bluuebunny/crossref_metadata_2025 huggingface dataset:
The Factors of Russias Problems on Economic Structure and Solutions
Authors: Shen Yicheng
Published: January 2025

Russia's economy has long been driven by its vast natural resources, especially its oil and natural gas exports. Based on the data in recent one or two decades, this study mainly focuses on problems and challenges that Russian economic are facing, for example, the overelience on fossil fuel export and the international politic pressure. It analyzes the causes of these problems and provides several solutions and suggestions for the future economy of Russia. To achieve long-term economic sustainability, Russia should reduce its dependence on fossil fuels and diversify into other sectors such as agriculture, manufacturing, and renewable energy. Additionally, improving domestic purchasing power and encouraging investment in local industries can help the economy withstand external shocks. Policy adjustments, such as managing interest rates and enhancing agricultural technology, are also crucial steps toward building economic resilience. The paper may offer possible solutions to Russia to improve the economic development.
Research on the Improvement Path of Financing Constraints for Small and Medium-Sized Enterprises Empowered by Digital Transformation
Authors: Xu Leqin
Published: January 2025

This paper, based on literature related to big data and corporate financing, analyzes and explores the mechanisms and effects of big data technology in alleviating corporate financing constraints. As is known to all, Financing constraints have always been an important factor restricting the development of small and medium-sized enterprises, and digital transformation provides new ideas to alleviate this problem. The current situation of financing constraints is apparently complex and diverse, which is involving multiple aspects such as information asymmetry, limited financing channels, high financing costs, policy and market environment, as well as enterprise ownership and industrial structure.It argues that big data technology, with its powerful data processing and analytical capabilities, effectively reduces information asymmetry, broadens financing channels for enterprises, and significantly lowers the costs of debt and equity financing, thereby alleviating corporate financing constraints. Digital transformation not only enhances the profitability and sustainability of small and medium-sized enterprises but also strengthens investor confidence by improving market transparency and risk management capabilities, providing strong support for corporate financing.
Analysis on the Management Model of PepsiCo
Authors: Zhu Peiling
Published: January 2025

In the world of food and beverage, PepsiCo is one of the leading companies. This study examines PepsiCo's management model, including leadership development, operational efficiency, supply chain management, product innovation, and corporate social responsibility. Based on the results of this study, PepsiCo maintained a steady supply of leadership through internal promotion and continuous training. Furthermore, the company consistently innovated its products in order to meet the market's demand for healthy food. With regards to marketing and brand management, multi-channel marketing and the development of brand IP greatly enhanced PepsiCo's market influence, especially among young consumers. In terms of corporate social responsibility and sustainable development, PepsiCo's PEP+ demonstrates its commitment to social responsibility and has a positive impact on society and the environment. This study provides an in-depth understanding of PepsiCo's management model as well as a blueprint for researchers seeking to study it.
ESG Rating Divergence and the Risk of Corporate Share Price Crashes: Facilitation or Suppression
Authors: Chen Zhe
Published: January 2025

The absence of standardized criteria has resulted in significant discrepancies in corporate ESG ratings across different agencies, potentially causing investors to misinterpret corporate ESG performance. This study empirically examines the relationship between ESG rating divergence and stock price crash risk, drawing on data from A-share listed firms in Shanghai and Shenzhen between 2015 and 2022.The findings reveal that ESG rating divergence plays a critical role in mitigating the risk of stock price crashes. This effect is primarily driven by the reduction in corporate earnings management and the decrease in analysts' forecast biases. The study holds substantial relevance for both theoretical and practical spheres in terms of enhancing the understanding of ESG rating divergence. Furthermore, it broadens the research on determinants of stock price crash risk and provides empirical evidence for promoting a unified ESG rating system in China.
Impact of Airline Alliance Participation on Quality of Carbon Emission Disclosure: Insight from 64 Airlines Worldwide
Authors: Dai Yubo , Mao Zihan , Lou Xiaofan
Published: January 2025

The rapid expansion of the aviation industry has served as a significant driving force for global economic growth. However, it is crucial to acknowledge that aviation has emerged as a major contributor to greenhouse gas emissions. Efforts have been made by airlines, government agencies, and international organizations worldwide to achieve carbon neutrality in the aviation sector. While some initiatives have yielded initial results, others have proven ineffective. Currently, airline alliances, as a distinctive international organization within the aviation industry, account for over half of global capacity and wield substantial influence. Extensive research exists on carbon emission disclosure in the aviation industry and the impact mechanism of airline alliances on their members is well-established; however, few studies have linked these two aspects to explore how joining an airline alliance affects airlines' progress towards carbon neutrality. This study selects 64 airlines from around the world to examine disparities in the quality of carbon emission information disclosure between independent carriers and members of airline alliances with an aim to comprehend the role played by airline alliances in promoting sustainable development among their constituents. The author hopes that this paper's findings can offer guidance and assistance for airline managers and leaders within relevant government agencies when making subsequent decisions regarding enhancements in carbon emission disclosure.
The Research on the Differences Between the Markowitz Model and the Index Model under Different Constraints
Authors: Li Ge
Published: January 2025

