This paper critically reviews the prevailing generalizations in current research on Generation Z (Gen-Z) travel behavior. While various studies have characterized Gen-Z’s transportation preferences as leaning towards sustainable and technology-integrated modes of transport, this paper argues that the findings are largely based on observations from developed countries and may not accurately reflect behavior in developing countries. This paper is written using a narrative literature study approach. Through a comprehensive literature review, the paper highlights the differences in Gen-Z travel patterns across different geographical regions, emphasizing the need for context-specific analysis. The paper addresses often overlooked factors such as economic limitations, infrastructure challenges, and cultural nuances that shape mobility choices. The aim is to dissect the cohort effect and look at its validity across different socio-economic landscapes through existing literature. As such, the paper provides nuanced insights into the heterogeneity of Gen-Z travel behavior and suggests cautioning against over-generalization, as well as advocating for a more localized approach in transportation policy and planning. The paper also encourages similar research in developing countries to gain a more comprehensive understanding of Gen-Z travel behavior globally.

Research indicates a strong correlation between sociodemographic factors and success in learning to read. This study examines the sociodemographic characteristics of 1131 preschool and 1st-grade children in Portuguese public schools and explores the relationship between these characteristics and key competencies for reading acquisition. The collection included a sociodemographic questionnaire and pre-reading skills, such as letter-sound knowledge. To assess the relationship between the sociodemographic variables and the letter-sound knowledge, inter-subjects (parametric and non-parametric) difference tests were conducted, as well as correlation analyses. To understand whether letter-sound knowledge is predicted by sociodemographic variables, a multiple linear regression analysis was performed using the Enter method. The results suggest that the mother’s education is the variable that most strongly contributes to success in reading acquisition. Socioeconomic status and the type of school also play a role in reading achievement. Identifying the sociodemographic factors that most strongly correlate with reading acquisition success is crucial for a more accurate identification of at-risk children and to provide targeted support/inclusion in reading skills promotion projects.

This study presents a comprehensive bibliometric analysis of the literature on public financial management (PFM), aiming to identify key trends, influential publications, and emerging themes. Using data from Web of Science and Scopus, the study examines the evolution of PFM research from 1977 to 2024. The findings reveal a significant increase in PFM research output, particularly after 2010, with countries like the United States, the United Kingdom, and China contributing the most publications. Central themes such as financial management, transparency, and accountability remain prominent while emerging topics like gender budgeting, health insurance, and blockchain technology reflect shifting priorities in the field. The study employed performance analysis and science mapping techniques to assess the structure and dynamics of PFM research. The analysis highlights key focus areas, including fiscal decentralization and sector-specific management, and identifies gaps in the existing literature, particularly regarding interdisciplinary and international collaboration. The results suggest that while PFM remains rooted in traditional governance and financial control, there is a growing emphasis on modern, innovative solutions to address contemporary challenges. This study’s insights provide a roadmap for future research, emphasizing the importance of transparency, technological integration, and inclusive financial policies. In conclusion, this bibliometric analysis contributes to understanding PFM’s evolving landscape, offering scholars and policymakers a clearer perspective on current trends and future directions in the field. Future research should focus on expanding interdisciplinary approaches and exploring the practical impacts of emerging PFM trends across different regions.

This study aims to identify the risk factors causing the delay in the completion schedule and to determine an optimization strategy for more accurate completion schedule prediction. A validated questionnaire has been used to calculate a risk rating using the analytical hierarchy process (AHP) method, and a Monte Carlo simulation on @RISK 8.2 software was employed to obtain a more accurate prediction of project completion schedules. The study revealed that the dominant risk factors causing project delays are coordination with stakeholders and changes in the scope of work/design review. In addition, the project completion date was determined with a confidence level of 95%. All data used in this study were obtained directly from the case study of the Double-Double Track Development Project (Package A). The key result of this study is the optimization of a risk-based schedule forecast with a 95% confidence level, applicable directly to the scheduling of the Double-Double Track Development Project (Package A). This paper demonstrates the application of Monte Carlo Simulation using @RISK 8.2 software as a project management tool for predicting risk-based-project completion schedules.

Pattaya City is a well-known tourist destination in Thailand, famous for its beautiful beachfront, lively nightlife, and stunning natural scenery. Since 2019, the Eastern Special Development Zone Act, the so-called EEC (Eastern Economic Corridor), has positioned the city as a focal point for Meetings, Incentives, Conferences, and Exhibitions (MICE), boosting its tourism-driven economy. Infrastructure improvements in the region have accelerated urban development over the past decade. However, it is uncertain whether this growth primarily comes from development within existing areas or the expansion of urban boundaries and what direction future growth may take. To investigate this, research using the Cellular Automata-Markov model has been conducted to analyze land use changes and urban growth patterns in Pattaya, using land use data from the Department of Land for 2013 and 2017. The findings suggest an upcoming city expansion along the motorway, indicating that infrastructure improvements could drive rapid urbanization in coastal areas. This urban expansion emphasizes the need for urban management and strategic land use planning in coastal cities.

This study evaluates the health and sustainability of higher education systems in nine countries: the USA, UK, Australia, Germany, Canada, China, Brazil, India, and South Africa. Using a multi-level analysis model and principal component analysis (PCA), nine key factors—such as international student numbers, academic levels, and graduate employment rates—were identified, capturing over 90% of the cumulative impact on higher education systems. India, scoring 6.2036 initially, shows significant room for improvement. The study proposes policies to increase graduate employment, promote international faculty collaboration, and enhance India’s educational expenditure, which surpasses 9.8% of GDP. Post-policy simulations suggest India’s score could rise to 8.7432. The paper also addresses the impact of COVID-19 on global education, recommending a hybrid model and increased graduate enrollment in China to reduce unemployment by 5.4%. The research aims to guide sustainable development in higher education globally.