Generational differences shape technological preferences and fundamentally influence workplace motivation and interactions. Our research aims to examine in detail how different generations assess the importance of workplace communication and leadership styles and how these diverse preferences impact workplace motivation and commitment. In our analysis, we studied the behavioral patterns of four generations—Baby Boomers, Generations X, Y, and Z—through anonymous online questionnaires supplemented by in-depth interviews conducted with a leader and a Generation Z employee. To verify our hypotheses, we employed statistical methods, including the Chi-Square test, Spearman’s rank correlation, and cross-tabulation analysis. Our results clearly demonstrated that different generations evaluate the importance of applied leadership and communication styles differently. While Generations Y and Z highly value flexible, supportive leadership styles, older generations, such as the Baby Boomers prefer more traditional, structured approaches. The study confirmed that aligning leadership and communication styles is crucial, as it significantly impacts the workplace atmosphere and employee performance. Our research findings hold both theoretical and practical significance. This research highlights how understanding generational preferences in leadership and communication styles can enhance workplace cohesion and efficiency. The results provide specific guidance for leaders and HR professionals to create a supportive and adaptable environment that effectively meets the needs of diverse generations.

This study aims to identify the causes of delays in public construction projects in Thailand, a developing country. Increasing construction durations lead to higher costs, making it essential to pinpoint the causes of these delays. The research analyzed 30 public construction projects that encountered delays. Delay causes were categorized into four groups: contractor-related, client-related, supervisor-related, and external factors. A questionnaire was used to survey these causes, and the Relative Importance Index (RII) method was employed to prioritize them. The findings revealed that the primary cause of delays was contractor-related financial issues, such as cash flow problems, with an RII of 0.777 and a weighted value of 84.44%. The second most significant cause was labor issues, such as a shortage of workers during the harvest season or festivals, with an RII of 0.773. Additionally, various algorithms were used to compare the Relative Importance Index (RII) and four machine learning methods: Decision Tree (DT), Deep Learning, Neural Network, and Naïve Bayes. The Deep Learning model proved to be the most effective baseline model, achieving a 90.79% accuracy rate in identifying contractor-related financial issues as a cause of construction delays. This was followed by the Neural Network model, which had an accuracy rate of 90.26%. The Decision Tree model had an accuracy rate of 85.26%. The RII values ranged from 68.68% for the Naïve Bayes model to 77.70% for the highest RII model. The research results indicate that contractor financial liquidity and costs significantly impact construction operations, which public agencies must consider. Additionally, the availability of contractor labor is crucial for the continuity of projects. The accuracy and reliability of the data obtained using advanced data mining techniques demonstrate the effectiveness of these results. This can be efficiently utilized by stakeholders involved in construction projects in Thailand to enhance construction project management.

Accessible tourism is an area that has received only scant attention in Hungarian tourism research. A change in this is only visible in recent years, as a result of the work of a few researchers starting to focus on this issue. Based on the findings of a questionnaire survey, the author of this paper presents important characteristics of travel by people living with disabilities, discussing the need to develop its infrastructure. The issue of accessible tourism concerns approximately 10% of the population of Europe, so in addition to the social and moral magnitude of the issue, serving the travel needs of people living with disabilities is also significant for the economy. In order to create the special supply and to provide equal access of services for those concerned, their expectations and unique consumer habits must be known. As member of an Erasmus project called Peer Act, the author also details the research findings of four project partner countries (Germany, Italy, Spain and Croatia) where data was collected from small samples.

The primary school stage is the key stage for students to form good habits and lay a good learning foundation, especially in primary schools, Chinese classes account for the largest proportion of all courses, the focus of learning began to shift to understanding and mastering. Through scientific methods, teachers can effectively improve the concentration of Chinese learning of primary school students in order to improve their interest and overall level,to have a profound impact on the future study and life of primary school students. This paper analyzes the importance and strategies of teachers' attention training in the middle Chinese classroom of primary school.

This study examines the bottleneck effect of logistics performance on Vietnam’s imports, utilizing bilateral trade data from 2007 to 2022. We evaluate the impact of logistics performance on imports of Vietnam using the augmented gravity model and a random effects estimator. Our findings reveal that the minimum logistics performance between Vietnam and its trading partners has a significantly positive impact on the Vietnamese imports. The magnitude of its bottleneck effects is much larger than the influence of Vietnam’s individual logistics performance or deviations in performance with its trading partners. Recognizing the impact of logistics bottlenecks on international trade enables policymakers to develop more effective and efficient logistics-related policies for enhancing bilateral trade with trading partners.

Globalization and economic integration have an impact on increasing trade volume and economic growth in various countries, especially those that are open in their economies. This situation also provides ease of capital mobility between countries, which makes investment not only rely on domestic investment but also on foreign direct investment. Exchange rates and inflation also affect export growth, imports, and economic growth. The purpose of this study is to determine the effect of exchange rate, inflation, foreign direct investment, government expenditure, and economic openness on export and import growth.  This study used time series data during the period 1980–2021, sourced from UNCTAD, ASYB, and Indonesian Central Bank (BI). The analysis model used is multiple linear regression with the help of EViews software, which first tests classical assumptions so that the regression results are Best Linier Unbiased Estimator (BLUE). The results show that foreign direct investment and government spending can significantly increase the rate of exports and imports. Meanwhile, the depreciating rupiah against the US dollar cannot encourage an increase in both exports and imports. Furthermore, foreign direct investment, government spending, and economic openness can significantly increase economic growth. The other variables, net exports and inflation, have no effect on Indonesia’s economic growth rate.