Investment portfolio optimization has been a commonly discussed topic. This paper compared the differences between two established models regarding such topic, the Markowitz Model and the Index Model, by comparing the optimized portfolio outcomes formed by ten stocks, one equity index (the S&P 500 Index), and a proxy for the riskless asset (1-month Fed Funds Rate) under five different scenarios that each simulates a particular real-life circumstance, and concluded that while the Markowitz Model produced more optimistic results under situations with no constraints, with an arbitrary box constraint, and with a constraint of excluding the broad index, the Index Model outperformed the Markowitz Model under the constraints that simulate Regulation T and the U.S. mutual funds industry. This paper provided an analysis of the strengths and weaknesses of each model under different schemes by comparing the total returns, risks, and reward-to-volatility rate of each portfolio. It may also guide the investors who aim to optimize their portfolios to some extent.
Analysis and Valuation of WiseTech Global Based on Combined CAPM and WACC Valuation
Authors: Zhao Lanxin
Published: January 2025

This paper provides a detailed analysis and valuation of WiseTech Global (WTC), a prominent growth firm in the Australian information technology industry, utilising the Capital Asset Pricing Model (CAPM) and the Weighted Average Cost of Capital (WACC). The research establishes WTCs classification as a growth firm based on quantitative and qualitative criteria, highlighting its exceptional performance metrics, including a compound annual growth rate (CAGR) significantly above its industry average. In addition, the CAPM model is applied to calculate the return on equity, while both the return on equity and debt is incorporated in the WACC calculation to assess WTCs overall capital cost. The analysis forecasts WTC's growth rates for both the short and long term, predicting future free cash flows (FCF) and using a Discounted Cash Flow (DCF) model for valuation. The results indicate that WTC may be overvalued by the market, leading to a recommendation for short selling its equity, questioning the assumption that growth companies inherently have superior future investment potential.
Analysis of the Impact of Urbanization Level on the Income Level of Provincial Cities: A Case Study of Provincial Cities in China
Authors: Liu Yuanqing
Published: January 2025

With the rapid urbanization process in China, understanding the impact of urbanization on socio-economic indicators has become important. This study first identified the possible relationship between urbanization and income inequality through literature review. Then, using data from the entire country and the eastern, central, and western regions, empirical analysis was conducted using random effects models. Using panel data and the regression estimation approach, this study investigates how China's urbanization affects income levels. The research data cover 31 provinces in China across 5 years, 2018 to 2022. Regression analysis is performed in this article using the Gini coefficient as the dependent variable and the urbanization rate, per capita GDP, percentage of tertiary industry, and education level as the independent variables. Hausman's test was used to identify the best model, and robustness tests were carried out to guarantee the accuracy of the findings. According to this study, the rate of urbanization has no discernible effect on income disparity across the country; but, in the central region, the rate of urbanization significantly increases the Gini coefficient, suggesting that the procedure of urbanization may make income inequality worse there. Policy makers might find significant value in the research findings as a reference, and it is advised that they take into account the various impacts of urbanization when developing regional economic policies in order to achieve more equitable socioeconomic development.
Artificial Intelligence and the Metaverse: Transforming the Future of Medical Education
Authors: Huang Cancan
Published: January 2025

This paper focuses on the prospects of artificial intelligence and future the metaverse in medical education and training. Artificial intelligence significantly improves the efficiency and quality of medical education through personalized learning path customization, virtual surgery simulation and image diagnosis assistance. The introduction of the metaverse, on the other hand, breaks the time-space limitation of traditional education, provides immersive learning experience for medical students, and greatly promotes the improvement of clinical skills and practical ability. However, AI and the metaverse in medical education and training also face challenges such as data security, algorithmic bias, educational imbalance and cyber-attacks. To safeguard patient privacy and data security, data protection measures need to be strengthened; at the same time, there is a need to promote the popularization of the technology to ensure that every student has equal access to quality educational resources. In summary, artificial intelligence and the future the metaverse bring unprecedented opportunities and challenges to medical education. With the continuous progress of technology and the expansion of application scenarios, these technologies will play a more important role in medical education and promote the cause of medical education to move forward.
The Impact of the Digital Economy on the Educational Landscape
Authors: Yuwen Xinuo
Published: January 2025

