This research analyzes the relationship between political stability, renewable energy utilization, economic progress, and tourism in Indonesia from 1990 to 2020. We employ advanced econometric techniques, including the Fourier Bootstrap Autoregressive Distributed Lag (ARDL) approach and Fourier Toda-Yamamoto causality testing, to ensure the robustness of our results while accounting for smooth structural changes in the data. The analysis uncovers a long-term equilibrium relationship between tourism and its fundamental determinants. Our research reveals significant positive impacts of political stability and renewable energy consumption on tourism in Indonesia. A stable political environment creates a favorable climate for tourism development, instilling confidence in both domestic and international tourists. Promoting renewable energy usage aligns with sustainable tourism practices, attracting environmentally conscious travelers. Furthermore, our findings demonstrate a bi-directional causal relationship between these variables over time. Changes in political stability, renewable energy consumption, and economic growth profoundly influence the tourism sector, while the growth of tourism itself can also stimulate economic development and foster political stability. Our findings underscore the need for environmentally sustainable and politically stable tourism policies. Indonesia’s tourism sector can grow sustainably with renewable energy and stability. Policymakers can develop strategies with tourism, political stability, renewable energy, and economic prosperity in mind.

This study offers a new perspective on measuring the impact of village funds (DD) on rural development. Using a mixed-method approach, the qualitative analysis reveals that, like previous rural development programs, the DD program struggles to implement inclusive methods for capturing community aspirations and evaluating outcomes. Despite rural infrastructure improvement, many villagers feel they have not fully benefited and do not view it as offering economic opportunities. The econometric model confirms the qualitative findings, indicating no significant DD influence on the village development index (IPD). Instead, effective governance factors like Musdes, regulations, and leadership are essential for the IPD improvement. Thus, enhancing village governments’ institutional capacity is crucial for increasing the DD effectiveness. The paper recommends several measures: training village officials in financial management and project planning, providing guidelines for the DD allocation and usage, creating robust monitoring-evaluation systems, developing communication strategies, and fostering partnerships with local NGOs and universities.

This study aims to examine the role of automotive industry development in the regional growth of Hungarian counties. Through word frequency analysis, the counties were grouped, and their unique characteristics were highlighted. Some counties already play a prominent role in the domestic automotive industry hosting established Original Equipment Manufacturers (OEMs), a significant number of automotive suppliers and high R&D and innovation potential. Another group includes counties that currently lack a significant automotive industry and did not identify it as a key focus area for future development. Additionally, an intermediate group has also emerged, including counties where the automotive industry is either in its early stages of investment, or such development is prioritized in regional planning documents. The study details the direction of automotive development in counties where the industry plays a significant role, focusing on labor market characteristics and human resource development. The findings have significant implications for the future of the automotive industry in these counties, underlining the urgent and immediate need for well-managed and well-established human resource development and ensuring effective partnership to realize its full potential in the automotive industry.

Most countries have adopted a more liberal policy to socialize public relations under the influence of neoliberalism and lobbying by economic elites to strengthen the role of market mechanisms and citizens’ entrepreneurial activity. The nature, scale, sequence, and strategy of economic and social reforms in each country have their specifics. Today multi-vector and large-scale changes are taking place in social and labor policy, and they do not always have an internal logic. The study assesses prospects for the development of the labor market in the context of global transformations. Within the framework of this study, the collected information was processed gradually. Data processing was modified during the study phase. At the first stage, data processing results were used to determine total and non-farm self-employment for two groups of countries with developing economies and estimate the scale of vulnerable employment. At the second stage, indicators were identified that characterize various categories of economically active population that belong to the precariat. At the third stage, the authors analyzed data on non-standard forms of employment. The authors assumed that these forms have a right to exist and will be implemented more often. There is an imbalance between standard and non-standard forms of employment. Further research should consider the transformation of labor from material and intangible dominants to creativity.

This study explored the relationships between college students’ indecisiveness, anxiety, and career decision-making ability. Using the convenience sampling method, 1072 college students at a college in Hunan Province, China completed a questionnaire online that included the Indecisiveness Scale, Career Exploration and Decision Self-Efficacy Scale, and Generalized Anxiety Scale-7. Participants reported their gender and place of origin (rural or city). They indicated whether they were an only child, were left behind, and liked the major they were studying. The t-test was used to identify differences in indecisiveness, career decision-making ability, and anxiety according to demographic characteristics. Correlations were calculated between the main variables of interest. Regression analysis was conducted to test the mediation model. Participants who liked their major were significantly more indecisive than those who did not like their major. Career decision-making ability was significantly higher among men than women, participants from urban areas than those from rural areas, participants who were an only child than those with siblings, and among non-left-behind participants than those who were left behind. Anxiety was significantly lower in participants who liked their major than those who did not like their major. In addition, anxiety partially mediated the relationship between indecisiveness and career decision-making ability. College students’ indecisiveness and career decision-making ability are affected by sociocultural background, gender, family background, and career interest. Anxiety partially mediates the relationship between indecisiveness and career decision-making ability. Implications of the findings for counseling college students are discussed.

This paper investigates the transformative role of Artificial Intelligence (AI) in enhancing infrastructure governance and economic outcomes. Through a bibliometric analysis spanning more than two decades of research from 2000 to 2024, the study examines global trends in AI applications within infrastructure projects. The analysis reveals significant research themes across diverse sectors, including urban development, healthcare, and environmental management, highlighting the broad relevance of AI technologies. In urban development, the integration of AI and Internet of Things (IoT) technologies is advancing smart city initiatives by improving infrastructure systems through enhanced data-driven decision-making. In healthcare, AI is revolutionizing patient care, improving diagnostic accuracy, and optimizing treatment strategies. Environmental management is benefiting from AI’s potential to monitor and conserve natural resources, contributing to sustainability and crisis management efforts. The study also explores the synergy between AI and blockchain technology, emphasizing its role in ensuring data security, transparency, and efficiency in various applications. The findings underscore the importance of a multidisciplinary approach in AI research and implementation, advocating for ethical considerations and strong governance frameworks to harness AI’s full potential responsibly.