bluuebunny/crossref_metadata_2025 huggingface dataset:
Mathematical models of SARS
Authors: Liu Liyuan
Published: November 2023

The COVID-19 pandemic ignited renewed efforts in quantitative analysis of the impact of pathogens on human health. The mathematical models were critical in understanding the outbreaks for future preventive and reactive approaches to similar outbreaks. This paper intends to explore and provide an understanding of the SARS-CoV-2 infection process, especially its kinetics. Additionally, the paper aims to provide an overview of the immune systems response to infection, especially the immune systems response to infected cells. This paper relates the symptoms of influenza to the observed symptoms of COVID-19, a disease caused by the coronavirus. The research method employed in this study involves the utilization of differential equations and computational simulations to model infection dynamics. This assumption provides the basis for the majority of the models. The paper also highlights some of the benefits of modelling SARS-CoV-2 and makes recommendations for future studies. Mathematical models provide insights into the dynamics of SARS-CoV-2 infection, aiding in the development of more effective preventive and therapeutic strategies. Further research should explore the integration of real-world data into models to enhance their accuracy.
Review on greedy algorithm
Authors: Wang Yizhun
Published: November 2023

The greedy algorithm is a commonly used algorithm design idea that can provide efficient solutions to many practical problems. This paper aims to review and summarize the basic ideas, characteristics and application fields of greedy algorithms, and discuss their advantages and limitations. Firstly, the basic concepts of greedy algorithms are introduced, including the greedy selection properties and optimal substructures. Then, some classic greedy algorithms such as the backpack problem, the activity selection problem, and the minimum spanning tree problem are introduced, and the concept of time complexity is introduced. Next, the application of greedy algorithms in practical problems, such as scheduling problems, network routing, and graph generation, will be discussed. Finally, the advantages of the greedy algorithm and the limitation of the inability to obtain the global optimal solution will be evaluated, and the improvement direction combined with other algorithms will be proposed.
Explore the Relationship Between Consumer Satisfaction and Consumer Loyalty Based on Four Industries
Authors: Xiao Boxiang , Kong Dezhi , Huang Xinyue , Cao Yanlu , Wang Yunting
Published: November 2023

In recent years, with the continuous development of customer relationship management, the two indicators of consumer satisfaction and consumer loyalty are often regarded as the criteria for measuring the success of customer relationship management, but at the same time whether these two indicators are applicable to the market competition environment is often controversial, this article will use the questionnaire survey method to explore the relationship between consumer satisfaction and consumer loyalty in the catering industry in the Macao Special Administrative Region, and use the case summary method to explore the other three industries in different market environments. It also summarizes the factors that contribute to this situation and also tries to provide more suggestions for improvement for practitioners.
The Effectiveness of Luckin Coffee Fission Marketing Based on Marketing Mix Theory
Authors: Liu Shuyao , Sima Tianyu , Zou Wuyou
Published: November 2023

Fission marketing is a special kind of marketing that is based on the old ways of marketing and is used to get more customers by splitting the terminal market. Luckin Coffee is one of the successful users of the fission marketing model. This study aimed to explore the advantages and disadvantages of Luckin s coffee marketing model as well as its impact on consumers. This paper further develops the factors in the marketing mix theory, uses the SWOT analysis method in the model analysis, and comprehensively discusses the advantages and disadvantages of the Luckin Coffee marketing model. This study concluded that Luckin Coffee has obtained a large number of customers through relationship marketing, price promotion, and other means, but customer loyalty is insufficient, brand understanding is inadequate, and the capital flow has many drawbacks. The overall marketing model has advantages and disadvantages, which is one of the typical cases of fission marketing. More opportunities and threats to Luckin s marketing model will also be discussed in the following section.
Analyzing the Importance of Building Positive Brand Image
Authors: Ma Xuexi , Zheng Shaoling , Zhou Yi
Published: November 2023

After getting a lot of praise for being a sales champion, Perfect Diary's reputation went downhill because of a number of problems with the brand itself. On the other hand, there are not many articles that discuss how to improve this issue and construct a positive image for the business. This paper addressed this subject in more detail. Using an examination of marketing mix theory and a SWOT analysis, the purpose of this paper was to investigate how Perfect Diary creates a favorable image for its brand. According to the findings of the study, Perfect Diary's brand image will suffer if the company maintains its low-price approach for an extended period of time, does not pay attention to place expansion, and engages in excessive promotion. Nonetheless, consumers will be drawn to the brand due to the packaging and other characteristics of its products, which will have a beneficial effect on the brand's image. As a result, in order to create a favorable public perception of their brand, Perfect Diary needs to implement the four pillars of the marketing mix theory.
Comparison of Decision Tree Regression with Linear Regression Based on Prediction of Apple Stock Price
Authors: Li Zongze
Published: November 2023

