bluuebunny/crossref_metadata_2025 huggingface dataset:
Neural Network-Enhanced Monte Carlo Simulation for Efficient European Option Pricing
Authors: Zhang Tianze
Published: December 2024

This study explores a hybrid method to enhance the efficiency of Monte Carlo simulations for European option pricing by incorporating neural network models. Traditional Monte Carlo Methods require high computational costs when dealing with high-dimensional financial derivatives due to the increased demand for simulation paths to achieve prediction accuracy. By integrating a feedforward neural network, this research aims to predict future price paths based on intermediate simulations, effectively reducing the number of paths while maintaining pricing accuracy. The proposed model employs residual block, regularization, early stopping, and other techniques to capture the nonlinear relationships between price paths and payoffs. Based on the trained model, the number of simulation paths required is successfully reduced from 10,000 to around 4,000 5,000 without significantly reducing prediction accuracy while achieving a balance in computation costs. The method exhibits stable predictive performance and computational efficiency, providing a potential solution for reducing the overhead of pricing complex financial derivatives. Future work could explore more advanced neural network architectures and hybrid with other techniques to further improve performance and efficiency.
Optimizing Red Wine Quality Prediction: The Impact of Feature Selection and Model Evaluation
Authors: Xu Baiqiu
Published: December 2024

The quality of red wine is crucial for both consumers and producers, influencing purchasing decisions and product improvements. This study aims to enhance red wine quality prediction models through effective feature selection and model optimization. By employing feature engineering to construct and assess feature contributions, the study identifies the best feature combinations and utilizes a five-dimensional evaluation framework of accuracy, precision, recall, F1 score, and Area Under the Receiver Operating Characteristic Curve (AUC-ROC) to screen various models. The research integrates new feature combinations with the optimal model and compares performance before and after feature selection through cross-validation, focusing on stability and generalization. The findings reveal that the Random Forest model, when combined with feature selection, outperforms models using original features in terms of generalization and stability. Key features such as alcohol content and free Sulphur dioxide significantly enhance prediction accuracy. However, new feature construction does not always improve model performance and may introduce noise. These results not only offer practical insights for production and quality control but also underscore the importance of careful feature selection in model prediction, contributing valuable academic knowledge to the field.
Predicting Rental Prices in India: A Machine Learning Approach with Hyperparameter Optimization
Authors: Zhang Junhao
Published: December 2024

This paper presents a comprehensive analysis and predictive modeling approach for rental prices in India. Utilizing a dataset of house rents from Kaggle, this study employs a range of machine learning algorithms to analyze and forecast rental prices. The methodology begins with establishing baselines using simple regression techniques. It then advances to more sophisticated models, including Gradient Boosting (GB) and Extreme GB (XGBoost), to enhance prediction accuracy. Hyperparameter tuning is conducted using the OPTUNA framework to identify the most effective algorithm. In cases of potential overfitting, the study shifts to ensemble methods, such as voting and bagging models, to improve robustness and generalizability. The paper aims to cover exploratory data analysis, data preprocessing, model training, and performance evaluation. By systematically comparing different algorithms and optimizing their parameters, this research provides a detailed framework for predicting rental prices with greater accuracy. The findings offer valuable insights for making informed decisions in real estate investments and rental management in India.
Applications and Challenges of Social Media Platforms in the Sports Events Management
Authors: Xu Lichen
Published: December 2024

The development of social media has precipitated a profound transformation in the dissemination of sports events. And the shift from traditional media to digitalization and multi-platform interaction has markedly enhanced audience participation and dissemination speed. Therefore, this paper explores the application of social media in sports events and its impact on event promotion, audience experience, and brand communication. In addition, it examines the characteristics and potential applications of various social media platforms, including Facebook, Instagram, and TikTok, to illustrate how social media can facilitate audience engagement, influence audience viewing habits, and offer innovative marketing strategies for events. At the same time, data analysis and user behavior research in sports events are explored to support decision optimization, and challenges faced by social media in sports event management, such as privacy issues and the spread of false information, are highlighted. The results indicate that social media not only broadens the audience reach for sports events but also enhances audience engagement and increases the commercial value of the events.
The Impact of Rural Household Wealth on Social Expenditure Burdens: An Empirical Analysis Based on CFPS 2014
Authors: Li Yutong
Published: December 2024

