Border areas can play a crucial role in market integration and infrastructure development between Central Asian countries, thus creating favorable economic growth and regional cooperation conditions. This study aims to assess the economic impact of border areas between Kazakhstan and Uzbekistan, focusing on their role in enhancing market integration and infrastructure development to foster regional growth and cooperation.  Focusing on labor and capital as essential production drivers, this study employs a sophisticated panel data regression model to explore the Cobb-Douglas production function’s application in these border territories. The research findings indicate that regions’ elasticity towards capital and labor inputs vary, necessitating differentiated economic strategies. For capital-intensive areas, we recommend prioritizing investments in infrastructure and technology to boost production outputs. Conversely, in regions where labor significantly influences production, the emphasis should be on human capital development through education, training, and improved labor market conditions. The study’s insights into the evolving trade relations between the two countries underscore the need for flexible economic policies to enhance regional integration and cooperation. This research not only fills a crucial knowledge gap but also offers a blueprint for leveraging the diverse economic landscapes of Central Asia’s border areas in future policy-making and regional economic strategy.

This study uses a Time-Varying Parameter Stochastic Volatility Vector Autoregression (TVP-SV-VAR) model to conduct an empirical analysis of the dynamic effects of China’s stock market volatility on the agricultural loan market and its channels. The results show that the relationship between stock market and agricultural loan market volatility is time varying and is always positive. The investor sentiment is a major conduit through which the effect takes place. This time-varying effect and transmission mechanism are most apparent between 2011 and 2017 and have since waned and stabilized. These have significant implications for the stable and orderly development of the agricultural loan market, highlighting the importance of the sound financial market system and timely policy, better market monitoring and early warning system and the formation of a mature and sound agricultural credit mechanism.

The objective of this article is to examine the provision of temporary exhibitions and events by Slovak museums and galleries, and to highlight their significance in the context of selected performances of these cultural attractions in the tourism sector. The article employs a secondary data analysis of the Ministry of Culture of the Slovak Republic and annual reports from 105 museums and 10 galleries in 2017, as well as 99 museums and 15 galleries in 2022. Correlation and regression analyses were employed to assess the dependence of variables. The results of the analysis confirm a direct, moderate dependence between the number of temporary exhibitions and events and the total number of visitors in museums and galleries. Additionally, the examination demonstrated that the exhibited activity has not had a positive effect on the revenues of museums and galleries. However, with an increasing number of events, their revenues from their own activities grew. The average revenues from one event were found to be higher in museums than in galleries.

This study aims to advance understanding of the factors affecting Generation Z employee commitment in the workplace of the information and technology (IT) companies in Vietnam. A survey of 450 Generation Z employees in IT companies shows that company remuneration, reward and welfare, work environment, colleagues, direct manager, promotion, job characteristics, green initiatives are positively related to Generation Z organizational commitment. More specifically, work environment and direct manager have the highest effect on Generation Z employee commitment to organization while promotion and colleagues have the lowest effect on Generation Z employee commitment to organization. Research results also revealed that green initiatives of the organization have significant effect on Generation Z employee commitment in companies. This finding suggests that including green initiatives in corporate strategy is a valuable approach for improving Generation Z employee commitment to organization. We discuss the implications for theory, practice, limitations, and directions for future research.

Surveys are one of the most important tasks to be executed to get valued information. One of the main problems is how the data about many different persons can be processed to give good information about their environment. Modelling environments through Artificial Neural Networks (ANNs) is highly common because ANN’s are excellent to model predictable environments using a set of data. ANN’s are good in dealing with sets of data with some noise, but they are fundamentally surjective mathematical functions, and they aren’t able to give different results for the same input. So, if an ANN is trained using data where samples with the same input configuration has different outputs, which can be the case of survey data, it can be a major problem for the success of modelling the environment. The environment used to demonstrate the study is a strategic environment that is used to predict the impact of the applied strategies to an organization financial result, but the conclusions are not limited to this type of environment. Therefore, is necessary to adjust, eliminate invalid and inconsistent data. This permits one to maximize the probability of success and precision in modeling the desired environment. This study demonstrates, describes and evaluates each step of a process to prepare data for use, to improve the performance and precision of the ANNs used to obtain the model. This is, to improve the model quality. As a result of the studied process, it is possible to see a significant improvement both in the possibility of building a model as in its accuracy.

Buru Regency is the primary hub for producing eucalyptus oil, a highly valued commodity in the region. The oil extracted from the eucalyptus epidemic plant possesses antiseptic, antibacterial, and antifungal characteristics. Amidst the Covid-19 pandemic, numerous industries require it as a fundamental component of pharmaceuticals. An essential factor in the eucalyptus oil production process is the presence of eucalyptus leaves. Therefore, leaf-sorting workers, including women, are required to ensure this availability. However, in reality, the daily lives of eucalyptus leaf massagers are characterized by challenging economic conditions and a socio-economic environment that lags behind workers in other sectors. This study aims to examine and investigate the roles and work patterns of employed women and the strategies they employ to ensure the consistent flow of household income. The research employed a qualitative methodology with a phenomenological approach. A total of 24 informants were purposefully selected based on their involvement in achieving the research objectives. The results indicate that the COVID-19 pandemic has altered the circumstances of women who collect leaves and rely heavily on eucalyptus trees as a natural resource. Physical adaptation strategies are the preferred methods used to fulfill household requirements. Implementing physical adaptations does not deter women leaf-sorters from continuing their work. Their commitment to meeting their basic needs significantly motivates them to persist in their role as leaf sorters. The income of women engaged in sorting eucalyptus leaves in their households during the COVID-19 pandemic.