Micro-mobility has the potential to address first -mile challenges, improving transit accessibility and encouraging public transit usage. However, users’ acceptability of modal integration between various micro-mobility options and public transit remains largely unexplored in the literature. Our study investigates the user behavior for first-mile options, focusing on four alternatives: walking, bicycling, motorcycling, and bus, to access urban mass rapid transit (UMRT) in Hanoi, Vietnam. Based on data collected from 1380 individuals, a Nested Logit Model (NLM) was proposed to analyze the determinants of users’ acceptability under each access mode option as well as evaluate further impacts of shifts in access mode choice on vehicle-kilometer traveled and emissions. The analysis shows that the availability of access modes might increase UMRT use by 47.83%. While this increase further generates additional vehicle-kilometer traveled due to the increase in park-and-ride users, this is offset overall by the large number of motorcycle users shifting to UMRT. Under the most optimistic scenario, modal integration for transit-access trips leads to an average reduction of 17.7% in net vehicle-kilometer traveled or 14.5% in net CO₂ emissions or 10.9% in NO_x from private vehicles. Our findings also imply that the introduction of parking fees for bicycling- or motorcycling-access trips, while impactful, does not significantly change UMRT choice. Therefore, the pricing schemes should be a focus of parking planning surrounding stations. Finally, a number of policy suggestions for parking planning and first-mile vehicles are presented.

The paper considers an important problem of the successful development of social qualities in an individual using machine learning methods. Social qualities play an important role in forming personal and professional lives, and their development is becoming relevant in modern society. The paper presents an overview of modern research in social psychology and machine learning; besides, it describes the data analysis method to identify factors influencing success in the development of social qualities. By analyzing large amounts of data collected from various sources, the authors of the paper use machine learning algorithms, such as Kohonen maps, decision tree and neural networks, to identify relationships between different variables, including education, environment, personal characteristics, and the development of social skills. Experiments were conducted to analyze the considered datasets, which included the introduction of methods to find dependencies between the input and output parameters. Machine learning introduction to find factors influencing the development of individual social qualities has varying dependence accuracy. The study results could be useful for both practical purposes and further scientific research in social psychology and machine learning. The paper represents an important contribution to understanding the factors that contribute to the successful development of individual social skills and could be useful in the development of programs and interventions in this area. The main objective of the research was to study the functionalities of the machine learning algorithms and various models to predict the students’s success in learning.

Lifelong learning (LLL) is progressively recognized as a crucial component of personal and professional development, particularly for adult students. As a heavily populated developing country, China requires profound national education reform to support its economic development and maintain its competitive advantage on the global economic stage. The governmental policy endorses the execution of diverse forms of lifelong learning programs to bolster the national education reform. However, implementing such programs can be challenging for all the stakeholders of the programs, especially for adult students. The weaker foundational knowledge and insufficient online learning abilities of adult students particularly highlight the academic challenges they face. This study explores the academic challenges faced by adult learners in a Chinese vocational college’s LLL program. Focusing on ex-soldiers, unemployed individuals, migrant workers, and new professional farmers (aged 22–44), data were collected from 16 adult students via purposive sampling. Semi-structured interviews and document analysis revealed recurring thematic academic challenges. Additionally, the study found that adult student attributes (highest education level, age) significantly influenced the unique academic challenges they encountered. This research provides practical solutions to improve LLL programs and promote successful lifelong learning experiences for adult students. 

Culture is a cohesive system of values, meanings, and behaviors. This study follows Hofstede’s framework of cultural dimensions, which is widely studied in different contexts. Although culture is a subject of extensive research, few recent studies evaluate culture between countries. This study analyzed the cultural dimensions identified in two Latin American countries: Colombia and Chile. In addition, it evaluated differences in both countries by sex. The study was conducted with 382 workers from Chile and 617 from Colombia. Significant differences were found between Colombia and Chile in power distance, paternalism, and masculinity-femininity. This exploratory study may contribute to discussing the role of culture and sex in organizations operating in different countries.

This study explores the influence of digital technologies, including media, on pre-service teachers’ interactions and engagement patterns. It underscores the significance of promoting digital competence to empower pre-service teachers to navigate the digital world responsibly, make informed decisions, and enhance their digital experiences. The objective is to identify key themes and categories in research studies related to pre-service teachers’ digital competence and skill preparations. Conducting a systematic literature review, we searched databases such as SCOPUS, ScienceDirect, and Taylor & Francis, including forty-three articles in the dataset. Applying qualitative content analysis, we identified four major themes: digital literacy, digital competencies, digital skills, and digital thinking. Within each theme, categories and their frequencies were examined. Preliminary findings reveal a growing prevalence of digital competence and literacy articles between 2019 and 2024. The paper concludes by offering recommendations for further research and implementations, with specific criteria used for article selection detailed in the paper. A digital literacy policy for teacher education preparedness is included.

Access to affordable and quality medicines plays a vital role for achieving Universal Health Coverage and in reducing out-of-pocket expenditures (OOPE) for households especially in developing nations such as India. Pradhan Mantri Bhartiya Janaushadhi Pariyojana (PMBJP), a Government of India initiative, aims to make low-cost and quality generic drugs and surgical equipment accessible to all segments of the population through its dedicated store outlets known as Pradhan Mantri Bhartiya Janaushadhi Kendra (PMBJK). In this study, a pilot survey comprising 20 stores/PMBJKs and 150 citizens was undertaken in the Bengaluru Urban District, India to understand various aspects of the PMBJKs including availability of drugs, stock-outs, accessibility to stores, perception and awareness levels along with challenges faced by store owners and citizens/beneficiaries. Based on the survey results, we capture the availability of drugs for 35 medicines and consumables belonging to 12 therapeutic categories across 20 store outlets. We also provide valuable insights and interdisciplinary recommendations on several facets including adopting technology-based measures for day-to-day functioning of stores, need for in-depth supply chain analysis for ensuring availability of drugs, encouraging prescription of generic medicines, increasing awareness levels in addition to promoting grassroot-level research, surveys and feedback mechanisms. These suggestions are expected to find their utility in policy-making, strengthen the implementation of the PMBJP scheme across Bengaluru and India as well as contribute towards achieving related Sustainable Development Goals.