As the rural economy develops, the proportion of social expenditures in rural households is gradually increasing, significantly impacting household wealth. This study empirically analyses the influence of rural household wealth levels on social expenditure burdens using data from the 2014 China Family Panel Studies (CFPS). By applying a multiple regression analysis, the study finds that household wealth levels in rural areas significantly affect the burden of social expenditures. Specifically, households with lower wealth levels often face greater financial pressures from these expenditures. The results of this research provide important insights into how economic conditions within households influence consumption behaviour. Understanding this relationship is crucial for developing policies that can alleviate the economic pressures faced by rural families, thereby promoting sustainable development in rural areas. This study offers both theoretical and practical contributions by enhancing the understanding of rural household economic behaviour, particularly regarding the impact of household wealth on social expenditure. The empirical findings provide valuable insights for policymakers seeking to better guide rural consumption patterns and alleviate the financial burden on low-income households. Furthermore, the research introduces a fresh perspective on optimizing social expenditure structures while fostering harmonious social relationships within rural communities.
Deviation from Rationality: Black Friday Studies and Tesla Stock Price Fluctuations
Authors: Wang Chunhui
Published: December 2024

This paper examines rationality from a bahaviour economic perspective, based on the case of consumers irrationality on Black Friday and investors irrationality in Teslas stock fluctuations, constructing an applicable insight into traditional economic theories. This study mainly focuses on three terms: Mental accounting, risk preference, attention theory and relevant social factors among consumers, investors, and market regulators, which results in market inefficiency and disinformation. Traditional theories suggest absolute rationality in decision-making based on perfect information and unchanged preference while the new behaviour theories reveal that humans are controlled by emotion, herding, fear of risk, and many other reasons that push them away from the rational path. In the key findings, consumers are easily overspending due to loss aversion, unjustified mental accounting, and eye-catching advertisement whereas investors in Tesla react overactive to clutter online but not to the financial condition of the enterprise itself, leading to the swing of stock price. Some rational tools like cooling-off periods and regulatory intervention may be suggested in advice. The final section of the paper indicates the future research direction could be on digital techniques and influences on irrational behaviour, accelerating the insights developed in mitigating the biases and instability.
Research on the Comparison of Option Pricing Models
Authors: Ouyang Qianyi
Published: December 2024

Option pricing is essential for market participants as it facilitates risk management and price discovery. This study provides a comprehensive elucidation of diverse option pricing models. The author delineates the development of option pricing models from the fundamental Black-Scholes-Merton model (BSM) to more intricate methodologies. The importance of comprehending option pricing for hedging strategies and risk management is crucial in financial mathematics. The study analyses several models, including the BS model, Jump Diffusion model (JDM), Binomial Tree model (BTM), Monte Carlo simulation (MCS), and stochastic volatility models (SVM), while addressing their applications, limitations, advantages, and disadvantages. This work delineates the history and distinctions between other models and the Black-Scholes-Merton model. The Black-Scholes-Merton model exerts the most substantial influence on financial markets. The alternative models exhibit greater flexibility and enhanced accuracy when confronting complicated and uncertain market trends. The trend of future development is bound to be the continuous updating of models to adapt to more complex situations.
Research on the Supply Chain Optimization Approach of JD's Transformation into a Digital Ecosystem Retailer
Authors: Duan Zeqi
Published: December 2024

With the rapid development of global e-commerce, digital retailing has become an emerging trend, forcing companies to continuously adjust and optimise their supply chain strategies to enhance market competitiveness. This essay will focus on analysing the supply chain optimisation strategies of Jingdong, a leading technology-driven e-commerce platform in China, during its transformation from a traditional e-commerce to a digital eco-retailer. The study focuses on JD's data quality and management issues supply chain innovation, and model adaptation issues. Through case studies on technological innovation, logistics expansion, and ecosystems, it is found that JD has achieved significant results in matching supply and demand and logistics efficiency. The results of the study show that JD has successfully constructed a highly flexible and responsive supply chain system through comprehensive data analysis and systematic integration of intelligent technologies, and this transformation has not only enabled JD to stand out in the highly competitive market but also provided a successful case for promoting the digital transformation of the whole industry. The significance of this paper is to analyse JD's supply chain optimisation strategy to provide a reference case for academia and corporate practice.
ESOP, Double Agency Cost, and Labor Investment Efficiency
Authors: Zhang Ruihan
Published: December 2024