Machine learning has been increasingly used in stock price prediction with outstanding success. Decision tree regression models and linear regression models are both important models for predicting stock prices. The paper use decision tree regression and linear regression models to predict the opening price, closing price, high price and low price of Apple's stock price data respectively. The prediction effects of the two models are evaluated by the indicators of goodness of fit, mean square error, root mean square error and mean absolute error, and the prediction effects of the two models are compared. This experimental concludes that the decision tree regression model has better and more advantageous prediction results compared to the linear regression model. This study has guiding significance for machine learning in predicting stock prices when choosing a basic model or a combination of models for prediction.
Using Machine Learning Methods to Predict Tesla Stock
Authors: Dai Silong
Published: November 2023

Electric vehicles are now a common mode of transportation due to the aggressive promotion of new energy. Tesla currently has the largest market share among all brands, as well as its techniques and patents may ensure the benefits of future development. And also, Elon Musk is a powerful and ambitious businessman who can steer a technological company toward a brighter future. Yet, due to some uncontrollable factors like Covid-19, disaster incidents, technical staff resignations, etc., might influence the prospects of Tesla stock. So, in this study, machine learning techniques will be primarily employed to forecast Tesla stock prices' trajectory over the next 30 days. The two primary methods used to forecast and evaluate accuracy to determine which model is more appropriate are linear regression and random forest. Before the model is trained, all of the stock data is divided into a training side and a test side. According to the research, linear regression model performs better in predicting the direction of Tesla stock than a random forest model. Based on the search results, it can be said that machine learning methods are likely to unearth patterns and insights that humans havent seen before and can be used to make accurate and unmistakable stock predictions.
Using Machine Learning Models to Predict the Uber Stock
Authors: Gao Jingyu
Published: November 2023

This paper aims to describe how to use machine learning models to predict the situation changing of stocks. This paper will use linear regression and random forest model to predict the Uber stocks stock's future closing price and probability of rise and fall. This paper firstly collected stock related information from Kaggle. The data of Uber stocks are from May 10, 2019 to March 24, 2022. The closing price and the future closing price are divided by taking 80% as the training set and 20% as the proportion of the test set. Then setting some technical indicators to analyze the accuracy and deviation of the prediction, such as root mean square error (RMSE), mean deviation error (MBE) and R-square. In future research, these methods could be used to apply machine learning models in stock forecasting, as well as other more accurate methods such as radio frequency technology and neural networks.
Reflections on the Development of the Street Stall Economy in China
Authors: Liu Yushan
Published: November 2023

Affected by the COVID-19 epidemic, economic development is under downward pressure. revitalizing the economy plays a unique role in easing unemployment and stabilizing society. The article first focuses on the reasons and current situation of the Chinese stall economy, then discusses the problems and solutions in the long-term development with the proposal that more specific time and space management, as well as digital technology, should be added to street vending to adapt to the future urban construction and social development. This helps to find a sustainable developing way for street business.
A Study on Parents' Childrenswear Consumption Mechanisms from the Perspective of Interactive Ritual
Authors: Ma Chenfei
Published: November 2023

Consumption is often influenced by the intermediary role of parents; however, the mechanism behind this influence remains unclear. Therefore, this study aims to explore the decision-making model of children's wear consumption based on the interactive ritual theory. Grounded research was conducted using data from semi-structured interviews with 24 parents. The findings of this study indicate that the decision-making process of parents regarding children's wear consumption can be considered an interactive ritual. The key elements that initiate this ritual include the characteristics of decision makers and users, the inherent attributes of the product, and social factors. Moreover, the interplay between perceived value and brand identity emerges as the central dynamic of this ritual, while the outcomes of the ritual manifest as purchase intention, customer satisfaction, and customer loyalty. Finally, the analysis of the dynamic process of children's apparel consumption is discussed, providing suggestions for the future focus of kids' garment enterprises, and outlining directions for future research.
Navigating the AI Revolution: Job Replacements and New Opportunities in the Labor Market
Authors: Wang Jiashuo
Published: November 2023