The digital economy is a big change that comes from innovative technologies, especially the Internet, artificial intelligence, and large amounts of data. This shift has improved learning by making it easier for people to get and get educational supplies. Online platforms like Massive Open Online Courses ( MOOCs ) and learning management systems ( LMS ) provide more people with access to good educational materials. This helps break down the barriers caused by area and money that have made it difficult for some people to get training in the past. The digital divide creates major problems because not everyone has the same access to technology and excellent online. This may make previously existing inequalities worse, especially for disadvantaged communities. Moreover, more people need to be good at using modern technology because kids have to learn how to utilize online websites. Making sure everyone gets virtual learning resources is very important for using the digital economy to help improve education for all. By tackling the problems of uneven access to technology and including online skills in school programs, people involved can create a more loving training program that helps everyone get back and promotes fairness in the economy.
A Comparative Analysis of Dewu's Differentiation Marketing Strategy with Similar Platforms/ Competitors
Authors: Zhang Zhanming
Published: January 2025

In the rapidly evolving landscape of e-commerce, differentiation has become a critical strategy for platforms to maintain competitive advantage and foster consumer loyalty. This paper explores the differentiation strategies of Dewu (Poizon), a leading e-commerce platform in the streetwear and luxury goods market in China, and offers strategic recommendations for strengthening its market position. Dewu's existing strategies, such as emphasizing product authenticity, integrating social commerce, and leveraging cultural storytelling, have helped it establish a niche identity. However, the platform faces challenges related to brand dilution, consumer dissatisfaction, and increasing competition in a digital-first environment. By exploring opportunities in personalization, immersive technologies, and culturally-driven marketing, this paper proposes three key recommendations for Dewu's differentiation strategy. These strategies aim to enhance consumer engagement, strengthen brand loyalty, and create innovative shopping experiences. Through a comprehensive analysis of Dewu's challenges and opportunities, this paper underscores the importance of differentiation in sustaining competitive advantage in the e-commerce sector.
Empirical Analysis of HSBC: A Comprehensive Evaluation from Investment Perspective Using Historical Data from 2021 to 2024
Authors: Xu Yuan
Published: January 2025

International commercial banks provide worldwide banking services and cater to a varied clientele, playing a crucial role in globalization. HSBC, established in 1865 in Hong Kong, serves as a notable leader in this field. This paper will perform an empirical analysis of HSBCs performance over the last three years, assessing the banks ability to manage risk and return while determining the trend in HSBCs equity and evaluating its investment potential. This analysis should serve as a valuable report for the companys decision-makers. This study employs both qualitative and quantitative research methods to conduct a comprehensive evaluation of HSBCs performance from 2021 to 2024. First, relevant financial ratios will be calculated based on the financial data from HSBCs financial statements. The second segment represents the studys primary focus, applying financial analysis tools to perform a quantitative evaluation of HSBCs performance. This includes computational and visual processing based on publicly available data from sources such as Yahoo Finance and the Kenneth R. French Data Library. Ultimately, forecasts will be produced, and sensitivity analyses conducted. Research indicates that HSBCs finances are relatively healthy. Although its debt ratio is quite high, and recent excessive dividends have led to negative growth in cash flow, financial analysis shows that HSBC possesses strong debt repayment capacity. The substantial dividends reflect the managements positive outlook on the companys future. Furthermore, the results of quantitative analysis indicate that HSBCs stock price is likely to rise in the future, demonstrating robust risk management and stable income capabilities. Investors may consider increasing their investment.
Analysis of the Realization for Trading Security of Cryptocurrency
Authors: Zhang Tianyu
Published: January 2025

With the advancement of digital economy as well as network technology, blockchain was gradually becoming an important driving force for development of different areas. Data on blockchain is stored in a way which is transparent, cannot be changed easily, and does not need to rely on centralized control. Cryptocurrency, which works through blockchain, was showing broad prospects for its use in finance, supply chains, healthcare, and other sectors. Blockchain's application in cryptocurrency is one of the more significant ones. The financial system that existed before faced many problems, and cryptocurrency introduced a new financial service model. While cryptocurrency development has created opportunities, challenges related to transaction security also have been brought along. Researchers work to find algorithms that are new, consensus methods and other protection strategies, to deal with security risks like hacker activity, transaction fraud, and manipulation of the market. These security risks were being addressed through these efforts which, by improving the safety of cryptocurrency itself, would give protection to enable its more widespread use in future. The significance of this paper is found in how it systematically looks at cryptocurrency transaction security, analyzing its safety as well as demonstration of the ways current security measures work and what cost comes with ensuring such safety. This will help dig deeper into the security of cryptocurrencies, and offer references for stable growth of cryptocurrency markets in the future.
The Impact of Corporate Philanthropy, Social Responsibility, Sustainability and Marketing on Brand Cohesion and Brand Effectiveness
Authors: Shen Haokun
Published: January 2025