Based on the data of Shanghai-Shenzhen A-share listed companies from 2015 to 2022, this paper investigates the impact of employee stock ownership plan implementation on labor investment efficiency. It is found that the implementation of ESOP can significantly improve the efficiency of labor investment, and in this process, the double agency cost plays a part of the intermediary role. In order to solve the potential endogeneity problem caused by self-selection bias, this paper uses the results of propensity score matching to perform regression again, and the conclusion remains unchanged. Further research shows that employee stock ownership plans improve labor investment efficiency mainly by improving labor overinvestment rather than labor underinvestment, and the improvement effect of employee stock ownership plans on labor overinvestment is more significant in private enterprises. On the whole, this paper explores the influencing factors of labor investment efficiency from a new perspective, and provides a reference for enterprises and related departments to improve the efficiency of labor resource allocation.
Enterprise Value Evaluation Based on DCF Model - A Case Analysis of Hengrui Pharma
Authors: Su Junxiao
Published: December 2024

The pharmaceutical industry plays a critical role in the national economy, and the valuation of pharmaceutical companies is also a key concern for investors. There are many kinds of method to evaluate the company. We can use the Discounted Cash Flow (DCF) model and relative valuation methods, such as the Price-to-Earnings (P/E) ratio and Price-to-Book (P/B) ratio. The DCF model is a common model for company valuation. Therefore, in this paper, we evaluate the financial data of Jiangsu Hengrui Pharmaceuticals Co., Ltd from 2019 to 2023 by using the DCF model. We also show how to calculate the weighted average cost of capital (WACC) using the financial data and compare the actual intrinsic value with the result evaluated from the DCF model.
The Development Process of Traditional Commercial Banks and Its Transformation in the New Era
Authors: Liu Ziming , Zhang Wenxi
Published: December 2024

With the development of digital technology, the rise of several online financial platforms has had a huge impact on traditional commercial banking. Compared with traditional commercial banks (TCB), digital finance has high efficiency, low risk, low threshold, and diversified services, which has caused huge competitive pressure on commercial banks. For the high-speed and high-quality development of the national economy, the transformation of TCB has been urgent. However, there is a lack of summary on the specific transformation methods and feasibility of TCB in the existing studies. This paper reviews the development process of TCB and digital finance, compares the advantages and disadvantages of digital finance compared with TCB, and tries to analyze the reasons and methods for the transformation of commercial banks. Finally, the conclusion is drawn: Although the emergence of digital finance has squeezed the ecological niche of some TCBs, the transformation process of TCBs is full of risks and challenges. However, commercial banks can achieve transformation by increasing initial capital investment, optimizing talent selection and management mode, and expanding business diversity to absorb and integrate the advantages of digital finance to promote their own and national economic prosperity and development.
The Differences in the Wealth Gap Between China and America
Authors: Guo Yahan
Published: December 2024

When delving deeper into the comparative analysis of the wealth gap between China and the United States, people must first acknowledge that these two nations, as pivotal engines of the global economy, have had their respective wealth distribution landscapes shaped by a myriad of factors, including their developmental trajectories, social structures, and policy orientations. While the wave of globalization has presented both countries with unprecedented opportunities for economic growth, it has simultaneously intensified infra-societal divisions, thrusting the issue of wealth inequality into the global spotlight. In the face of the ever-widening wealth gap, both China and the United States are actively exploring effective solutions. China has endeavored to forge a more equitable and rational social structure by deepening its reform and opening-up policies, promoting high-quality development, and strengthening its social security system. Meanwhile, the United States has sought to alleviate wealth inequality by adjusting tax policies, enhancing vocational education and training, and expanding social security coverage. Looking ahead, both countries must continue to strengthen their cooperation and exchanges, sharing their successful experiences and lessons learned in poverty reduction, social security, and tax regulation. By doing so, they can jointly contribute to narrowing the wealth gap on a global scale and fostering a more inclusive and sustainable development paradigm.
Competitive Analysis of Cross-border E-commerce Business of Logistics Enterprises: The Case of Rookie Wrap Company
Authors: Juan Xinkai
Published: December 2024

This paper discusses the competitiveness of logistics companies in cross-border e-commerce business, using Rookie wrap as an example. Through a comparative analysis of the development history, characteristics and comparison with other logistics companies (e.g., S.F.Holding Co.,Ltd), this paper summarizes the key factors affecting the competitiveness of logistics companies, including market size, revenue capacity, business diversification, growth rate, technological innovation and service innovation. It is found that Raiding Bird Wrapped, relying on the strong background of Alibaba Group, has a huge potential scale and influence in the field of e-commerce logistics, and actively lays out intelligent logistics and overseas markets. In contrast, SF has a more comprehensive business layout, including express delivery, supply chain management, e-commerce logistics and international business, showing a stronger anti-risk ability. The article points out that the key to enhance the competitiveness of logistics enterprises is to actively explore the market, increase market share, and adjust and optimize the business structure, focusing on the development of business strengths, while trying to expand new businesses. Through continuous technological innovation and service upgrading, logistics enterprises can consolidate their position in the fierce market competition and realize sustainable development.
Application of SARIMA Model: Forecasting CPI and PPI Inflation Rates in the U.S.
Authors: Yao Xingjie
Published: December 2024

