This study investigates the impact of the metaverse on English language teaching, focusing on the perspectives of students from the University of Boyacá. The use of the metaverse was compared with the Moodle platform in a virtual educational environment. A mixed-method approach combining quantitative and qualitative methods was employed. The sample consisted of 30 university students enrolled in English courses, randomly assigned to two groups: one using the metaverse and the other using Moodle. Students’ grades on different activities and assessments throughout the course were collected, and semi-structured interviews were conducted to explore students’ perceptions of the educational platforms. Results revealed that while students recognize the potential of the metaverse to enhance interactivity and learning experience, they also identified technical and accessibility challenges. Although no significant differences in grades were found between the groups, less variability in grades was observed in the metaverse group. The mixed design allowed for a more comprehensive understanding of the impact of the metaverse on English language teaching, while providing a variety of student perspectives on their experience with educational technology. This research contributes to understanding the role of the metaverse in English language teaching and highlights key areas for future research and developments in the field of virtual education.

Border areas can play a crucial role in market integration and infrastructure development between Central Asian countries, thus creating favorable economic growth and regional cooperation conditions. This study aims to assess the economic impact of border areas between Kazakhstan and Uzbekistan, focusing on their role in enhancing market integration and infrastructure development to foster regional growth and cooperation.  Focusing on labor and capital as essential production drivers, this study employs a sophisticated panel data regression model to explore the Cobb-Douglas production function’s application in these border territories. The research findings indicate that regions’ elasticity towards capital and labor inputs vary, necessitating differentiated economic strategies. For capital-intensive areas, we recommend prioritizing investments in infrastructure and technology to boost production outputs. Conversely, in regions where labor significantly influences production, the emphasis should be on human capital development through education, training, and improved labor market conditions. The study’s insights into the evolving trade relations between the two countries underscore the need for flexible economic policies to enhance regional integration and cooperation. This research not only fills a crucial knowledge gap but also offers a blueprint for leveraging the diverse economic landscapes of Central Asia’s border areas in future policy-making and regional economic strategy.

Purpose: This study aims to identify the primary determinants of consumer behavior influencing customer satisfaction in the context of online mobile application (App) purchases of perishable products. Utilizing the well-established SERVQUAL (Service Quality) model, which has been extensively studied in various service-oriented settings, the research seeks to determine the factors with the greatest impact on customer satisfaction during online transactions of perishable products. Design: The investigation focuses on analyzing the five core dimensions of the SERVQUAL model: tangibles, reliability, responsiveness, assurance, and empathy. The study employs a survey methodology administered through Google Forms, targeting the population residing in the Klang Valley of Malaysia. A total of 400 samples were successfully collected using a snowball sampling technique. Methodology: The study employs the SERVQUAL model as the theoretical framework to examine the dimensions of tangibles, reliability, responsiveness, assurance, and empathy. The survey, conducted through Google Forms, targeted the population in the Klang Valley of Malaysia, with a sample size of 400 collected through snowball sampling. Findings: The study’s outcomes reveal the robust predictive capability of the overarching SERVQUAL model in the realm of online perishable product procurement. Notably, the assurance dimension emerges as the most influential factor, emphasizing its pivotal role in shaping and defining customer satisfaction for online retailers of perishable goods in the Malaysian market. Novelty: This research contributes to the understanding of consumer behavior in online perishable product purchases, by identifying determinants of consumer behavior; the study promotes sustainable production and responsible consumption within the perishable products category, offering insights beneficial for online retailers in the Malaysian market. This study aligns with United Nations sustainable development goals especially industry innovation, food security and responsible consumption.

The use of public transport is one of the concepts of sustainable transport. However, people prefer to use private vehicles, which causes various problems, one of which is the high carbon emissions produced. This research aims to encourage programs to use passenger public transportation through a carbon tax. The method in this research is descriptive quantitative with primary data and secondary data. Secondary data was developed in the research by collecting literature study sources on the concept of sustainable transportation development as well as primary data carried out by analyzing calculations regarding the implementation of the carbon tax. There are several proposals that can significantly accelerate the achievement of goals, namely a collaborative approach through collaboration between local government agencies, a policy of progressively implementing a carbon tax as a coercive policy and supported by a program to provide supporting facilities for public transportation. Decision making in this research was carried out by looking at the percentage increase in public transportation use based on the application of a carbon tax or carbon tax.

This study examines aggressive behavior among adolescents in school settings, focusing on its associations with mental health dimensions such as dysfunctional negative emotions and anxiety. A total of 403 adolescents (234 girls and 169 boys) aged 12 and 13 years participated in the study. Self-report questionnaires assessed aggressive tendencies and mental health symptoms, while demographic variables such as age and gender were also collected. Data analysis revealed a non-normal distribution, as determined by the Kolmogorov-Smirnov and Shapiro-Wilk tests. Consequently, non-parametric statistical methods were employed, including the Spearman correlation coefficient to explore relationships between variables and the Mann-Whitney U test to analyze gender differences. The results demonstrated significant positive correlations between aggressive behavior and dysfunctional negative emotions (r = 0.191, p < 0.01) and between aggression and anxiety (r = 0.275, p < 0.01). Additionally, gender differences emerged, with females reporting higher levels of mental health symptoms than males (p < 0.05). These findings highlight the complex relationship between mental health challenges and aggression, emphasizing the significant roles of gender and emotional regulation in shaping these dynamics. The study calls for the development of tailored psychological interventions that not only address aggressive behaviors but also consider the unique mental health needs and emotional profiles of adolescents, ensuring a more personalized and effective approach to support their well-being.

Choosing a university is a crucial decision for each field of study, as it significantly influences the quality of graduates. An important factor in this decision is the university’s annual benchmark scores. The benchmark score represents the minimum score required for admission. This study evaluates the benchmark scores in the logistics sector for several prominent universities in Vietnam during the period 2021–2023. The research process utilized data on the benchmark scores for the years 2021, 2022, and 2023. The weights of these benchmark scores were calculated using the Rank Order Centroid (ROC) method, and the Probability method was employed to compare the benchmark scores of the universities. The analysis identified C3 as the criterion with the highest importance, while U3 emerged as the top-ranked alternative. The two-stage comprehensive sensitivity analysis revealed that universities consistently ranked high or low regardless of the method used to calculate benchmark score weights or the method employed for ranking. Additionally, the smallest weight change that affected the overall Probability ranking was 4.61%. This study provides significant guidance for students in selecting a university for logistics studies and serves as a foundational reference for universities to assess their capabilities in logistics education, thereby fostering healthy competition among institutions.