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.

The trend towards younger ages in early childhood education has become one of the new trends in children's education in China. Based on Heckman's Curve theory, this paper analyzes the intrinsic relationship between the trend towards younger ages in early education and Heckman's Curve, as well as their impact on the early education industry in China's economically developed regions. From the perspective of the Heckman Curve, families in economically developed areas are increasingly valuing early education, and the trend towards younger ages is a real-world confirmation of Heckman's Curve. The study finds that the early education industry is facing the dual challenges of market structure adjustment and consumer upgrading. In such a market environment, early education brands need to continually adjust their educational models and pricing strategies to better meet market demands and enhance brand influence and competitiveness. With increasing market competition and diverse consumer demands, early education brands should strengthen the development of teaching content, improve teaching quality and service, focus on brand marketing and market promotion, continuously improve customer satisfaction and loyalty, and achieve sustainable development and long-term success. Only through constant innovation and optimization can they remain competitive in a fierce market, winning trust and support.

In today's society, with the rapid development of the economy and the rapid development of science and technology, China's post-00s young people are growing up in an era of material wealth and information explosion. As a unique social group, their consumption behavior and concept have aroused widespread concern in the society. Based on the survey data of 300 post-00s college students, this study aims to deeply explore the main reasons affecting the over-consumption phenomenon of Chinese post-00s young people, in order to provide scientific reference for the formulation of marketing strategies and the sustainable development of economy. This study will adopt the quantitative research method. A questionnaire was published on Weibo to conduct variance analysis on 300 randomly selected post-2000 college students, including their basic information, monthly income and consumption amount, consumption items and consumption concepts. The results of the study show that over-consumption is common among the post-00s college students interviewed. Behind this kind of consumption behavior, it is mainly influenced by the change of social and economic environment, personal growth and educational background, as well as the change of culture and value concept. In view of the above situation, this study proposes to establish a comprehensive consumption education system to guide the post-00s young people to form a healthy consumption concept.

In recent years, Fluctuations in the stock market has become one of the hotspots in the field of finance. As one of the indicators reflecting the stock market situation in the United States, the volatility of the NASDAQ Industrial Index has attracted academic attention. This study uses time series modeling techniques to analyze NDX100 data representing the NASDAQ 100 index to gain insight into market trends and make informed predictions. Using historical price and volume data, the authors built robust models using statistical tools, time series models, and machine learning algorithms. The analysis included autocorrelation and stationary testing, and the ARIMA model was selected. The results show that there are clear autocorrelations and patterns in the data, indicating market inefficiency. This research contributes to understanding market dynamics and highlights the importance of data-driven analytics in financial decision making. Future research could focus on refining the model to improve prediction accuracy.

Short videos have emerged as a crucial marketing tool for numerous firms to captivate consumers. This study aims to explore the influence of short video marketing on consumers' purchase intention. This paper initially examines previous studies and explores the current comprehension and theoretical structure of short video marketing's impact on customers' purchase intention. Through the examination of past research findings, we can gain a more comprehensive understanding of the function and impact of short video marketing in current research analysis to collect and analyze consumers' perspectives and purchasing intentions regarding short video marketing. This study examines the influence of short video marketing on consumers' desire to purchase by analyzing the collected data. The analysis results will provide empirical evidence on the impact of short video marketing, enhancing the comprehension of the role of short video marketing in consumers' purchase decision-making.

This paper aims to improve the accuracy of credit risk assessment by optimising the traditional random forest model through the sparrow search algorithm. The study used Pearson correlation analysis to explore the extent of association between customer indicators and loan delinquency. The results show that income, homeownership status, and years of employment in the organisation are positively associated with non-delinquency, while age, loan purpose, amount, interest rate, percentage of income, length of credit history, and approval status are negatively associated with loan delinquency. The model achieved 99.87% accuracy in the training set after 15 iterations. The confusion matrix showed 20,021 customers were successfully predicted with only 26 prediction errors. The test set accuracy was 82.55% with 7092 customers successfully predicted and 1499 prediction errors. In summary, the study achieved significant results in credit risk assessment and provided financial institutions with a more accurate basis for decision-making.

In this era of rapid Internet development, competition among brands is becoming increasingly fierce, offering consumers a wide variety of choices and making their decision-making process complex and hesitant. Against this backdrop, brand loyalty plays an important role in a company's marketing and development. As an emerging marketing model, social marketing strategies, with their unique interactivity and speed of dissemination, enable brands to establish and maintain relationships with consumers based on target audiences and product characteristics. This paper will explore the impact of social marketing strategies on brand loyalty and reveal the regular factors involved through research methods such as literature review, observation, and qualitative analysis. The conclusion of the study is that proper use of the right social marketing methods can improve customer loyalty to the brand, and the emphasis on product quality is as important as marketing methods.

This study compares the evolution of economic structures in China's Hong Kong and Singapore, and explores the differences in development paths between the two under similar backgrounds. Although Hong Kong has transformed into a diversified free port, there are still potential shortcomings compared to Singapore, a free trade port. This study analyzes the transition of industrial structures and the reasons behind them from the perspective of new structural economics, and examines the impact of government macroeconomic regulation. By comparing the actions and economic performance of the two governments, this paper aims to explore how Hong Kong can adjust its development philosophy in response to challenges and seize opportunities to consolidate its position as an international financial center.

In recent years, China's coffee market has been in a state of fierce competition, and in addition to brands such as Starbucks, which have long occupied a large market share, some new brands are also actively exploring their own paths of development. Among them, Tims Hortons China ("Tims China"), as a coffee brand from Canada, whose entry into China's coffee market really started in 2019, but according to the "2023 China's Urban Coffee Development Report," Tims China has, in just four years, already become the No. 3 coffee shop chain brand in China. The rapidity of its development path has caught the attention of many. In this paper, we will explore how Tims China, as a foreign coffee brand, has been able to position itself in the fiercely competitive Chinese coffee market through a strategy of scale and differentiation, and has been able to grow and expand quickly. By summarizing Tims' development strategy, we can provide references and lessons for the development of the business.

China's A-share stock market has long been influenced by the banking sector, which holds a significant market capitalization. However, much of the current market research is macro-focused, which can result in a lack of correlation with individual stocks. Thus, this paper will begin with individual stocks and utilize the autoregressive integrated moving average (ARIMA) forecasting model to statistically predict their expected value. Additionally, it will analyze the errors of individual stocks and various statistical indices, and ultimately relate them to the fluctuations and patterns in the banking sector. Through these analysis in individual stock behavior, this paper will provide insight into seeking the volatility and movements of individual stocks and exploring the correlation between market sentiment and individual stocks, particularly in relation to the banking sector. By understanding these trends and correlations, it is possible to predict stock movements, analyze stock fluctuations, and analyze market behavior. This information can be valuable to individuals and companies working in the stock market.

This paper systematically studies the profound impact of blockchain technology and cryptocurrencies on the financial sector, and deeply analyzes the transformation potential they bring to the traditional financial system through decentralized, secure and transparent transaction models. This study uses the comprehensive data set provided by the Kaggle platform to build a hybrid analysis framework integrating longitudinal data analysis and advanced prediction technologies, focusing on the dynamics of the cryptocurrency market between 2017 and 2021. By using ARIMA modeling technology, this article explores market trends, participant behavior, and volatility, understands the challenges and opportunities that cryptocurrencies bring, and then provides valuable insights. The findings of this study highlight the importance of the regulatory framework in risk management and maintaining financial stability, while also highlight the potential of blockchain technology to drive financial innovation and reshape monetary policy. This study has important practical significance for the financial sector to effectively utilize blockchain technology.