This article investigates the relationship between AI and the labor market, with a specific focus on job replacements and new opportunities. It examines the impact of AI on various sectors such as technology, law, medicine, finance, and creativity. AI has revolutionized work by automating repetitive tasks and, consequently, displacing certain job roles. However, it has also generated new avenues that demand a combination of technical expertise and human skills. To thrive in this evolving landscape, individuals and organizations must adapt to the changing nature of work and harness AI's potential for innovation and productivity. While embracing AI-driven advancements, it is crucial to uphold human values and ethics. The article emphasizes the need for a harmonious association between humans and AI in the labor market. By leveraging the unique strengths of both, individuals and organizations can drive efficiency, creativity, and productivity. This entails cultivating agility and adaptability to navigate the transformative impact of AI. Organizations must proactively integrate AI as a tool to enhance productivity and create new opportunities while ensuring that the human element remains integral to decision-making and problem-solving processes.
A Review of Stock Price Prediction Based on LSTM and TCN Methods
Authors: Zheng Ze
Published: November 2023

In financial analysis, stock price prediction is a difficult and important problem that has received a lot of attention from researchers and practitioners in recent years. The application of machine learning and artificial intelligence algorithms to stock price forecasting has demonstrated significant potential for increasing forecasting accuracy. Long momentary memory (LSTM) and transient convolutional networks (TCN) are two famous profound learning calculations that have been generally utilized for stock cost expectation. The most recent approaches to stock price prediction using LSTM and TCN methods are reviewed in this paper. We highlight the most recent research trends in this field and talk about these methods' benefits and drawbacks. Additionally, we discuss potential future research directions in this field. The survey is expected to give a knowledge into the present status of exploration on stock value forecast and guide specialists and experts in working on the exactness of expectation.
Impact of COVID-19 on China's A-share Real Estate Market
Authors: Teng Feiyang , Zhang Li , Zhao Yang
Published: November 2023

With the outbreak of the 2019 epidemic, many industries have been affected to a greater or lesser extent. The real estate market is huge and involves many industries, so it is particularly important to analyze how it will be affected by the epidemic This study analyses the profitability and financial position of three large real estate companies, Vanke A, Jindi Group and China Merchants Shekou, by using a case-based analysis of their revenue and profit growth rates, return on net assets, gross sales margin, net profit margin and debt servicing capacity. companies. Based on the comparison of the three red lines and the impact of the epidemic on the development of the three companies before and after the epidemic, corresponding recommendations and decisions are given. This paper will help to analyze and predict how the property market will fluctuate in the aftermath of the epidemic and what measures should be taken in aftermath.
Venture Capital Funding and Early-Stage Startup Performance
Authors: Wang Yaoxuan
Published: November 2023

This paper explores the significance of team composition, market valuation, and deal structure in venture capital (VC) investments. The research highlights that the success of a startup is heavily influenced by the skill, knowledge, and dedication of the founding team. Additionally, market valuation plays a crucial role in determining the expected return on investment for venture capitalists. Various valuation methods, such as the discounted cash flow model and the Berkus method, are discussed to aid in the assessment of a startup's future prospects. Furthermore, the paper emphasizes the importance of a solid transaction structure, which includes equity, voting rights, and clear responsibilities for both parties involved. A strong transaction structure aligns the objectives of venture capitalists and startups, encourages rapid development, and reduces conflicts. Case studies of successful VC investments, such as Airbnb and Uber, are presented to illustrate how team composition, market valuation, and deal structure contribute to their growth and success. Overall, this research provides valuable insights into the factors that influence VC investments and their implications for startup success, investment performance, and economic development.
An Empirical Analysis of Forecasting Bitcoin and Gold Price Using ARIMA Model
Authors: Kwok Tsz Lap
Published: November 2023

The autoregressive integrated moving average (ARIMA) model is a widely used technique for capturing past dependencies and trends in order to generate future predictions. This study presents a comparative analysis of the ARIMA models forecasting capabilities as applied to gold and Bitcoin prices. The methodology employed consists of obtaining historical price data, implementing machine learning techniques, fitting the ARIMA model, then validating its predictive ability using multiple error metrics. Our results indicated that the optimal ARIMA parameters for Bitcoin and gold are different, which emphasizes their different price behaviors. Additionally, the study examined implications for policy, including issues such as prices for CPUs and GPUs, the role of market dynamics, as well as the possibility for price manipulation, which is of special relevance for cryptocurrencies that exist outside the mainstream. The study also suggests potential directions for future research, such as applying advanced machine-learning techniques and adopting cross-validation. This research offers important insights regarding Bitcoin and gold price dynamics and demonstrates the applicability of the ARIMA model for financial forecasting while demonstrating the necessity of further investigation into more refined predictive models.
The Impact of Commercial Banks' Interest Rate Policies on SME Innovation under Digital Inclusive Finance
Authors: Wang Yining
Published: November 2023