This research seeks to improve the precision of future inflation rate forecasts through a comprehensive analysis of the time series data of the U.S. Consumer Price Index (CPI) and Producer Price Index (PPI). This holds significant reference value for the government when formulating economic policies, monetary policies, and fiscal decisions, especially when facing economic fluctuations or external shocks, as it can provide more accurate inflation expectations, thereby enabling the formulation of more forward-looking regulatory measures. The data for this research is sourced from the FRED database, which contains detailed historical CPI and PPI data. This research utilized the traditional SARIMA model for time series analysis and performed thorough data preprocessing and trend analysis to guarantee the stability and predictability of the data. The results indicate that the SARIMA model exhibits different effects in capturing the trend changes of CPI and PPI inflation rates: first, the SARIMA model demonstrates high accuracy in identifying and predicting the long-term trend of CPI; second, it shows stronger adaptability and accuracy in short-term predictions of PPI change rates. This indicates that different economic indicators respond differently to the model. In the future, it may be worth considering the introduction of other advanced forecasting models, such as machine learning algorithms and hybrid models, to further enhance the predictive capability regarding changes in the inflation rate, thereby providing policymakers with more precise data support.
Understanding Female Consumer Psychology and Marketing Strategies in Chinas Tea Beverage Industry
Authors: Huang Chixin
Published: December 2024

This research delves into the psychology of female consumers and the effectiveness of marketing strategies in China's rapidly expanding and highly competitive tea beverage industry. Through a detailed analysis of a survey conducted with 66 young, urban women, the study investigates their purchasing behaviors, brand preferences, and the significant impact of various marketing strategies on their decision-making processes. The findings reveal that taste, health benefits, and price are the most influential factors driving purchase decisions, with Heytea emerging as the most favored brand among respondents. Additionally, the study underscores the crucial role of social media in shaping consumer awareness and engagement, though it also highlights that direct interaction with brands on these platforms remains limited. Emotional drivers, such as indulgence and self-reward, further influence purchasing behavior, yet overall brand loyalty is found to be moderate. These insights highlight the importance of tea brands prioritizing high product quality while continuously innovating their marketing strategies to effectively connect with and retain this key demographic in a highly competitive market.
Research on the Development of Intelligent Logistics Technology--Taking Community End-of-Life Delivery as an Example
Authors: He Yueyao
Published: December 2024

The development of the Internet has brought new opportunities for the development of the logistics industry, allowing China's logistics enterprises to grow rapidly. With the establishment of more logistics companies, the domestic logistics industry has formed a huge logistics network that leads the world. Affected by the epidemic, contact-free intelligent distribution has become a new direction for the development of community distribution. With the rapid development and growth of the e-commerce field, the demand for logistics and distribution has increased dramatically, and shortening the distribution time of each transportation link and reducing labor costs have become the focus of the logistics field. This paper focuses on intelligent express cabinets, unmanned delivery vehicles, and drone distribution. It analyzes the development history and current state of these technologies. The paper highlights how intelligent technology improves supply chain efficiency. It also identifies the existing shortcomings and risks in the application of intelligent technology in logistics and distribution. Finally, it offers optimization suggestions.
South Korea: Becoming a Developed Nation Through Reforms and Macroeconomic Policies
Authors: Huang Jingru
Published: December 2024

In the 1960s, the Republic of Korea was one of the poorest countries in the world, yet in the 2000s, the country became classified as a developed country. This paper explores South Koreas transformation from a developing nation to a developed economy, emphasizing the role of strategic government policies, financial reforms, and the impact of the 1997 Asian Financial Crisis. The $58 billion bailout by the International Monetary Fund and subsequent reformscorporate restructuring, banking sector overhaul, and labor market adjustments through South Koreas Five-Year Planswere crucial in stabilizing the economy and restoring investor confidence. This paper also analyses these interventions from both classical and Keynesian economic perspectives, highlighting how they improved market efficiency, financial discipline, and aggregate demand. The policies and plans that were included in South Koreas dramatic change from a poor country into a developed one offer valuable insights for developing countries on financial stability and strategic policy implementation in achieving sustainable economic growth.
The Relationship Between National Income and Mental Health: Analyzing GNI and Depressive Disorders Across Nations
Authors: Xu Meng
Published: December 2024