Companies need to continuously track market change data and update their products and services to remain competitive. In addition, the company's sustainability and social responsibility will also affect its reputation. Companies need to comprehensively improve their overall strength in the three areas of public welfare, social responsibility and sustainable development, and then establish the brand's attractiveness and influence. This paper analyzes the success and publicity of companies in the three areas of public welfare, social responsibility and sustainable development through literature reviews and theoretical analysis, and discusses the help and significance of marketing publicity for the development of enterprises. The research shows that marketing and publicity that focuses on brand benefits can achieve long-term benefits for products and brands and help companies establish long-term relationships with consumers. In addition, establishing close partnerships with different companies, organizations and communities can also achieve sustainable development of the enterprise and improve brand awareness and competitiveness.
The Current Situation and Challenges of Supply Chain Management: Taking Huawei as an Example
Authors: Wei Chiheng
Published: January 2025

Globalization has extended the supply chain to many countries and regions around the world. Enterprises not only have to manage local suppliers but also work with multinational suppliers, manufacturers, logistics service providers, etc. The supply chain network has become complex and full of uncertainty. This paper aims to explore the importance of supply chain management in the modern business environment and analyze how to improve the efficiency and reliability of the supply chain through optimization and innovation. First, this paper will introduce the basic concepts and principles of supply chain management. Then, through literature analysis and network data analysis and taking Huawei as an example, this paper will deeply explore the methods and technologies of supply chain optimization, including Huawei's inventory management, demand forecasting and logistics optimization. Finally, this paper will discuss the importance of supply chain innovation and propose some feasible innovation strategies. This paper finds that supply chain management is changing from the traditional "cost efficiency orientation" to "risk management and resilience building".
Logistics Demand Forecasting and Simulation Based on Support Vector Machine
Authors: Li Nanjin
Published: January 2025

The need for regional logistics has increased dramatically due to the logistics industry's rapid development, underscoring the need for accurate forecasting. The deployment of a precise logistics demand forecasting model has the potential to mitigate expenses, augment logistics efficacy, and furnish direction for forthcoming logistics sector planning. This research suggests an approach based on the Support Vector Machine (SVM) model to increase the accuracy of logistics demand forecasting in light of the complexity of regional logistics demand forecasting. First, in order to determine the primary factors influencing regional logistics demand, grey relational analysis is utilized. Subsequently, the sample data is input, and the Support Vector Machine model is utilized for learning, establishing a relationship model between regional logistics demand and influencing indicators. The predictions produced by a Back Propagation (BP) neural network are then contrasted with this. Lastly, data on logistics demand from Jiangsu Province covering the years 2004 to 2022 is used for simulation study. The results demonstrate that the Support Vector Machine performs better in regional logistics demand forecasting when compared to the BP neural network. The studys findings support the advancement of scientific demand forecasting for regional logistics, offer a vital basis for decision-making in logistics system design, and strengthen the areas potential for sustainable growth.
Decentralized Autonomous Community: Concept, Model, and Innovation
Authors: Lu Wencong , Qian Wenxin , Chen Junru
Published: January 2025

The current economic organizational forms are increasingly inadequate for humanity's long-term development. Blockchain technology, much like the advent of steam engines and power systems, is transforming national governance and market operations. A substantial body of literature has explored Decentralized Autonomous Organizations (DAOs) built on blockchain technology. This paper builds upon existing literature to introduce the concept of a Decentralized Autonomous Community (DAC), delineate its legal framework, and propose a technical model based on the Consortium Blockchain. DACs not only address internal and external decision-making and governance within community systems but also ensure appropriate national supervision. By leveraging the innovative potential of blockchain, DACs promise a more efficient and equitable economic structure that aligns with contemporary societal needs.
The Impact of High-speed Rail on FDI Attraction in Chinese Cities
Authors: Wang Xinyue , Charoenseang June
Published: January 2025

