Within the last four years, Lithuania has faced different foreign policy challenges due to geopolitical situations such as the Ukraine-Russia war, the migration crisis on the border with Belarus, and the conflict with China. After opening a Taiwanese representative office in Vilnius, China downgraded diplomatic relations with Lithuania. The purpose of the article is to assess the impact of the changes on international economic relations between Lithuania and China. The paper employs descriptive statistics, correlation-regression, sensitivity analysis, and agglomerative hierarchical cluster analysis. The research is based on the impact of international economic relations on international trade by analyzing separately imports and exports. Our research fills a gap in international relations and globalization theory by focusing on international collaboration between small and large countries, while the large country implements economic sanctions. In the context of Lithuania, exports to China and imports from China comprise a small percentage in the structure of international trade. Lithuania’s GDP level reacts sensitively to changes in export and import data only if they change drastically (over 50%).

During crisis events, the government implements many policies to control the development of the crisis and stimulate the economy damaged by the crisis. The government plays a very important role during the crisis. The stock market is a reflection of a country’s economic situation. This article takes the Chinese government policies during the COVID-19 crisis as the research object and analyzes the impact of government policies on the CSI300 index. The following conclusion is drawn: not all government restrictions will cause a decline in stock market prices, among which the Wuhan lockdown policy has promoted the rise of the CSI300 index. The two stimulus policies implemented by the Chinese government are both conducive to the rise of CSI300 index. During the COVID-19 crisis, investors holding high assets, high leverage, and low profitability companies will be significantly negatively affected after the government implements restrictive policies. After the government implements stimulus policies, investors holding high asset and high leverage companies will suffer losses. Investors who hold low asset, low leverage, and high profitability companies will have profits. And this article also finds that the size of company assets is an important driving factor for abnormal returns.

In the current context of multicultural collision, online information is impacting traditional gender values. To analyze the changes in gender role attitudes and gender awareness among Chinese Generation Z college students under the influence of various social factors, the study focuses on Generation Z college students and explores the impact of cultural, media, educational, and family factors on gender role attitudes and gender awareness among Chinese Generation Z college students through questionnaire surveys and quantitative analysis methods. The research results show that Generation Z college students exhibit extremely favorable gender perspectives, with the proportion of bisexual gender roles approaching 38%, surpassing the number of students with traditional understanding of single sex gender roles. At the same time, in school gender awareness education, research has found that the proportion of bisexual gender roles is the highest among students who accept open mindedness, at 46.6%. In family gender awareness education, students who receive parental gender awareness sharing education have the highest proportion of bisexual gender roles, accounting for 48.5%. Therefore, the current gender education for the new Generation of students in China needs to abandon traditional avoidance-based teaching methods and adopt an open and supportive attitude to guide students’ gender values.

In the fast-paced modern society, enhancing employees’ professional qualities through training has become crucial for enterprise development. However, training satisfaction remains under-studied, particularly in specialized sectors such as the coal industry. Purpose: This study aims to investigate the impact of personal characteristics, organizational characteristics, and training design on training satisfaction, utilizing Baldwin and Ford’s transfer of training model as the theoretical framework. The study identifies how these factors influence training satisfaction and provides actionable insights for improving training effectiveness in China’s coal industry. Design/Methodology/Approach: A cross-sectional design that allowed the study to capture data at one point in time from a large sample of employees was employed to conduct an online survey involving 251 employees from the Huaibei Mining Group in Anhui Province, China. The survey was administered over three months, capturing a diverse sample with nearly equal gender distribution (51% male, 49% female) and a majority aged between 21 and 40. The participants represented various educational backgrounds, with 52.19% holding an undergraduate degree and most occupying entry-level positions (74.9%), providing a broad workforce representation. Findings: The research indicated that personal traits were the chief predictor of training satisfaction, showing a beta coefficient of 0.585 (95% CI: [0.423, 0.747]). Linear regression modeling indicates that training satisfaction is strongly related to organizational attributes (β = 0.276 with a confidence interval of 95% [0.109, 0.443]). In contrast, training design did not appear to be a strong predictor (β = 0.094, 95% CI: [−0.012, 0.200]). Employee training satisfaction was the principal outcome measure, measured with a 5-point Likert scale. The independent variables covered personal characteristics, organizational characteristics, and training design, all measured through validated items taken from former research. The consistency of the questionnaire from the inside was strong, as Cronbach’s alpha values stood between 0.891 and 0.936. We completed statistical testing using SPSS 27.0, complemented by multiple linear regression, to study the interactions between the variables. Practical implications: This research contributes to the literature by emphasizing the necessity for context-specific training approaches within the coal industry. It highlights the importance of considering personal and organizational characteristics when designing training programs to enhance employee satisfaction. The study suggests further exploration of the multifaceted factors influencing training satisfaction, reinforcing the relevance of Baldwin and Ford’s theoretical model in understanding training effectiveness. Ultimately, the findings provide valuable insights for organizations seeking to improve training outcomes and foster a more engaged workforce. Conclusion: The study concluded that personal and organizational characteristics significantly impact employee training satisfaction in the coal industry, with personal characteristics being the strongest predictor. The beta coefficient for personal characteristics was 0.585, indicating a strong positive relationship. Organizational characteristics also had a positive effect, with a beta coefficient of 0.276. However, training design did not show a significant impact on training satisfaction. These findings highlight the need for coal companies to focus on personal and organizational factors when designing training programs to enhance satisfaction and improve training outcomes.

With the advent of the big data era, the amount of various types of data is growing exponentially. Technologies such as big data, cloud computing, and artificial intelligence have achieved unprecedented development speed, and countries, regions, and multiple fields have included big data technology in their key development strategies. Big data technology has been widely applied in various aspects of society and has achieved significant results. Using data to speak, analyze, manage, make decisions, and innovate has become the development direction of various fields in society. Taxation is the main form of China’s fiscal revenue, playing an important role in improving the national economic structure and regulating income distribution, and is the fundamental guarantee for promoting social development. Re examining the tax administration of tax authorities in the context of big data can achieve efficient and reasonable application of big data technology in tax administration, and better serve tax administration. Big data technology has the characteristics of scale, diversity, and speed. The effect of tax big data on tax collection and management is becoming increasingly prominent, gradually forming a new tax collection and management system driven by tax big data. The key research content of this article is how to organically combine big data technology with tax management, how to fully leverage the advantages of big data, and how to solve the problems of insufficient application of big data technology, lack of data security guarantee, and shortage of big data application talents in tax authorities when applying big data to tax management.

This study aims to quantitatively analyze the equity of social service space in urban parks in China, in order to explore the equity issues faced by different social groups in accessing urban park services. The research background focuses on the importance of urban parks as social service spaces, particularly in improving residents’ quality of life and well-being. Through a comprehensive literature review, the study examines the social service functions of urban parks, the relationship between parks and social psychology, and the theoretical framework of equity. The study employs quantitative research methods, collects data on urban park usage and resident satisfaction, and defines relevant analysis variables. The data analysis section reveals the basic characteristics of park service space usage and resident well-being index through descriptive statistical methods. Subsequently, quantitative analysis is conducted to evaluate the current status of equity in urban park service space and explore the key factors influencing equity. The study reveals a significant correlation between social psychological factors, resident well-being index, and equity in park service space. Finally, the research conclusion emphasizes the importance of improving equity in social service space in urban parks and provides specific policy recommendations. At the same time, the study acknowledges its limitations and suggests future research directions. This study provides insights for urban planners and policymakers on how to enhance equity in urban park services and offers important strategic guidance for improving overall well-being of urban residents.