This study explores the intricate relationship between economic inequality and the prevalence of depressive disorders across countries from 1990 to 2021. Gross National Income (GNI) per capita is used as an economic measure, and its association with mental health outcomes, particularly depressive disorders, is analyzed. By employing advanced predictive models, including Random Forest, ARIMA, and ETS, we estimate future mental health trends, providing a comprehensive picture of how economic factors shape mental health disparities globally. The datasets are sourced from the World Bank and WHO, ensuring robustness in the studys conclusions. According to the forecasts generated by the ARIMA model, depressive disorder rates might escalate to exceed 6,000 cases per 100,000 people by 2030 in the absence of specific interventions. This underscores the pressing necessity for policymakers in high-income nations to tackle both income disparities and enhance mental health facilities. Both the ARIMA and ETS models delivered forecasts that closely aligned with actual rates, where the ARIMA model exhibited an RMSE of 927.97, while the ETS model demonstrated a slightly better performance with an RMSE of 573.65. These findings underscore the significance of economic factors in forecasting depressive disorder rates.
How Aging and Low Fertility Influence Household Savings: A Case Study in China
Authors: Li Yushi
Published: December 2024

This paper investigates the intricate relationship between demographic changes, particularly population aging and declining fertility, and household savings rates, with a specific emphasis on China. These demographic shifts carry significant consequences for economic growth and stability. As China's population ages, the growing demand for healthcare and pensions exerts pressure on household savings, while a declining fertility rate raises concerns about the future labor force and the sustainability of long-term savings. This paper reviews key theoretical frameworks such as the life-cycle hypothesis and precautionary savings theory, examining how shifts in population age structure influence consumption patterns, savings behavior, and overall economic resilience. Additionally, it delves into the broader socio-economic challenges posed by these demographic trends, including potential labor shortages and increased fiscal strain. By synthesizing a wide range of research, this review provides a comprehensive analysis of these demographic trends, offering insights for policymakers to promote sustainable household savings while ensuring balanced economic growth.
Transportation Integration in the Greater Bay Area: A Strategic Analysis of Guangzhou's Economic Prospects
Authors: Huang Tao
Published: December 2024

After 2020, the development of the Guangdong-Hong Kong-Macao Greater Bay Area has garnered significant attention and sparked extensive research and discussions. The Outline of the Development Plan for the Greater Bay Area was officially released on February 18, 2019, marking a new phase in its development. Guangzhou, as the political, economic, and cultural center of Guangdong Province, plays a crucial role in enhancing its transportation advantages within this new development framework. Improved transportation construction can boost Guangzhou's competitiveness in various ways. This paper aims to discuss the opportunities and challenges presented by transportation integration in Guangzhou by comprehensively analyzing the economic structure of the Greater Bay Area, examining the implemented or planned transportation projects since the concept was introduced, and integrating transportation integration theories with Guangzhou's actual circumstances. The study will explore aspects such as policy direction, geographical location, and future planning, concluding with recommendations for Guangzhou's economic development based on its current situation and objectives.
The Development and Transformation of Digital Economy Before and After the Pandemic Era
Authors: Liu Jianzhou , Wu Yuner
Published: December 2024

COVID-19 has significantly impacted the global economy. The pandemic pushed the digitalization of the economy as a catalyst accelerating the changes and leaving a profound imprint in the digital economy as many temporary measures had a long-lasting impact or were kept or modified. Nowadays, digital technology has gradually transformed from being merely an information carrier into a production factor. The digital economy enhances the efficiency of production factor allocation by upgrading industrial structures digitally and helping manufacturing break down information barriers. As a result, the application of digital technology has become a key factor in the development and transformation of the manufacturing industry. COVID-19 has driven the transformation of the industrial chain in production, transportation, storage, and sales, improving the efficiency of various economic operations through the expanded application of the digital economy. In the post-pandemic era, the digital economy mainly faces challenges from security, governmental regulation, and the digital divide, whose solution or proper handling is vital for the development of the digital economy. However, the vision for the development of the digital economy is bright as it is beneficial to both individuals and enterprises, is encouraged by many governments, and is consistent with the idea of connectivity and sustainability.
The Research of Supply Chain Management in Chinas E-commerce Environment Taking JD.com as an Example
Authors: Cao Yue
Published: December 2024