This research aims to investigate how China's high-speed rail system affects Chinese cities' appeal to foreign direct investment. This study uses the multi-time point difference to difference model to investigate the consequences in relation to foreign direct investment in high-speed rail in Chinese cities using panel data from 300 prefecture-level cities in China between 2008 and 2021.The findings indicate that the appeal of foreign direct investment is significantly impacted by the introduction of China's high-speed rail. Placebo test and delayed single-stage regression are also used in this paper, which proved that result is robust. In a further heterogeneity test, Chinese cities are classified according to center-periphery, high-speed railroads and city type. The findings indicate that the FDI influx into nearby cities, non-main line cities, and agricultural cities is significantly impacted by high-speed rails opening. There is no significant effect on FDI inflow in central cities and Cities with high-speed rail main lines The influence of FDI inflow on the service cities is negative. Construction of high-speed rail should be prioritized by the government in the nation's agricultural and comparatively underdeveloped cities, and encourage the building of high-speed rail that is not main line.
The Impact of the Digital Economy on the Export Competitiveness of Green Products in China
Authors: He Yifei
Published: January 2025

This paper utilizes Chinese firms' import and export data and applies a difference-in-differences (DID) method to study the impact of the digital economy on the export competitiveness of green products, while exploring its mechanisms and heterogeneity. The findings indicate that firms' digital transformation significantly enhances the export competitiveness of green products, and this result remains robust under various control variables. The mechanism of influence is primarily reflected in improving production efficiency, reducing production costs, and enhancing firms' Environmental, Social, and Governance (ESG) performance, ultimately helping firms improve their competitiveness in the international market. Heterogeneity analysis reveals that the enhancement effect on export competitiveness is more pronounced for local and innovative firms compared to central enterprises. Additionally, firms exporting to RCEP member countries benefit more from digital transformation due to the characteristics of market demand. Importing firms also see significant competitiveness improvements by increasing supply chain efficiency and adopting advanced technologies. This study has important practical implications for deepening the understanding of the economic effects of the digital economy, promoting green transformation among Chinese firms, and addressing international green trade barriers.
The Impact of Agricultural Science and Technology Innovation on Global Food Supply Chain An Empirical Analysis Based on Panel Data from 68 Food Producing Countries
Authors: Yang Dan
Published: January 2025

With the frequent occurrence of geopolitical, economic and military conflicts in the world, the supply chain security of the global food industry chain is facing serious challenges. In this paper, global food supply chain security(FSCS) is divided into two dimensions: food supply chain dependence and food supply chain concentration, based on cross-country panel data of 68 food-producing countries around the world from 2001 to 2021, firstly, to analyze the global food security situation, and then, based on constructing indexes to measure the agricultural scientific and technological innovation, to empirically estimate empirical estimation of the agricultural scientific and technological innovation(ASTI) capacity impact on global food supply chain security. The results of the study show that agricultural science and technology innovation capacity has a negative impact on both food supply chain concentration and food supply chain dependence; on the whole, the improvement of agricultural science and technology innovation capacity can bring about a decrease in global food supply chain concentration and dependence.
Diamond Price Prediction Based on Regression Algorithms: Analyzing Key Factors and Model Performance
Authors: Xiao Minxi
Published: January 2025

This research investigates the application of machine learning approaches for forecasting diamond prices and determining the main factors that influence pricing within the jewelry sector. The dataset used comprised 53,940 entries, each with 10 attributes. Data preprocessing involved eliminating invalid entries and encoding categorical attributes. Various regression models, including random forest, k-nearest neighbors, Extreme Gradient Boosting (XGBoost), and multilayer perceptron, were assessed. The cross-validation results revealed that the XGBoost model achieved the best performance, delivering the lowest Root Mean Square Error (RMSE) and high predictive accuracy. In testing, the XGBoost model obtained an R-squared (R) of 0.982129 and an adjusted R of 0.982114. The critical factors affecting diamond prices were identified as carat, cut, color, and clarity. This study offers a systematic framework for pricing strategies in the jewelry market and emphasizes the significant role of machine learning in predictive modeling. Further research should aim to refine feature engineering and data processing to enhance accuracy and expand its practical application.
Digital Transformation and Corporate Innovation Quality -- Based on an Internal Management Perspective of the Enterprise
Authors: Zou Hua
Published: January 2025