Digital inclusive finance, as a new financial service model, promotes small and medium-sized enterprise innovation by providing easier financing through various technological means. The government's regulatory policies and commercial banks' interest rate policies have an impact on their financing services, thus affecting SME innovation. In addition, relevant studies are less concerned with the role of commercial banks' interest rates in SME innovation. In order to examine the effects of commercial banks' lending rates, government regulation, and SMEs' innovation benefits and costs on the evolutionary game, we build a three-party evolutionary game model of commercial banks, government, and small and medium-sized enterprises in a digital inclusive finance environment. It is found that commercial banks and the government agree on an appropriate interest rate policy to help SMEs innovate while protecting their interests. To control SME innovation, the government must play a significant role in the regulation of digital inclusive finance; commercial banks should lower the loan interest rate ceiling to support SME innovation; and SMEs should strengthen themselves to obtain high-quality loans so that they can better innovate.
Googles Stock Price in Covid-19: An Exploration of Machine Learning Techniques for Prediction
Authors: Wang Zijian
Published: November 2023

The stock market, as well as the global financial and public health systems, were significantly impacted by the abrupt onset of the COVID-19 pandemic. The complicated dynamics caused by the epidemic made it even more difficult to predict stock values. Forecasts from conventional models were less accurate because they have trouble reflecting the psychological characteristics of investors. To increase the accuracy of stock price predictions, researchers investigated machine learning methods like hybrid models and Artificial Neural Networks. In terms of forecasting stock values during crises, there is still a study void. This study study investigates the applicability of decision trees, random forests, and Long Short Term Memory (LSTM) models for analyzing stock market dynamics in the context of an epidemic. Through comparative analysis, it was determined that the LSTM model outperformed the alternative methods, thus establishing its superiority in predictive accuracy. The implications of these findings extend to investors and regulatory bodies, shedding light on the behavior of stock markets during periods of adversity. Subsequent research endeavors should focus on exploring innovative techniques that can further enhance the precision of stock market predictions.
Prediction and Feature Importance Analysis for Diamond Price Based on Machine Learning Models
Authors: Zhang Hairong
Published: November 2023

The advent of Artificial Intelligence (AI) has facilitated the prediction of diamond prices through data analysis techniques. By incorporating relevant data, various models were constructed to examine the interrelationships between different factors and subsequently forecast diamond prices, which were then subjected to rigorous verification. The findings revealed that the XGBoost model demonstrated superior performance, exhibiting a high coefficient of determination (R square) and a low Root Mean Squared Error (RMSE). Furthermore, employing the feature importance method elucidated the significance of specific factors in determining diamond prices. Notably, carat weight emerged as the most influential factor, followed by width, clarity, and color. Conversely, other factors exhibited a lesser impact on price determination. These findings provide valuable insights for stakeholders in the diamond industry, enabling them to prioritize the most influential factors when assessing and forecasting diamond prices. Future research endeavors could explore additional data sources and advanced AI techniques to further enhance the accuracy and comprehensiveness of diamond price predictions.
The Evolution of Generally Accepted Accounting Principles: A Focused Look into the International Financial Reporting Standards
Authors: Zhang Hongchi
Published: November 2023

Financial reporting has long been an essential lens through which shareholders assess the managements operation of companies and through which external users such as potential investors evaluate how companies are structured and perform financially for economic decision-making. For this reason, the truth and fairness of financial statements is emphasized in financial accounting to reflect the economic substance over the legal form. As cross-border trades and investments grew by leaps and bounds after the World War II, a call for a globally uniform and consistent set of accounting standards thrived in full swing. Hence, the genesis of IAS and subsequently IFRS for better quality, comparability, understandability, and transparency of financial statements. Over recent years, the trend in accounting harmonization with gradual convergence between IFRS and US GAAP has also become prominent. However, accounting standards are never perfect in presenting economic reality upon their inception. Blatant financial scandals play an indispensable role in shaping accounting standards for improvements. This paper takes a focused look into IFRS to examine how the generally accepted accounting principles evolve in reaction to scandals and loopholes criticized, with a detailed analysis of the standards for leases and revenue recognition. A generic discussion on the difference and convergence between IFRS and US GAAP concludes this paper.
Examining the Market Potential and Feasiblity of Chipotle Mexican Grill in the Chinese Market
Authors: Ko Jou-hsuan
Published: November 2023

