With the high-quality development of the socio-economic landscape and under the support of national policies, the internet industry has rapidly emerged. In the era of the internet, the development potential and prospects of listed companies in the internet sector are closely related to the overall trend of societal development. The equity structure of a company is the cornerstone of corporate governance and thus affects the company's operational performance. Therefore, this paper conducts an empirical analysis to explore the relationship between the equity structure and corporate performance of listed companies in the internet sector from two dimensions: the nature of equity and the concentration of equity, in hopes of providing references for the sound development of listed companies in the internet industry.

With the continuous development of digital technology, the digital economy represented by big data, blockchain and other technologies is rising and becoming one of the important means of national economic development, which has had a significant impact on various industries, including the cultural and tourism industry. The integrated development of digital economy and tourism industry is an inevitable trend, and it is also a necessary path to achieve high-quality development of tourism industry today. The two industries promote each other and develop together. The "digital cultural tourism" produced by the integration of the two industries has also shown great potential in the growth of tourism economy, and has become one of the keys to the sustainable development of tourism. The digital platforms of the tourism industry in various countries are also constantly improving and have achieved many results. However, at the same time, there are still some problems in the development of digital tourism. To address these issues and promote the sustainable development of the tourism industry, relevant departments should take timely measures to further promote the digital development of the cultural and tourism industry.

In the wave of digitalization where “smart manufacturing” has become a mainstream trend, there are immense growth opportunities for small and medium-sized enterprises (SMEs) in the manufacturing industry. However, given the characteristics of “small, weak, and scattered” nature of SMEs, digital transformation still faces many obstacles and challenges from a professional, investment, and practical implementation perspective. There are many difficulties in practice. This paper proposes routes and strategies for SMEs to undergo digital transformation from the perspectives of talent cultivation structure, industry differences, policy formulation during implementation, data security issues, and further improvement of relevant laws and regulations. It is suggested that enterprises should formulate and implement more comprehensive and long-term digital strategic plans based on their own actual situations. Governments should also focus on supporting SMEs’ digital transformation in various aspects such as talent cultivation, policy support, laws, and regulations. Together, we should promote technological innovation and talent cultivation to lay a solid foundation for successful transformation.

As a matter of fact, the outbreak of the global phenomenon of large-scale infectious disease in early 2020 (i.e., Covid-19) has brought great impact to the global economic market. This study will investigate LV stock prices during Covid-19 based on linear regression, random forest and XGBoost models. As one of the most severely affected industries, this study selects the most representative and socially influential brand Louis Vuitton as investigation target. Different machine learning models have been used in stock price prediction at the beginning of the epidemic outbreak, combining the eigenvalues of the market panic index and the epidemic related situation when the time series is close to a random walk. To evaluate the models, MSE and R-squared error are used to compare the degree of fit of the model. According to the analysis, the stock price prediction models will have better performance on the basis of considering the market sentiment and the epidemic situation.

Under the background of rural revitalization strategy, small towns featuring "old-age care" have emerged. However, the development of retirement towns in our country,China,started late, and the current situation of assimilation is more serious. It is a very important issue to solve.Through comparative analysis of the characteristics of Wuzhen Yayuan and Hogeweyk Town in the Netherlands, the paper explains the feasibility of the pilot of the Dutch Hogeweyk model in Wuzhen Yayuan, discusses the reference significance brought by the successful experience of Hogeweyk town to Wuzhen Yayuan, and provides the world view and methodology for the development of domestic elderly care town industry. With the high-quality development of China's economy, the circular development model of Hogeweyk should be the development trend of the domestic elderly care town industry.

This paper discusses the problems of the traditional carbon emissions trading mechanism, such as failing to effectively incorporate carbon sinks into the carbon market and failing to adequately incentivise the economic and ecological development of cities, and proposes a new urban carbon neutral trading system to solve these problems. The new urban carbon neutral trading system is based on the city as a unit, and by fully integrating carbon sinks into the trading system, it adopts the market mechanism to regulate the balance between carbon emissions and carbon sinks, so as to realise the coordinated development of the urban economy and the green environment. In addition, this study develops a comprehensive evaluation index system for urban carbon neutrality, and uses big data and intelligent analysis techniques to improve the accuracy and real-time performance of urban carbon management. These innovations not only help strengthen urban environmental management, but also promote urban economic transformation and provide theoretical support for sustainable regional economic growth.