In the context of the increasingly fierce global competition and the rapid development of information technology, how to enhance its innovation capabilities and market competitiveness through digital transformation has become a research topic widely concerned about the current academic and practical fields. This article selects the relevant data of China's import and export companies from 2017 to 2021 as a research sample. Through detailed data analysis and case research, it reveals the significant effect of digital transformation in improving the innovation quality of enterprises. The research results show that (1) Digital transformation significantly promotes the improvement of the quality of innovation in enterprises; (2) Digital transformation By optimizing the internal management process of the enterprise and improving the efficiency of resource allocation, it enhances the competitiveness of enterprises during the period of kinetic energy conversion; (3) Digital tools have also promoted the efficient allocation of R & D personnel, promoted cross -departmental collaboration, and enhanced the innovative vitality of enterprises. The research results provide theoretical support for enterprises to optimize management and innovation strategies in the background of digitalization.
Research on the Effects of Regional Economic Integration for Urban Economic Development
Authors: Xu Mingze
Published: January 2025

Since the 1970s, regional integration policies have been implemented across the globe, with examples ranging from the European Union and ASEAN to the North American Free Trade Agreement (NAFTA) and various regional trade agreements in African countries. As part of this global trend, China established the Pearl River Delta regional integration policy, leveraging its proximity to Hong Kong and Macau to attract investment and build a modern economic system. This initiative has significantly contributed to making Guangdong Province the leading economic powerhouse in China today. The purpose of this research is to investigate the impact of regional integration policies on economic growth in urban areas. Using the Pearl River Delta (PRD) cities as the treatment group and non-PRD cities as the control group, this study examines the economic effects of regional integration policies in the Pearl River Delta from 2002 to 2022. By utilizing the natural logarithm of GDP (ln-GDP) as an indicator of economic levels and applying the difference-in-difference (DiD) method for analysis, this research aims to provide comprehensive insights into how regional integration policies drive urban economic growth.
Impact of Narrow Framing on Portfolio Allocation: A Numerical Simulation-Based Approach
Authors: Zhao Siqi
Published: January 2025

Many phenomena observed in financial markets remain unexplained by the Expected Utility Theorem (EUT), a framework which is commonly used to analyze decision-making behavior. In recent years, several theories related to behavioral economics have been proposed to address the limitations of this model and provide solutions to the problems that the EUT cannot explain. While this has significant theoretical importance, there have been few studies that have used real-world dynamics to validate the new findings. This study explores the behavioral patterns explained by a model that includes the narrow framing effect using three products in financial markets. Specifically, the study uses a multivariate GARCH model and asset simulations to validate theoretical predictions and investigates the theoretical impact of the narrow framing on portfolio allocation decisions. The results show that the theory is consistent with the real-world financial markets. This study provides new insights into understanding the changes in financial markets.
Analysis of Regional Differences in the Relationship Between Healthcare Expenditures and Per Capita Disposable Income of Urban Residents in China
Authors: Chen Chuqi
Published: January 2025

Based on the data of urban residents' healthcare expenditure and per capita disposable income in different regions of China, this paper explores the relationship between the two using regression analysis. The results show that per capita disposable income has a significant impact on healthcare expenditure, but the significance level and direction of the impact differ in different regions. In the Eastern and NorthEast regions, per capita disposable income has a significant positive effect on healthcare expenditure, which means that the higher the income level of residents, the higher their healthcare expenditure. In the Central region, the influence of per capita disposable income on healthcare expenditure is not significant, which means that the level of residents' income has less influence on healthcare expenditure in this region. In the Western region, per capita disposable income has a negative effect on healthcare expenditure, but the effect is not significant. This paper provides empirical evidence for understanding the geographic differences in healthcare expenditures of Chinese residents and provides a reference basis for formulating regionally differentiated healthcare policies.
Forecasting the Shanghai Composite Index Using the ARIMA Model
Authors: Li Yufei
Published: January 2025

In this study, the ARIMA (AutoRegressive Integrated Moving Average) model will be used to forecast future daily closing prices of the Shanghai Composite Index from January 1, 2017. Among the models tested ARIMA(4,1,0), ARIMA(4,2,0) and ARIMA(4,1,1), we chose the ARIMA(4,1,1) model to be most appropriate due to having the lowest AIC and BIC values as well as it gives best residual variance based on this accuracies. The model was accurate in capturing historical trends of the Shanghai Composite Index and made sensible short-term forecasts. While the model worked well on historical data, its forecast was at odds with how the Shanghai Composite Index has dived lately in real life. The deviation is due to external economic conditions, market sentiment and the models inability to cope with non-linear market dynamics. To overcome these hindrances, additional investigations should aim to accommodate for exogenous variables, enable non-linear models such as GARCH or update the model in real time to better capture market underlying financial markets. The present study mostly contributes to the literature on financial forecasting as well as ARIMA models also in Chinese stock market.
Solution of Package Auctions in Centralized Clearinghouses
Authors: Gao Ming
Published: January 2025