In the environment of the rapid development of e-commerce in China, JD.com has adapted to this trend and established its own relatively complete e-commerce and logistics system. However, JD.com still needs to continue optimizing its supply chain and solve some existing problems in order to cope with the changing environment and enhance its competitiveness. These problems include logistics cost, cooperations with traditional enterprises, and dual-channel supply chain. In response to these problems, this article puts forward three suggestions. From the aspect of the inter-enterprise information sharing, this article first advises JD.com to optimize existing logistics costs. Then the second one is to advise JD.com to keep developing the internet of things (IOT) technology from the aspect of logistics technology. Moreover, the last suggestion is that JD.com should use different pricing strategies depending on different circumstances from the aspect of the client demands and experiences. Eventually, this article aims to provide ideas for JD.com and other similar enterprises in their future reform and thus make certain contributions to the development of e-commerce and even the economy in China.
Forecasting Amazons Quarterly Net Sales Based on Time Series
Authors: Wang Shihan
Published: December 2024

This paper presents an in-depth analysis of the Autoregressive Integrated Moving Average (ARIMA) model for forecasting Amazons quarterly net sales, using historical data from 2007 to 2019. The models ability to handle trends and seasonality in time series data is highlighted. The study outlines the data transformation process, including log transformations and differencing, to ensure stationarity before model development. Four potential ARIMA models were constructed based on the observed autoregressive and moving average characteristics. The ARIMA(3,1,4) model was ultimately selected for its optimal balance between simplicity and prediction accuracy. A thorough diagnostic assessment was then conducted to ensure that the selected model met important assumptions of the ARIMA framework. The study proceeds to forecast Amazons sales for the next eight quarters in 2020 and 2021, demonstrating the model's practical utility in predicting future sales trends. The insights obtained aim to optimize inventory management, improve resource allocation, and better understand seasonal sales fluctuations. These findings offer strategic insights for e-commerce decision-makers.
A Case Study on How to Improve Cold Chain Logistics for Specialty Food and Agricultural Products
Authors: Guan Kelan , Lin Wantong , Zhou Xiaoquan
Published: December 2024

Even with China's continuous progress in cold chain logistics (CCL) and route planning, issues with ensuring food quality still arise, especially when shipping speciality foods and agricultural products in the cold chain. Furthermore, there is a greater need for cold chain transportation as a result of the recent expansion of the markets for specialized foods and fresh agricultural products. However, due to the lack of transportation connection, it is difficult to maintain high quality of some products as part of the transportation process, which leads to difficulties in maintaining the original quality of specialty foods when transported across regions. By analyzing typical cases of cold chain logistics in China, this study delves into the problems in the existing cold chain transportation system and proposes targeted strategies to improve link management and technology application during delivery. Making a cold chain distribution plan that fits China's present business environment is the goal of this study. In order to improve agricultural product quality assurance during transportation, as well as promoting the high-quality development of the sector in China, this entails optimizing resource allocation and technical standards.
Problems and Solutions in US Stock Market
Authors: Liu Zihe
Published: December 2024

This research explores critical challenges facing the U.S. stock market, specifically focusing on the impacts of algorithmic trading-induced market volatility and cybersecurity threats. Algorithmic trading, which utilizes high-speed computer systems to make trades, has increased market efficiency but also introduced risks of extreme price fluctuations and flash crashes. In parallel, the digitalization of financial markets has heightened exposure to cybersecurity threats, posing risks to trading integrity and data security. To address these issues, this study proposes two targeted solutions. For the issue of market volatility driven by algorithmic trading, the research recommends implementing circuit breakers and trading halts. These mechanisms can prevent severe market disruptions by temporarily pausing trading during extreme price movements, allowing the market to stabilize and preventing panic-driven selloffs. For the cybersecurity challenges, the study suggests enhancing information sharing and fostering collaborative defense strategies among financial institutions and regulatory bodies. By encouraging greater collaboration, the financial sector can more effectively identify and counteract cybersecurity threats, reducing vulnerabilities across the market.
Analysis of the Current Situation and Strategies of Traditional Vehicle Transition to New Energy Vehicles in China
Authors: Liu Ruochen
Published: December 2024

