With the rapid development of technology, the digital economy has become one of the main drivers of global economic growth. However, it also brings a series of challenges and opportunities for sustainable development. This paper delves into the impact of the digital economy on sustainable development, analyses the challenges involved, and explores the potential opportunities for sustainable development in the digital economy. Firstly, the author sorts out the definition, scope, and development trend of the digital economy. Then, the application of digital economy in various fields is explored in detail, revealing its potential value in social, economic, and environmental aspects. However, the rise of the digital economy has also brought about a series of environmental, social, and economic challenges, such as e-waste, the digital divide, structural change in employment, and inequality. Meanwhile, this paper highlights the opportunities the digital economy presents for sustainable development, promoting environmental sustainability, social inclusion, and economic innovation. Through innovations in digital technologies, environmental issues are better addressed, socially inclusive growth is achieved, and economic innovation is driven. The article emphasises the positive interaction between the digital economy and sustainable urban development through case studies. It concludes with an outlook on the future trends of the digital economy and recommendations for integrating sustainable development concepts to ensure that the digital economy becomes a powerful enabler of sustainable development. Through comprehensive analyses, this paper aims to provide insightful perspectives on the relationship between the digital economy and sustainable development.

Tesla currently stands among the world's most prominent corporations, especially in the development of new energy sources and the automotive industry. With the company's growth rising, the value of its stock has become a major focus for investors. There are many ways to predict stock prices, but most of them are more subjective and based on personal experience, so the value of the reference is not great and varies from person to person. Therefore, this paper aims to investigate whether it is possible to analyze the price trend of Tesla's stock from the perspective of data through machine learning. The research will examine the stock price of Tesla based on the ARIMA-LSTM combined model prediction method to determine if this method can be applied to predict the stock price trend of Tesla and similar technology companies. Finally, after testing Tesla's stock data in 2019, it can be concluded that the machine learning prediction method based on the ARIMA-LSTM combination model is highly accurate and can be used to predict the future stock price trends of similar companies.

Since the COVID-19 occurs from 2020, global economy has a tremendes shrinking in amount and sphere, which brings business objects uncertain financial turbulence. Hence, corporate cash holdings are a concern by managers and investors as it represents the survival ability of companies. This study investigates information asymmetry and corporate cash holdings during COVID-19 pandemic period. After analyzing on large Chinese lised companies sample, we test two opposing hypotheses. According to free cash flow theory, cash flow declines further as the level of information asymmetry rises. However, considering profound event, companies may increase cash holdings for precautionary motive during a long time. As a result, using the difference-in-difference method, this paper finds a positive relationship between information asymmetry and cash holdings, while COVID-19 hurts cash holdings for Chinese listed companies. The robustness test also gains similar results. Overall, the results may support the agency theory and precautionary motives for holding cash.

since the eighteenth congress, the CPC Central Committee and the State Council issued "on further perfecting the central government scientific research project funds management policy several opinions" and a series of optimization of scientific research funds management policy documents, stimulate scientific research personnel innovation, but the financial reimbursement process and procedures are relatively complex, how to balance the free financial control and the contradiction between strict financial regulation is more and more prominent, increase the communication cost of scientific research personnel and financial personnel. Based on the background of"streamlining administration and delegating power", this paper takes the reimbursement of scientific research funds as the starting point, analyzes the problems of reimbursement of the department, discusses how to strengthen the reimbursement management of colleges and universities from the perspectives of financial personnel and researchers, and puts forward optimization measures, so as to improve the financial operation efficiency of colleges and universities.

The Russia-Ukraine conflict has triggered a global energy crisis, which has brought extensive and profound impacts on China’s energy development. This paper analyzes the impact of the Russia-Ukraine conflict on China’s energy industry, discussing the changes in the international crude oil and natural gas markets, the global energy restructuring, and the acceleration of energy transformation. In response to the energy market volatility that may be brought about by the conflict, the paper proposes strategies for China to cope with it, including diversifying energy supply, strengthening geopolitical risk management, and building an energy community. In addition, the paper analyzes Russia’s position in the international energy market and focuses on the impact of China’s crude oil and natural gas import costs, the stability of the energy supply chain, and Sino-Russian energy cooperation and investment. Finally, the paper emphasizes the importance of accelerating energy green and low-carbon transformation and building energy communities, providing ideas for the sustainable development of China’s energy sector. This paper figures out that China’s energy industry should adopt a more flexible and resilient approach to respond to unforeseen circumstances such as the Russia-Ukraine conflict.