Package auctions, a mechanism for resource allocation, allow bidders to submit offers on combinations of goods, capturing the intrinsic synergies between items. These auctions play a pivotal role in centralized clearinghouses, particularly within sectors characterized by complex transactions, such as financial markets and logistics. However, the implementation of package auctions presents significant challenges, including issues of efficiency, fairness, and the prevalence of strategic bidding behaviors that can undermine market integrity. This report meticulously examines the winner determination problem (WDP) inherent in package auctions, characterized by its combinatorial complexity and NP-hard classification, which complicates the timely and accurate evaluation of bids. Furthermore, it addresses the strategic maneuvers employed by participants, such as bid shading and collusion, which exacerbate concerns surrounding resource allocation fairness. To tackle these multifaceted challenges, this report proposes innovative solutions, including advanced algorithmic approaches, the design of incentive-compatible mechanisms, the adoption of dynamic auction formats, and the integration of blockchain technology for enhanced transparency. By implementing these strategies, stakeholders can significantly improve the efficiency and effectiveness of centralized clearinghouses, fostering a more equitable and trustworthy environment for all participants and ultimately enhancing market performance across diverse sectors. They are suggested investing in the development of machine learning models and heuristic-based approaches to make the WDP more computationally tractable in large-scale package auctions.
Examination of Problems and Solutions of Chinese Stock Market
Authors: Ge Sheng
Published: January 2025

In the past few decades, the Chinese economy has developed rapidly, and in this process, the Chinese stock market has experienced significant growth over the last several decades but also exhibits many puzzles around its performance. This study identifies problems of the Chinese stock market, analyzes the causes and impacts, and proposes solutions. The findings suggest that three prevailing problems are excessive policy intervention, the nature of emerging stock markets, and surge growth of listed companies with declining quality. These issues together lead to systematic underperformance in the stock market. To remediate the problems, this study further proposes a series of solutions include promoting policy transparency, improving stock market maturity, and imposing more stringent controls on IPO and continued listing requirements. Together, the solutions should improve long-term stability and performance of the Chinese stock market. This study provides a certain reference for a deeper understanding of changes in the Chinese stock market and making accurate investment decisions.
Vietnam V30 Closing Price Forecast Based on ARIMA and ETS
Authors: Zhang Hongyu
Published: January 2025

Stock price forecasting is a key subject in the financial field. Accurate stock price simulations are crucial for investors to make decisions about when to buy or sell stocks for profit. Under the current environment of global economic fluctuations, it is particularly urgent to develop and implement an effective stock price forecasting model. In this study, the VN30 composite index of Vietnam from 2016 to 2023 was selected as the research object, and the ARIMA model and ETS model were used to predict the index. The results show that the ARIMA model outperforms the ETS model in forecasting accuracy, which is reflected in its lower root-mean-square error (RMSE) values. This indicates that the ARIMA model can provide a more accurate prediction of the VN30 index in Vietnam. This study compares ARIMA and ETS models for predicting Vietnam's VN30 index closing prices. It advances financial market research, offering valuable insights for investors, policymakers, and analysts. By enhancing prediction accuracy, it supports informed decision-making, market transparency, and policy formulation, while also providing guidance for model selection and optimization in future studies.
Financial Performance and Global Market Competitiveness of ByteDance
Authors: Wang Runjia
Published: January 2025

ByteDance, one of the worlds leading technology companies, has experienced rapid financial growth, driven primarily by its flagship products TikTok and Douyin. This study examines ByteDances financial performance from 2020 to 2023, focusing on revenue growth, profitability, cash flow, and key financial ratios. ByteDance's revenue surged from $34 billion in 2020 to an estimated $85-$90 billion in 2023, demonstrating a compounded annual growth rate (CAGR) of approximately 30%. Despite facing challenges in profitability due to heavy investments, the company has made strides towards achieving a break-even point by 2023. Strong liquidity and manageable leverage ratios further reinforce ByteDance's financial stability. In addition to its financial analysis, this study also evaluates ByteDances global market competitiveness and the company's diversification into new sectors like e-commerce, gaming, and enterprise software. ByteDances strategic expansion across North America, Europe, and Asia-Pacific has positioned it as a strong competitor in global markets. This analysis underscores ByteDance's remarkable ability to sustain high growth rates, adapt to regulatory challenges, and diversify its revenue streams, positioning it as a leading global technology company.
Supply Chain Management and Optimisation for Online Shopping Platforms
Authors: Hu Yiwei , Zhai Yujia
Published: January 2025