The global climate issue has become one of the most significant problems for the. world, demanding an urgent transition to a new, sustainable energy paradigm. As one of the slightly larger automobile markets in the world, China has begun to address the underlying issue proactively by hastening the transformation from conventional fuel vehicles to new energy vehicles (NEVs). Consequently, to this end, the Chinese government has rolled out a set of policies that include provisions such as financial subsidies, tax incentive plans, as well as the development of the charging infrastructure, which has effectively stimulated the sales growth and industrial upgrading of new energy vehicles. This paper will provide a comprehensive analysis of the current status and impact of policy implementation, while also discussing the challenges of transitioning, such as technological limitations, market resistance, and international competition, and formulating specific strategies that target these issues. These studies seek to be real-data-based and explain how to approach sustainable development in the new energy vehicle industry of China.
Analysis on the Urbanization in China and the United States
Authors: Wu Jiaming
Published: December 2024

This article discusses urbanization in China and the United States, and show the differences in the developing paths and similarities in the challenges. The paper studies how China, as a developing country, expands its urbanization significantly in the past decades and how it responds to the challenges of urbanization. On the contrary, the United States, as a developed country, has already gone through what China is experiencing now. This paper finds that environment and infrastructure are the main issues both countries would face in urbanization. Policies in developed countries tend to focus on enhancing quality of life, green infrastructure, and sustainable urban design. However, governments in developing countries tend to be more concerned with resolving informal settlements, enhancing infrastructure, and controlling the fast growth of metropolitan areas; therefore, in pursuit of faster urbanization, they have not noticed the serious impact on the environment. As urbanization is a complex and multifaceted process affecting cities development and surrounding areas, countries could learn from each other and design policies that suit their own development goals.
A Study on the Causes and Solutions to the Global Aging Population
Authors: Huang Ziyang
Published: December 2024

The global demographic landscape is undergoing significant changes due to increasing life expectancies and declining birth rates, leading to an aging population across many countries. This paper explores the multifaceted causes behind this demographic shift, including healthcare advances, fertility patterns, and improved living conditions. This paper examines the implications of an aging population on economic stability, social structures, and public services. In particular, this paper studies the impact on productivity due to a lack of young population, the pressure on the pension system from the increasing number of the elderly, and the corresponding challenges in the healthcare system. The study also analyzes various policy responses implemented by different nations to address these challenges, focusing on innovative strategies from developed and developing countries. Special attention is given to China's approach, highlighting its pension reforms, healthcare enhancements, and elderly care initiatives. By comparing and contrasting these strategies, this paper aims to offer insights into effective policy frameworks and potential areas for future research in managing the impacts of an aging population.
The Benefits and Risks of Chinese VIE Firms
Authors: Liu Dunxu
Published: December 2024

The VIE structure is a unique structure widely used by Chinese companies, especially in industries with restricted foreign investment. Through this structure, Chinese companies can allow foreign investors to indirectly invest money and receive profits through complex contractual agreements without violating domestic and foreign investment restrictions. The operating mechanism of the VIE structure can bring convenience to Chinese companies, provide them with opportunities to enter the international capital market, help them circumvent foreign investment access restrictions, improve company valuations and market liquidity, and simplify the IPO process. However, the structure also faces many risks, including legal uncertainty, regulatory risks, and tax and information security issues. Given that the VIE structure relies on contracts with uncertain enforceability, which are not recognized in the Chinese legal system, foreign investors face greater legal risks when investing in VIE-structured companies. Through an in-depth analysis of Chinese VIE firms, this article aims to provide a reference for investors and policymakers to better understand its advantages and disadvantages and explore its future development direction.
Exploring China's Transition from Old to New Driving Forces -- From the Perspective of New Productive Forces
Authors: Zhu Zixin
Published: December 2024

This paper explores Chinas transition from traditional growth drivers, such as manufacturing and investment, to new quality productive forces that emphasize innovation, technological advancement, and sustainability. Against the backdrop of diminishing returns from resource-intensive industries and rising global competition, China has strategically pivoted toward innovation-driven growth as a necessary path for long-term economic resilience. The research focuses on analyzing the role of new quality productive forces in driving this transition, with a particular emphasis on their impact on productivity, industrial upgrading, and sustainable development. Using a combination of qualitative analysis and case studies, this paper examines the technological innovations and policy initiatives that are reshaping Chinas economic landscape. The study includes an analysis of sectors such as renewable energy, telecommunications, and electric vehicles to illustrate how these new forces are transforming industries and creating new opportunities. The findings reveal that while the transition presents significant challenges, such as the need for large-scale workforce reskilling and managing technological disruptions, it also offers substantial opportunities for economic growth and global leadership. The study concludes that fostering new quality productive forces is essential for China to maintain its competitive edge in the digital economy and achieve sustainable, long-term growth.
The Implications of Population Aging for Socio-economic Development
Authors: Ye Peiwen
Published: December 2024

