social class, perceived status and the middling tendency on pro-environmental behaviour. Using the International Social Survey Programme Environment dataset, and conducting multilevel mixed-effects linear regressions, we find that the middling tendency and biased status perceptions significantly influences pro-environmental behaviour. Those who deflate their social position have higher pro-environmental behavior and this reinforces the idea that pro-environmental behaviour is driven by a post-materialist effect rather than a status enhancement effect. Moreover, the objective middle class is still a stronger contributor to higher PEB levels compared to subjective middle class. We also find the relation between class, status and PEB vary by country. These findings provide vital insights into the intricate and heterogenous dynamics between class, status and pro-environmental behaviour among different countries and shed light on class and status as driving forces behind pro-environmental behaviour.