Online shopping has become an integral part of modern daily life and has made important contributions to the development of the retail industry. In China, it has made a great contribution to economic growth and progress. However, with the influx of more and more manufacturers into the market, the industry is becoming more and more competitive. As a result, some consumers have suffered the impact of inferior products, and this vicious competitive situation is not what the market wants to see. Not only that, the supply chain also faces many problems such as information asymmetry and inventory overhang. To change this situation, the management and optimization of the supply chain is crucial. This paper aims to deeply study the supply chain of online shopping platforms, analyze it from multiple dimensions, propose corresponding optimization strategies, and provide references for research and practice in related fields based on the publication standards of academic papers.
Analysis of the Path to Improving the Integration and Allocation Efficiency of Hotel Supply Chain Resources
Authors: Lu Jinwen
Published: January 2025

In today's highly competitive market environment, the rapid development of information technology and the rising expectations of customers are profoundly affecting all walks of life, especially the hotel management industry. Competition between hotels has largely transformed into competition between supply chains. However, there are many challenges and problems in hotel supply chain management. Improving the resource integration capability and allocation efficiency of the hotel supply chain becomes a key issue that hotel companies need to sort out urgently. The main purpose of this paper is to probe how to innovate the hotel supply chain management model by citing big data analysis technology. Specifically, this paper aims to build a supply chain database information system through data analysis and real-time monitoring to help hotels achieve efficient supply chain management. On this basis,this paper will analyze in depth about the future development trend of hotel supply chain management, to provide useful reference and inspiration for the sustainable development of the hotel industry.
Research on Whether Influencer Coffee Shops Could Operate as Chains
Authors: Yoshiyama Rie
Published: January 2025

In recent years, influencer-driven coffee shops have become a prominent trend in the food and beverage industry. The trend involves brands capitalizing on the growing influence of social media platforms. The different establishments are not only selling coffee but also creating a lifestyle brand that appeals to the millennial and Gen Z markets. The convergence of influencer marketing and caf culture has significantly reshaped consumer behavior, leading to the rapid expansion of these niche businesses. This study examines the business models of influencer-driven coffee shops, which have gained significant traction through their innovative concepts, curated ambiance, and strategic use of social media marketing. The research aims to identify the critical factors contributing to the success of these establishments in a highly competitive industry, with an emphasis on their strategies to attract and retain a dedicated customer base. Through a SWOT analysis, the study assesses the strengths, weaknesses, opportunities, and threats that influence their operations. Key strengths include strong brand equity and adaptability to trends, while weaknesses are tied to challenges in scalability and operational efficiency. Opportunities for expansion lie in franchising and international market entry, whereas threats stem from intense competition and economic volatility. The paper concludes with strategic recommendations for fostering sustainable growth and addressing the complexities of scaling influencer-driven coffee shops into larger chains.
Research on Green Logistics and Pathable Path--Taking SF Express as an Example
Authors: Liu Xiaoxuan
Published: January 2025

With the gradual enhancement of global environmental awareness, the logistics industry as an important part of modern economic activities, its operation has a serious impact on the green logistics came into being. This paper takes SF Express as an example, and studies in depth its practice cases and possible paths in green logistics. The results show that SF Express has effectively reduced carbon emissions and improved logistics efficiency by promoting the application of green packaging, upgrading warehousing and transportation technology, and creating a series of initiatives such as a green low-carbon industrial park. In addition, SF Express also actively advocates the theory of green consumption and encourages consumers to participate in environmental protection actions by generating "carbon points" and other incentives through quantifying the effect of carbon reduction. SF Express's green logistics strategy is a reflection of its commitment to environmental protection and provides a green path for other logistics companies to follow. This study has important theoretical and practical significance for promoting green logistics.
Research on the Psychological Impact of Black Myth: Wukong on Chinese High School Students
Authors: Wang Luozihang
Published: January 2025

This research investigates the psychological impact of Black Myth: Wukong on Chinese high school students, emphasizing its visual allure, plot design, and cultural relevance. As China's first AAA game, Black Myth: Wukong reimagines the classic tale of Journey to the West, blending traditional Chinese mythology with cutting-edge graphics and modern gameplay techniques to create a deeply immersive experience. The study reveals that students are particularly drawn to the games breathtaking visual effects, intricate storytelling, and strong connection to Chinese culture. These aspects not only evoke emotional engagement but also shape their gaming preferences, influencing both their entertainment choices and purchasing behaviors. Moreover, the game's cultural significance fosters a sense of pride and connection to Chinese heritage among young players, offering them a unique opportunity to engage with their cultural identity in a contemporary medium. This demonstrates the games substantial psychological and cultural influence, highlighting the potential for video games to bridge the gap between traditional narratives and modern technology while resonating deeply with younger audiences.