The severity of population aging profoundly impacts social and economic development over time. This paper analyzes some important factors leading to population aging, their social impacts, and development trends summarizes some strategies that may slow down this social phenomenon and demonstrates some factors that may gradually reduce the effect of population aging and the development reasons for these factors. Some aspects that may promote the intensification of population aging and corresponding solutions are proposed to reduce the negative impact. Conclusion Population aging would have negative influence mostly in the future. However, this social phenomenon will also contribute to the development of the society in some totally new developed parts that may lead to the change of economy of the society. Moreover, population aging will also have influence on a countrys culture and politics which might change peoples cognition in the future and the countrys diplomacy with other countries.
Research on Different Development Stage Consumption and the Consumption Impact on Sustainable Development in South Korea
Authors: Dong Jing
Published: December 2024

Sustainable development has become a cornerstone of global economic progress, shaping the decisions and policies that guide nations today. The economic trajectory of each country, including the current situation, is deeply rooted in its historical development. By examining this historical context, we can better understand the present and make informed predictions about the future. This article delves into the economic evolution and consumption patterns in South Korea over the past 50 years. Through a detailed analysis of historical data, the study seeks to reveal how South Koreas economic strategies and consumption trends have influenced its sustainable development. Furthermore, the article offers tailored recommendations for promoting sustainable growth in alignment with South Koreas current economic landscape. By exploring the intricate relationship between consumption levels and economic development, this study provides valuable insights into how past practices have shaped present conditions and offers a roadmap for future sustainability. The goal is to not only understand the past but also to leverage this understanding to craft strategies that ensure long-term economic and environmental well-being.
Study on the Dynamic Relationship Between Social Security Expenditure, Population Aging and Economic Growth
Authors: Zhao Pangbo
Published: December 2024

As the global wave of aging accelerates, China has entered a notable phase of moderate aging. This profound demographic shift has not only reshaped the population composition of society but also posed severe challenges to the driving force of economic development and the carrying capacity of the social security system. This paper delves into the intricate and interdependent relationship network among population aging, social security expenditures, and economic growth. The research finds that the aging process directly impacts the potential and speed of economic growth by reducing labor supply and increasing labor costs. Conversely, the strength of economic growth serves as the cornerstone, determining the financial adequacy and sustainability of the social security system, which in turn indirectly influences the welfare protection level for the aging population. Therefore, the core strategy for addressing the challenges of aging lies in stimulating the vitality and potential of economic growth to provide a solid economic foundation for the social security system. Simultaneously, it is necessary to meticulously design social security policies to ensure that expenditures meet the reasonable needs of the elderly population while avoiding excessive fiscal shocks to stability.
The Economic Impact of Income Inequality in Eastern, Central and Western China
Authors: Fang Yuzhe
Published: December 2024

It is important to address one of the most common problems in economics for decades, which has been the global wealth inequality, and to promote common economic prosperity and balanced economic growth. This research examines the various impacts of income inequality on economic growth in Eastern China, and compares it with economic development in Central and Western China. Shanghai, Suzhou and Hangzhou in Eastern China have experienced significant economic transformation, but this has also exacerbated the unequal distribution of wealth and income. By analyzing economic growth, infrastructure investment, and the allocation of educational resources across regions, this paper emphasizes how these elements lead to significant economic inequalities among the Eastern, Central, and Western China. Furthermore, the paper investigates the adverse financial impacts of income inequality on consumer demand, social stability, and labor force utilization, and provides policy suggestions for fostering common prosperity and more balanced economic growth. In short, it is necessary to achieve more inclusive and sustainable economic growth through more balanced regional development policies.
Optimization Strategy and Environmental Impact Analysis of Green Supply Chain
Authors: Hu Jie
Published: December 2024

With the increasingly severe global environmental problems and the enhancement of public awareness of environmental protection, Green Supply Chain Management (GSCM) has become an essential strategy for enterprises to achieve sustainable development and enhance competitiveness. Green supply chain management not only focuses on economic benefits, but also emphasizes reducing environmental pollution and improving resource utilization efficiency in the whole process of the supply chain, to promote the harmonious coexistence between enterprises and the environment. Through literature review and case analysis, the current situation and trend of global supply chain carbon emissions are analyzed, and the research focus and direction are clarified. Through the effective use of PLCs automation, ERP can make the supply chain information transparent and strengthen the management of the supply chain. At the same time, LCA's carbon footprint tracking improves the efficiency and accuracy of tracking, and promotes the digital and decentralized development of the carbon market.