This paper outlines the research perspectives, objectives and methods to explore the ideas and applications of artificial intelligence in optimizing supply chain inbound management. By leveraging AI algorithms for demand forecasting, inventory optimization, and transportation planning, Amazon has improved efficiency, reduced costs, and increased customer satisfaction. The integration of robotic warehousing systems, automated guided vehicles, and shortest path algorithms has revolutionized warehouse operations, enabling faster order fulfillment and resource utilization. Despite challenges such as data security, technological uncertainty, and employee resistance, companies can address these issues through enhanced data protection measures, flexible technology architecture, and promoting collaboration between AI and employees. The future of AI in supply chain management will require continuous adaptation to technological advances, efficient path planning solutions for multiple robots, and cultivating harmonious relationships between AI systems and human workers. Embracing AI-driven innovation offers great potential for optimizing inventory processes, improving operational efficiency, and achieving sustainable growth in the digital age. Through a comprehensive literature review and case study analysis, it aims to provide valuable insights into the role of artificial intelligence in the transformation of supply chain operations.

This study investigates the role of consumer attitudes in shaping brand development within WeChat group buying, a unique social commerce model in China. By applying the Elaboration Likelihood Model (ELM), the research explores how factors like perceived value, social influence, trust, convenience, and entertainment influence consumer attitudes through both peripheral and central processing routes. Using a multi-dimensional survey, the study finds that initial consumer engagement often begins with peripheral cues, such as social influence and price advantages, which later transition to central-route engagement centered on product quality and service satisfaction. This transition fosters brand loyalty and encourages repeat purchasing behavior, highlighting the critical role of social influencers (group leaders) in facilitating these shifts. However, the study’s focus on Chinese consumers presents a limitation in generalizability, with future research suggested to include longitudinal data and cross-cultural comparisons. These findings offer valuable insights for businesses looking to strengthen brand loyalty within social commerce platforms like WeChat.

This paper examines the case of Kowloon Walled City, using it as a practical demonstration of the Austrian School's a priori theoretical framework while refuting the mainstream economic view that government intervention is necessary to supply public goods and maximize welfare. Kowloon Walled City, which existed as an anarchic enclave until its demolition in 1993, offers a compelling example of how a community can meet its collective needs—ranging from property protection to social services and sanitation—without governmental oversight. The residents achieved comprehensive satisfaction through voluntary cooperation, fully exercising their rights to person and property. This analysis contributes to the broader discussion of public goods provision, a fundamental source of government legitimacy, and argues that government intervention often proves less efficient than non-intervention, highlighting the relevance of Austrian economic theory in practical settings.

Logistics is an important part of the national economic system, which plays the function of promoting the circulation of goods between regions and maintaining market balance. In recent years, the rapid development of technological innovation, the complexity of market supply, and the increase of cost (such as vehicle safety and cargo damage) have brought huge impacts and fluctuations to traditional logistics companies that take integration and coordination as their business, and it is urgent to sort out and summarize from the theoretical aspects. Taking a logistics company in Shanghai as an example, this paper summarizes and analyzes the impact of technological innovation (such as new models such as flying wing trailers) on logistics enterprises, discussing and illustrating the role of load factor on the logistics industry. It aims to explore a feasible solution for related enterprises, establish a competitive advantage, seize the opportunity for future development and occupy more market shares.

The purpose of this report is to analyze the impact of VAT sharing reform on the income gap between urban and rural areas in China. The VAT sharing reform, a significant fiscal policy, aims to address fiscal decentralization and revenue distribution. This report highlights the importance of this reform in narrowing the urban-rural income gap, which is crucial for achieving common prosperity. The key issues analyzed include the disparities in income levels, access to public services, and employment opportunities between urban and rural areas. The methodology involves case studies, data analysis, and literature review. The primary findings suggest that while the reform has contributed to revenue redistribution and improved infrastructure in rural areas, it also presents challenges such as fiscal imbalances and inefficiencies. The report offers practical suggestions to enhance the effectiveness of the reform, including targeted revenue redistribution, incentive structures for local governments, and integrated fiscal policies.

This article analyzes the economic crises of South Korea in 1997 and Brazil in 1999, focusing on the two countries' reliance on foreign capital and their recovery policies under the leadership of the International Monetary Fund (IMF). Both countries suffered severe currency devaluation and economic recession due to capital flight. However, with different economic structures and response policies, the recovery paths of the two countries are also very different. South Korea had benefited from an export-led recovery and sweeping financial reforms, while commodity-dependent Brazil faced more challenges. This study provides an important reference for emerging economies dealing with foreign investment dependence and post-crisis recovery issues. This article specifically analyzes key economic indicators such as Foreign Direct Investment (FDI) flows, per capita Gross Domestic Product (GDP), and exchange rate fluctuations during the economic crisis in South Korea and Brazil, and conducts an in-depth comparison of the two countries' policies to respond to the crisis. Finally, this article puts forward specific countermeasures and suggestions such as diversifying the industrial structure, strengthening the independence of monetary policy, and improving public trust to deal with possible financial instability in the future.

In the financial markets, stock price prediction has always been a classic, popular, and challenging research topic. The ability to effectively predict stock movements can allow investors to maximize returns and manage risks, which reinforces the efficiency of capital markets. Furthermore, understanding and improving prediction models contributes to the academic study of market behavior and the development of more robust financial models. However, stock prices are subject to various economic, political, and psychological factors, introducing high uncertainty and making accurate forecasting a complex endeavor. In this research, two forecasting methods will be used to forecast the NASDAQ index. Their prediction result will then be compared. The ARIMA model and the ETS model are the two forecasting models used in this study. The past 10 years (2013-2024) of NASDAQ index (open) will be used as the data for the training set and test set. The goal of this study is to compare and evaluate the accuracy of each model and determine the model that is better suited for financial forecasting. The result shows that the RMSE value of ARIMA model fitting is lower than ETS model fitting. The ARIMA model provides a better predicting result in predicting the NASDAQ index. This paper compares ARIMA and ETS models to provide insights for future investment decisions and show a new perspective on stock price forecasting.

This paper analyses the characteristics of the existing cold chain logistics from the perspective of cold chain inventory, and puts forward the corresponding management optimization ideas in combination with the inventory of a supermarket. Using Activity Based classification, ten kinds of fruits in the inventory are classified, and reasonable management suggestions are put forward to finally achieve the purpose of optimization and improvement. This thesis is divided into five parts, the first part is an introduction which gives the background of cold chain logistics. The second part is the research status, which contains the current status of cold chain inventory management and research status. The third part is the problem analysis, which is an analysis and research on the current status of inventory in supermarkets and identifies several problems. The fourth part is the optimization solutions and suggestions for the problems of inventory in supermarkets respectively. The fifth part is the conclusion and the outlook for the future.

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.

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.