Given the proliferation of data, personalized marketing and recommendation algorithms have become essential components of digital platform marketing. The paper examines the terrain of customized marketing and recommendation systems in the digital age, specifically concentrating on TikTok. The study utilizes a literature review method to clarify the core principles and mechanisms that form the basis of TikTok's recommendation algorithms. The importance of this research is in identifying the effects of tailored marketing methods on user engagement and satisfaction. The study explores how TikTok combines content-based and collaborative filtering methods, shedding light on the issues presented by content similarity and the platform's unique solutions. The methodological framework includes the analysis of data such as user engagement, click-through rates, and feedback channels to assess the efficacy of tailored content. This study offers valuable insights into improving recommendation algorithms, tackling ethical issues, and adjusting to changing user preferences.

This paper addresses the problem of allocating 30 unclaimed items to researchers in a fair manner. Five definitions of fairness are derived, considering philosophical, social, and economic aspects. A quantitative evaluation system is established to measure fairness. The allocation is then evaluated using this system. Foundational models, based on zero-one integer linear programming, are developed for each definition. Social interactions between researchers are incorporated into the models, including competition, collaboration, and an auction model. The second section introduces the concept of item relationships, as the value of items can be enhanced when certain items are possessed together. Matrices are used to represent these relationships, making the model more applicable to real-world situations. Sensitivity analysis is conducted to assess the accuracy of each model. The coding implements linear programming and analysis, presenting the results in various visual forms. After refining the model, distributions are calculated using different models and compared. The model is then applied to distribute items among five researchers, and multiple fairness assessments are conducted based on different definitions. The results indicate that, out of four definitions (sixteen in total), two are fair, one is relatively fair, and one is unfair. In conclusion, this paper utilizes linear programming to evaluate fairness in allocation scenarios. The model is refined with adjustments such as mutual interactions, auctions, item interdependencies, and relationships. It provides a comprehensive assessment of fairness and offers practical insights for decision-makers when addressing allocation issues, not only for this particular problem but also for similar situations in society.

in contemporary times, the global economy has witnessed increased interconnectivity. This also means that in the context of the global economy, China is more susceptible to the influence of external factors. In recent years, the COVID-19, which has spread widely around the world, has severely impacted the development of China's real economy with its high infectivity and uncertainty. At the same time, due to the geopolitical impact of the Russia-Ukraine conflict, China's major imports of fertilizers from Russia and cereals from Ukraine have been weakened. Finding ways to cope with the weakening of the economy has become a top priority in line with the development trend. The study suggests that top priority is to increase the diversity of food production and increase the diversification of national food reserves. At the same time, it is necessary to strengthen the country's strategic energy reserves to reduce external dependence and prevent future problems. Externally, China are supposed to strive to build a global economic community, strengthen international cooperation, and be able to "learn from the enemy and learn from the enemy".

An In-depth Analysis of KFC's Customized Marketing Strategy in the Chinese Market and its Significance for International Business Expansion. KFC, an eminent player in the global restaurant sector, has made a substantial and influential footprint in China's vast consumer market. The primary aim of this research is to conduct a meticulous examination of KFC's tailored marketing strategy employed within the intricate landscape of the Chinese market. This investigation delves into the intricacies of how KFC has adapted its diverse product offerings to cater specifically to local preferences, implemented culturally resonant marketing campaigns, and devised strategic distribution channels that effectively penetrate the unique characteristics of the Chinese market. By meticulously scrutinizing KFC's market positioning and strategies in China, this comprehensive analysis underscores the pivotal role of carrying out exhaustive market research and crafting contextually appropriate marketing plans. The findings offer actionable insights and serve as instructive case studies for other multinational enterprises seeking to establish a foothold or expand their presence in the highly competitive and rapidly evolving Chinese market. Thus, this study contributes to the broader discourse on international marketing strategy, highlighting the importance of localization and strategic adaptability in achieving sustainable business success across diverse markets.