Many U.S. quick-service restaurant chains have expanded their business into the Chinese market, The development in the fast food industry has provided people with a more conventional diet. However, people start to prefer a more healthy diet as the awareness and recognition of personal health rises in recent years. This research focuses on Chipotle Mexican Grills business potential to develop in the Chinese market and how to incorporate its business with several Chinese e-commerce platforms. The research has looked through literature reviews in the field of marketing strategies and management, global restaurant chains, healthy diets, and the Chinese market. The qualitative research design has helped the research to collect deeper insight from Chipotles American market and then employ it to the Chinese market. The results of the research recommended Chipotle enter the Chinese market as a direct sale store, allowing better control over service and quality. The results of the research indicated a good opportunity for Chipotle to collaborate with the Chinese e-commerce platform to make more profitability and more brand recognition. The results of the research also showed great feasibility for Chipotle to enter the Chinese market since there are enormous potential customers in the marketplace.
Analyze of Amazons Big Acquisition in the Industry of Retail: Whole Foods Market
Authors: Jiang Qilin
Published: November 2023

There are different types of analyze about the Amazons acquisition of Whole Foods Market. This report gives an introduction of the two companies, Amzon is one of the bigeest E-commerce platforms in USA, and Whole Foods Market is a supermarket focused on the Natural organic food. Then this report analyzed the reason of the acquisition: Amazon would like to enter into the physical retailing and Whole Foods Market faced the financial problems . After that, this report analyzed the influences of the acquisition to Amazon using the SWOT model and PESTEL model in order to give a comprehensive picture of this picture. Considering that the acquisition happpend in 2017, and it might be uncomprehensive to give analyze or comment for it at earlier time, and it is more persuasive to give an analyze after 6 years. Based on the history data, this acquistiiton formed the win-win for the two companies, but there are still some recommends. For example, they should balance the online selling and the offline selling, solve the conflict between the high quality of the Whole Foods Market and the low cost of the Amazon, they should continue focus on how to be separated from the strong competitors.
Analysis of Marketing Strategy of Mixue Ice Cream & Tea on Social Media Platforms
Authors: Liu Yicong , Wang Shiyu , Zhang Yu
Published: November 2023

With the improvement of people's quality of life, in addition to focusing on food, people are also fonder of various drinks. Since its establishment in 1997, Mixue Ice Cream & Tea has been continuously developing and growing. By 2023, the number of Chinese stores in Mixue Ice Cream & Tea has exceeded 10000, covering 31 provinces (cities, autonomous regions), and is actively exploring overseas markets, with a large number of loyal consumers nationwide. The brand expanded rapidly in the sinking market with the business model of low price and franchising and became the fastest dark horse in the tea industry. This study provides a brief overview of the market development status of Mixue Ice Cream & Tea and studies its marketing strategies based on the 4P theory. It analyzes the products, prices, place, promotion strategies, and the reasons for their effectiveness in Mixue Ice Cream & Tea, and proposes suggestions for future sustainable development. This study found that the marketing strategy of Mixue Ice Cream & Tea is effective, attracting a large number of consumers for Mixue Ice Cream & Tea. Its marketing strategy can be summarized as follows: positioning the brand with genuine materials and high quality and affordable prices, and using a combination of online and offline marketing strategies to meet the consumer needs of the target market with safe and reassuring products.
A Study on the Development of Chinese Agriculture under the US-China Tariff War and Countermeasures
Authors: Zhu Yuxuan
Published: November 2023

Since the trade friction between China and the US in 2018, the US has maintained a surplus in agricultural trade between China and the US, and China will also impose agricultural tariffs in response to the US sanctions. the list of tariff increases announced by China and the US in 2018 covers all types of agricultural products traded between China and the US, meaning that agricultural trade becomes an important part of the game between the two countries. Based on the list and the analysis of previous literature, this paper focuses on the development of Chinese agriculture and tries to provide countermeasures. The study finds that the US-China tariff war has both positive and negative impacts on China's agricultural development, bringing benefits to some enterprises and pushing back the development of new foreign trade markets. It has caused losses to relevant stakeholders, increased price volatility of agricultural products, and is detrimental to the development of agricultural foreign trade and the restructuring of agriculture. In the future, the development of Chinese agriculture can be promoted through the promotion of market stability, the continuous optimization of the agricultural structure and the improvement of modernization.
The Main Issues and Countermeasures Facing the Global Economy after the Relaxation of Epidemic Control Policies
Authors: Yue Sijia
Published: November 2023

