The significance of financial literacy is garnering worldwide attention across all age groups. Financial literacy has been defined by certain scholars as a necessary skill for individuals to possess in order to effectively navigate their future financial endeavors. The aim of this article is to perform a bibliometric analysis and systematic literature review in order to investigate the present corpus of scholarship on the application of Financial Literacy. The present study entailed a comprehensive analysis of existing research papers to ascertain the principal contributors to this specific domain, noteworthy subthemes, and prospective directions for further investigation. There has been a noticeable rise in the quantity of literature pertaining to this topic during the period spanning from 2020 to 2023. Furthermore, the utilization of network analysis was employed to chart research clusters. The aforementioned discovery yielded a cumulative total of 84 scholarly publications. The findings of the analysis indicate that there exists a gap in the comprehensive research of the keywords “Financial Behavior”, “Financial Attitude”, and “Financial Inclusion”.

The role of agriculture in greenhouse gas emissions and carbon neutrality is a complex and important area of study. It involves both carbon sequestration, like photosynthesis, and carbon emission, such as land cultivation and livestock breeding. In Shandong Province, a major agricultural region in China, understanding these dynamics is not only crucial for local and national carbon neutrality goals, but also for global efforts. In this study, we utilized panel data spanning over two decades from 2000 to 2022 and closely examined agricultural carbon dynamics in 16 cities of the Shandong Province. The method from the Intergovernmental Panel on Climate Change (IPCC) was used for calculating agricultural carbon sinks, carbon emissions, and carbon surplus. The results showed that (1) carbon sink from crops in the Shandong Province experienced growth during the study period, closely associated with the rise in crop yields; (2) a significant portion of agricultural carbon emissions was attributable to gastrointestinal fermentation in cattle, and a reduction in the number of stocked cattle led to a fall in overall carbon emissions; (3) carbon surplus underwent a significant transition in 2008, turning from negative to positive, and the lowest value of carbon surplus was noticed in 2003, with agriculture sector reaching the carbon peak; (4) the spatial pattern of carbon surplus intensity distinctly changed before and after 2005, and from 2000 to 2005, demonstrating spatial aggregation. This research elucidates that agriculture in Shandong Province achieved carbon neutrality as early as 2008. This is a pivotal progression, as it indicates a balance between carbon emissions and absorption, highlighting the sector’s ability in maintaining a healthy carbon equilibrium.

The focus of this research is the task of assistance from the government in improving agriculture in the region and analyzing the obstacles that occur. However, there has been a decrease in the number of assistance tasks given by the central government to the local government of Rokan Hulu, Riau Province, Indonesia in 2022. This study aims to evaluate and find out the obstacles to the implementation of assistance tasks in Rokan Hulu Regency in 2022. This study uses a qualitative method with an exploratory type and is analyzed using Nvivo 12 Plus software. The results of this study show that the Rokan Hulu regional government only gets one implementation of assistance tasks, namely from the Ministry of Agriculture through the Director General of Infrastructure and the Director General of Food Crops whose performance achievements have been maximized. The findings in this study are that in its implementation there are obstacles, one of which is the relatively short period of implementation of assistance tasks, making it difficult to implement assistance tasks by regional apparatus organizations as recipients of assistance tasks. The conclusion in this study is that the implementation of assistance tasks there is one assistance task received from the Ministry of Finance whose implementation in the region is carried out by the Food Crops and Horticulture Service. This research contributes to the government of Rokan Hulu, Indonesia, namely as a basis for policymaking, especially in the use of the budget for assistance tasks.

Cities play a key role in achieving the climate-neutral supply of heating and cooling. This paper compares the policy frameworks as well as practical implementation of smart heating and cooling in six cities: Munich, Dresden and Bad Nauheim in Germany; and Jinan, Chengdu and Haiyan in China, to explore strategies to enhance policy support, financial mechanisms, and consumer engagement, ultimately aiming to facilitate the transition to climate-neutral heating and cooling systems. The study is divided into three parts: (i) an examination of smart heating and cooling policy frameworks in Germany and China over the past few years; (ii) an analysis of heating and cooling strategies in the six case study cities within the context of smart energy systems; and (iii) an exploration of the practical solutions adopted by these cities as part of their smart energy transition initiatives. The findings reveal differences between the two countries in the strategies and regulations adopted by municipal governments as well as variations within each country. The policy frameworks and priorities set by city governments can greatly influence the development and implementation of smart heating and cooling systems. The study found that all six cities are actively engaged in pioneering innovative heating and cooling projects which utilise diverse energy sources such as geothermal, biomass, solar, waste heat and nuclear energy. Even the smaller cities were seen to be making considerable progress in the adoption of smart solutions.

This study investigates the impact of artificial intelligence (AI) integration on preventing employee burnout through a human-centered, multimodal approach. Given the increasing prevalence of AI in workplace settings, this research seeks to understand how various dimensions of AI integration—such as the intensity of integration, employee training, personalization of AI tools, and the frequency of AI feedback—affect employee burnout. A quantitative approach was employed, involving a survey of 320 participants from high-stress sectors such as healthcare and IT. The findings reveal that the benefits of AI in reducing burnout are substantial yet highly dependent on the implementation strategy. Effective AI integration that includes comprehensive training, high personalization, and regular, constructive feedback correlates with lower levels of burnout. These results suggest that the mere introduction of AI technologies is insufficient for reducing burnout; instead, a holistic strategy that includes thorough employee training, tailored personalization, and continuous feedback is crucial for leveraging AI’s potential to alleviate workplace stress. This study provides valuable insights for organizational leaders and policymakers aiming to develop informed AI deployment strategies that prioritize employee well-being.

Accurate prediction of US Treasury bond yields is crucial for investment strategies and economic policymaking. This paper explores the application of advanced machine learning techniques, specifically Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) models, in forecasting these yields. By integrating key economic indicators and policy changes, our approach seeks to enhance the precision of yield predictions. Our study demonstrates the superiority of LSTM models over traditional RNNs in capturing the temporal dependencies and complexities inherent in financial data. The inclusion of macroeconomic and policy variables significantly improves the models’ predictive accuracy. This research underscores a pioneering movement for the legacy banking industry to adopt artificial intelligence (AI) in financial market prediction. In addition to considering the conventional economic indicator that drives the fluctuation of the bond market, this paper also optimizes the LSTM to handle situations when rate hike expectations have already been priced-in by market sentiment.