The financial market is the mechanism used to trade financial assets and determine their prices. The market system that is extensive is composed of multiple branches, including the securities market, stock market, fund market, and others. Due to the development of modern economy, financial mathematics has gradually become an important part of the financial market. By combining its own characteristics with modern science and technology, and exploring the securities theory of the financial market, financial institutions can obtain more precise data resources. Financial mathematics uses mathematical thinking and computer advantages to quantify the financial market. Then constructing mathematical models, analyzing the data, and calculating them, which is a significant way to promote the development of the financial market. This paper mainly explores the impact of financial mathematics on the financial market, with the aim of better promoting social development. In this paper, the method of literature analysis is used to investigate the influence and promotion of financial mathematics in the field of modern financial markets. The conclusion shows that financial mathematics is an important part of the promotion of the market and that this new discipline has unlimited potential.

Xiaohongshu, a rising lifestyle-sharing platform, has garnered significant popularity among femal. Despite recent controversies over false traffic, it remains a pivotal influence on femal’s shopping decisions. This study aims to explore why Xiaohongshu continues to be influential in the consumer decisions of femal after false traffic. This paper used a case study to analyze a survey of 200 femal from diverse backgrounds to understand their methods of gathering shopping information and making purchase decisions on social platforms, focusing on Xiaohongshu's unique attributes. First, the study reveals that enhanced, deceptive content on the platform frequently persuades women, suggesting a need for improved information authenticity, consumer education, and self-regulation in advertising. Secondly, digital influencers and trends heavily influence the platform's young audience, highlighting the importance of encouraging influencers to share genuine experiences over mere advertising. Lastly, the natural trust engendered by word of mouth (WOM) and user-generated content (UGC), critical features of Xiaohongshu, underscores the platform's strategy to bolster UGC and WOM credibility. In conclusion, Xiaohongshu plays a crucial role in the shopping decisions of contemporary female consumers, underscoring its significance in the social media landscape.

With the development of technology, the Internet, and big data, all industries have gradually undergone digital transformation. Simultaneously, as transportation demand grows, digital and intelligent solutions have created new development potential for the railroad business. Huawei, a Chinese technolgy company, grasped the chance to enter the railroad sector and pioneered the development of the intelligent railway by combining digital and railroad technologies. This study uses ten pieces of literature and Huawei Intelligent Railway objects to look at how digitalization of the railway affects the environment, society, and government, as well as the effects of ESG theory and the SWOT approach. Finally, the examination of this research leads to the conclusion that Huawei’sbusiness model of digital technology-enabled railway helps the improvement of the environment, society, and government. As a result, it is possible to infer that successful digital technology empowerment benefits global development by promoting the betterment of the environment, society, and government.

With the development of the tobacco industry under the background of the digital economy, more and more tobacco enterprises have begun to pay attention to inventory management and introduce digital technology. The parts inventory management of tobacco enterprises itself has the characteristics of many types of equipment parts and complex management forecasts. Therefore, in the background of the development of the digital economy, reducing inventory costs, reducing inventory overhang, and improving enterprise profitability has become the top priority of tobacco enterprise management. This paper aims to analyze the practical problems of parts inventory management in tobacco enterprises. The main problems include complex inventory management, imperfect inventory monitoring and assessment mechanisms, unscientific traditional inventory forecasting methods, imperfect information construction, and difficulty in guaranteeing the quality of parts. Provide suggestions for improving inventory management ability. Tobacco enterprises should improve the parts inventory management strategy, optimize the parts inventory forecast, strengthen the information construction, improve the quality of the part and establish a sound monitoring and assessment mechanism.

This paper explores the transformative impact of big data technology on cross-border supply chain inventory management. In the era of globalization, supply chains face increased complexities and risks, particularly in cross-border logistics. Challenges include transportation uncertainties, delays due to long-distance transport, infrastructure disparities, and transparency issues. Integrating big data analytics offers a solution to these challenges by enabling predictive analytics for demand forecasting, inventory optimization, and risk management. This study highlights the role of big data in enhancing supply chain transparency, reducing uncertainties, and improving decision-making processes. Examples from JD E-commerce and NongFu Spring demonstrate the practical application of big data in optimizing inventory management and mitigating risks. JD E-commerce employs artificial intelligence and big data analytics for inventory management, leading to reduced turnover days and cost efficiency. NongFu Spring, on the other hand, uses big data for scenario marketing and supply chain optimization. The paper concludes that big data technology not only revolutionizes inventory management but also plays a crucial role in addressing risks in the supply chain, thus leading to more efficient, transparent, and resilient supply chains in the face of globalization challenges.