The study is designed to dig the association between ESG and economic efficiency. Total samples used are 520 listed enterprises in Chinese stock market for one year (2020). Multiple regression is adopted to analyze this research. The independent variable is ESG scores, and the dependent variable is return on assets (ROA). Control variables include size, leverage, and cashflow. The effect of overall and individual ESG on ROA is examined. Comparing the impact of ESG in different industries and analyzing the reasons for it. This paper finds no important association between ESG and ROA. For individual factors in the industry level, social has no significant impact. However, governance and environmental performance have a significant impact in some specific industries, such as information transmission software and the retail industry, respectively. This study indicates that ESG did not become a key factor determining corporate performance in China in 2020. Furthermore, it provides suggestions for the sustainable growth of companies and the investment of investors.

The review examines corporate financial performance and risk evaluations' quantitative trend from 2015 to 2024, pointing out the linkage among profitability, leverage, market risk, and financial resilience. The article compiles different studies about real industries with corresponding statistics and data to determine primary indicators for companies such as ROA, ROE, Net profit margin, and EPS growth rate and those related to the risk side, like Altman Z-score, beta, VaR, and credit default rate. The findings show that tech firms enjoy the best financial conditions with low risk while energy and financial services firms have high leverage, high systematic risk. The temporal patterns suggest that those mega events, such as the outbreak of the COVID-19 pandemic and the application of ESG policies can impact on corporations. It also means that firms should combine traditional financial ratios with some forward-looking quantitative models, such as predictive analytics and machine learning to improve long-term corporate resilience and support strategic decision-making.

This research investigates the influence of an investor's emotional state on risk aversion in financial decision-making and its subsequent impact on aggregate stock returns. Grounded in Behavioral Finance Theory, this study challenges the rational investor paradigm of Traditional Finance by examining the psychological underpinnings of market behavior. The research employs a qualitative, interpretivist methodology, utilizing semi-structured interviews with a stratified sample of 30 professionals from Australia's finance and human psychology sectors. Data will be analyzed through thematic analysis to identify key patterns and themes. The study seeks to identify specific emotional states that impact risk aversion, evaluate the scope of emotional influence on investment decisions, explore mechanisms for balancing rationality and emotion, and deduce evidence-based strategies for Australian investors to optimize decision-making. The findings are expected to provide significant insights into the role of psychology in financial markets and offer practical guidance for achieving more consistent and optimal investment returns.

As a crucial component of new-quality productive forces, the low-altitude economy is increasingly becoming one of the new drivers of economic development in the new era. The development of ESG practices is an unavoidable topic for emerging industries like the low-altitude economy. This paper aims to explore the internal connection between ESG practices and low-altitude economy enterprises, analyze how ESG practices drive the development of these enterprises, and identify the challenges they pose. Ultimately, this paper argues that value creation for low-altitude economy enterprises can be achieved through three ESG dimensions as paths: leading green standards in the environmental dimension, consolidating safety and trust in the social dimension, and building a collaborative ecosystem in the governance dimension. Guided by these three paths, low-altitude economy enterprises can explore a comprehensive development path that covers all aspects.

As one of the factors of production in the new era, data resources have exerted a significant impact on society. In 2022, the Chinese government issued the "Twenty Measures on Data" policy, which clearly demonstrates the country's determination to develop data resources. As an integral part of data resources, the development of public data is an indispensable link in releasing data productivity, and plays an irreplaceable role in promoting social development and improving public efficiency. This study selects relevant literatures from the China National Knowledge Infrastructure (CNKI) database and uses the CiteSpace bibliometric tool to explore the current development status, key concerns, and future research priorities of public data in China. The research finds that public data has become a hot topic in the era of big data. Keyword clustering analysis shows that concepts centered on public data, such as data governance and digital economy, have become hot issues, while also triggering scholars' reflections on the authorized operation of public data and social responsibility.

Fear appeal advertising remains a complex and debated topic in marketing research, with past studies often reporting inconsistent findings regarding its persuasive impact. This study aims to clarify these contradictions by introducing self-esteem as a pivotal moderating variable, examining its role within the framework of the Extended Parallel Process Model (EPPM). An online survey was conducted, generating 155 valid responses for analysis. The results demonstrate that self-esteem significantly influences the effectiveness of fear appeal advertisements. Specifically, individuals with low self-esteem were found to be the most susceptible to persuasion. Furthermore, a key finding is that self-esteem moderates the relationship between perceived threat and ad effectiveness. For the low self-esteem group, a higher perceived threat increased the ad's effectiveness, whereas the opposite effect was observed for the high self-esteem group. These findings contribute to the literature by identifying a crucial psychological mechanism, thereby offering a more nuanced understanding of fear appeal effectiveness for both academic research and targeted marketing strategies.

As China's real estate sector contends with a significant downturn, Affordable Rental Housing (ARH) REITs are gaining prominence as a pivotal financial innovation. These instruments are designed to channel private capital into addressing the critical shortage of affordable housing, offering a new funding model to the traditional market. Pilot programs such as the China Merchants Fund Shekou Rental Housing REIT serves as clear example to demonstrate the sector's expansion potential through successful new listings and follow-on offerings. Based on the analysis of secondary market indices, the project has truly shown notable financial resilience, which maintains a stable occupancy despite broader operational headwinds. However, for ARH REITs to evolve from a short-term crisis mitigation tool into a sustainable long-term solution for the housing market, they must successfully navigate the persistent challenges of widespread market oversupply and tepid consumer demand. Their ability to scale is greatly hinged on overcoming these systemic market weaknesses.

This paper review concerns how FinTech changes lending markets. This paper review tracks its growth from consumer credit to business loans and mortgages. They are supported by new technologies, such as AI, big data analytics and blockchain. They enable alternative credit scoring using rental histories for financial inclusion. They also enable real-time risk adjustments and fully automated loan processes. First, FinTech lenders often replace traditional banks in certain areas because they operate under different rules but can also partner with traditional banks. There are some important challenges related to algorithmic governance. For example, concept drift problem means that models become outdated during economic changes. Another problem is bias, which means that models will make unfair lending decisions. Data poverty problem excludes people with few digital footprints. Nonbank lending can cause credit escalations due to easy access to a range of credit products.​​

This review investigates how big data is reshaping financial analytics, emphasizing improvements in operational efficiency, transparency, and risk management. It systematically examines key enabling technologies, including distributed computing frameworks, cloud platforms, and AI/ML tools, and analyzes their applications in algorithmic trading, predictive modeling, automated financial reporting, and regulatory compliance. The paper demonstrates how big data facilitates explainable AI for transparent decision-making, enhances predictive risk assessment through stress testing and early warning systems, and supports the development of robust, data-driven financial infrastructures. Additionally, emerging trends such as blockchain integration, real-time analytics, and ethical considerations are explored, offering actionable insights for both researchers and practitioners seeking to advance resilient and intelligent financial frameworks.

Rural microcredit plays a vital role in rural development, making tremendous contributions to increasing farmers' income, improving the rural living environment, responding to emergencies, and promoting the agricultural industry. This paper conducts an overall analysis of the current status, characteristics and main problems of rural microcredit, and puts forward corresponding suggestions. The study finds that although rural microcredit has provided great help to rural economic development, the risk management system still has defects and loopholes. To better meet its needs and play its role, measures such as improving and strengthening the risk management system and innovating or expanding its industry fields should be taken to better serve and gain the trust of farmers.