As a business league, there are a lot of business in the NBA, and the most hotly debated one is the salary of NBA players. The difference between one player’s salary and another might be like a chasm, even though those players are in the same league. In this paper, we selected over 100 players who play in the NBA league and separated them into two parts by their salaries and performance. We collected different datasets for those players, both on-court and off-court, to find out which factor is highly related to the salary. We aim to help NBA teams and players find the right salary for each one of them. The result of our research is surprising. We found out that factors like age, points per game, and field goal percentage are not quite related to the salary the players get paid, but the real plus-minus and the followers on social media are highly related to the player’s salary.

This paper studies the application of data analysis in the field of customer segmentation and personalization. With the advent of the era of big data, enterprises and organizations have rich data resources that contain important information about customer behavior, preferences, and purchasing habits. Through data analytics, companies can better understand customer needs and provide personalized products and services, thereby improving customer satisfaction and loyalty. This study aims to explore the application of data analytics in the field of customer segmentation and personalization, and provides some common data analysis methods. Data analysis methods include probabilistic methods and Bayesian methods, among others. Through case studies, the application of data analysis in the field of e-commerce is explained. The research results show that data analytics has important value and potential applications in customer segmentation and personalized marketing. However, data analysis still faces some challenges and limitations in practice, including data security and quality issues. Future research can continue to explore methods and techniques for data analysis, solve problems such as data privacy and security, and apply data analysis in more fields.

This study explored those relationship between the mean population, unemployment rate, population growth rate, Gross Domestic product(GDP) per head and the ratio of elderly population within 6 countries from 2010 to 2015, highlighting the vital role of older workers (as measured by labor force participation of older people) in the national economy. A statistic table below illustrates the relationship between those factors and the degree of the influence with the topic. The result shows that the positive association between GDP per head and the elderly, same with the strong relationship with in the population and the elderly. Elderly population has a positive association with unemployment rate as well, but inversely proportional to the population growth rate. This indicates that the marginal impact of elderly population aging on economic growth depends on the size of population. Within different countries, the indicators are different as well. The range of countries are involved in both developed economies and developing economies, considering the population size and the economic situation, taking those representative sample to investigate the economic growth and the elderly population.

This study will explore the impact of the registration system on the stock market after China changed from the approval system to the registration system. Under the approval system, the government monopolizes the right to review stock listings in the approval system. Therefore, this situation not only easily creates the government's monopoly power but may also lead to companies over-packaging IPO application materials to increase the possibility of passing the review. This will cause the government to spend too much time and energy conducting substantive studies of corporate application materials, reducing work efficiency. Therefore, the registration system will be officially implemented in March 2023. The proposed research will investigate the issuance and distribution of new shares, changes in the price-earnings ratio, and changes in the latest lottery rate and yield, as well as the changes in the hairstyle system and how it performed after listing (industry, valuation, and average growth rate) to conduct a comprehensive analysis. Thus, the existing research results are used to propose the impact of the registration system on the Chinese stock market.

This paper introduces non-experts to the process of using predictive analytics models to solve real-world classification and prediction problems. There are two types of models: decision trees and regression models. This article summarizes the previous understanding and application of predictive models and consumer behavior, and also introduces the better use of predictive analysis models, including the accuracy and efficiency of each model. Predictive analytics models are widely used in our lives. Anyone interested in either business or medical science can learn this technology to better explore different fields. The results of this paper suggest that people can further innovate such models, so as to make the use of methods simpler and more efficient.

The Federal Reserve's consecutive interest rate hikes led to a decline in the prices of US Treasuries and mortgage-backed securities (MBS), which comprised a significant portion of Silicon Valley Bank (SVB)'s asset portfolio. As a result, SVB experienced substantial floating losses, exceeding its owner's equity, creating immense pressure on its assets and liabilities. The analysis also highlights the simple deposit and asset structures of SVB, with a high proportion of demand deposits and a significant allocation to bonds. The aggressive interest rate hikes by the Federal Reserve, coupled with financing difficulties for startups, accelerated deposit consumption and intensified debt pressure for SVB. Furthermore, the article reveals the low coverage rate of deposit insurance, particularly at SVB, where only 7% of deposits are insured. This adds to the vulnerability of SVB and its depositors. In conclusion, this article examines SVB's balance sheet and interest rate risk exposure, identifies shortcomings in the management supervision system, and provides three reflections on the financial event.

Using cross-sectional data in the 2018 wave of CHARLS, we use a simple OLS approach to explore the effect of public health insurance on the mental health of middle-aged and elderly people. After analysing the overall mental health condition among people over 45 ,We find that there is a positive and significant correlation between public health insurance coverage and improved mental health outcomes. Specifically, males benefit more from public health insurance than females; people with agricultural hukou have less desired effect than people with non-agricultural hukou; the impacts on the working group are more significant than the none-working group. According to our findings, we recommend Chinese government consolidate public health insurance schemes and expand the coverage of public health insurance. Additionally, efforts to reduce income inequality and put more attention on agricultural groups are recommended to improve overall mental health outcomes in China.

In this paper, we focus on China's power sector to investigate ways to improve emissions reductions in the context of global warming and rising carbon emissions. This paper reviews the current state of adapted carbon emission reduction policies in China's power industry and assesses the potential effectiveness of two mechanisms, carbon taxation, and carbon trading, in achieving substantial emissions reductions. China's power sector is a major contributor to global carbon emissions, and the paper explores the balance between short-term carbon tax policies and long-term carbon trading strategies aimed at promoting an early peak in carbon emissions as well as carbon neutrality within the country. This research finds that the carbon tax can have positive impacts in the short term, whereas carbon trading exhibits higher efficiency in the long term. The paper addresses this by proposing a combination of the two mechanisms to achieve effective emissions reductions in the power industry, supporting China's goal of achieving carbon neutrality by the time of 2060. Finally, we explore the feasibility and benefits of implementing a carbon tax, highlighting its suitability for near-term implementation in the power industry. We conclude that a combination of carbon taxes and carbon trading can make a significant contribution to China's carbon peak and carbon neutrality targets.

Stocks is one of the most popular financial tools around the world, However, it is essential to determine which stock to buy and the moment we buy in and sell out, only catch up with the proper opportunity, then we can make fortune from the stock market. So how can we find out those stocks which has great potential to grow in the future? Our study focuses on the leading stocks effect, which refers to in a specific industry, when some stocks in that industry have reached their price limit, which we call leading stocks, and in the following trading days, the stocks from the same industry will be affected by leading stocks and have a potential growth. In that case, if we can find out the leading stock in a specific industry and monitor it growth every day, then base on correlation coefficient, we can determine which stock to buy in and make profit via this strategy.

In the current era of digitization, networking, and intelligence, realizing the importance of transportation infrastructure alongside internet connectivity and urban development is crucial. This article focuses on Tencent's efforts in smart transportation construction, aiming to understand its unique advantages in traffic service development compared to other companies. Additionally, the study explores the practical application of CIM technology in Tencent's transportation domain, facilitating the intelligent evolution of the transportation sector. By examining Tencent's strategies, technical capabilities, and comprehensive planning, we can gain a better understanding of their competitive edge in the field of traffic service development. Overall, this research aims to comprehensively understand Tencent's smart transportation initiatives, highlighting their advantages in traffic service development, and showcasing the transformative power of CIM technology in driving intelligent transportation solutions.