Due to the COVID-19 epidemic, many countries have taken a number of epidemic prevention and control measures, which have had a huge impact on the global economy. This paper studies the major issues facing the global economy after the relaxation of epidemic control policies, such as economic recession, inflation, debt crisis and energy crisis, and countermeasures. In this paper, corresponding countermeasures are proposed to address economic recession, including increasing government spending, reducing taxes, lowering interest rates, and increasing the money supply and to address the inflation, including reducing government spending, increasing taxes, raising interest rates, and reducing the money supply. In response to the debt crisis, corresponding countermeasures have been proposed from the aspects of strengthening government supervision, adjusting government expenditures, tax rates, interest rates, and money supply. In the light of the energy crisis, this paper puts forward corresponding countermeasures from aspects of improving energy utilization efficiency, reducing energy consumption, developing green energy that can replace traditional energy, and strengthening the supervision of the energy market.
Implement of the Marketing Mix Theory in Increasing Customer Satisfaction at Internet-famous Restaurant
Authors: Gu Yiqi
Published: November 2023

Since people like to post photos on social platforms as a way to share them in their daily lives, restaurants have discovered that this can be utilized as a free promotional advertisement. The restaurant began to pay attention to the decoration of the store but also forgot the importance of the product itself. The purpose of this research was to discover how to improve the Internet-famous restaurant's current situation when the satisfaction of consumers shows a downward trend. Taking TASTIEN as an example, the marketing mix theory of the 4Ps and data from other scholars' research were utilized for relevant analysis. The reason for the decline in TASTIEN's product quality was the excessive number of franchised stores. Therefore, TASTIEN should improve the detection of food ingredients and continue to innovate. Whats more, the problem of too many complaints from TATINE customers is due to poor quality of service. In this regard, TASTIEN should invest more time in training employees and improving basic behavioral qualities. Similarly, TASTIEN is not promoted well because it is overly reliant on one platform. It should try to follow the social trend, enter the market as a sponsor, and participate in more social platforms.
Time Series Modeling and Forecasting of US Consumer Price Index Using WTI Crude Oil Price
Authors: Liu Yuxi
Published: November 2023

This study aims to forecast U.S. inflation by using crude oil prices as a key variable. WTI crude oil price and Consumer Price Index Year-over-Year (CPI YoY) data from 2000 to 2022 are extracted to construct a time series model. The empirical analysis relies on Autoregressive Integrated Moving Average (ARIMA) model and regression to formulate forecasts based on historical patterns and error dynamics. The study finds out that compared to the automatically generated ARIMA model, using fitted values of the WTI time series model to predict CPI YoY through a multi-variable model is better. According to the prediction, the CPI YoY forecast for 2023 reveals a decreasing tendency in 2023, implying a slower rate of increase in U.S. inflation. The result provides insights into economic conditions, helps decision-making, and mitigates the potential risks associated with price fluctuations. Overall, the research contributes to a deeper understanding of the dynamics between energy markets and inflationary pressures in the United States.
Tower Semiconductor Acquisition: Advancing Intels Presence in the Global Market
Authors: Lyu Lei
Published: November 2023

With the gradual implementation of the IDM strategy of Intel corporation, Intel moves faster toward its goal of dominating the worldwide foundry services and capacity market by giving it access to one of the most comprehensive portfolios of unique technologies. As a result, acquiring Tower for its specialized technologies and customer-first approach is a necessary step for progression of this strategy. This article aims to illustrate the reasons, analysis, and impact of it. The research unequivocally demonstrates that Intels acquisition of Tower will significantly impact the market competition landscape, technological innovation, and employment opportunities in the industry. This article gives a positive attitude to this acquisition, its a wise and appropriate choice for intel due to technical and military aspects. However, considering towers earnings in recent years have been modest, it could be suggested for leaders to make reasonable arrangements for the allocation of research and development. Facing this competitive race, intel needs to consider the future developing directions.
Research on the Marketing Strategies of Luxury Bag Brands in the Chinese Market
Authors: Chen Zihan
Published: November 2023

In recent years Chinas luxury industry has been developing rapidly, and the market for luxury bag consumption is gradually maturing. The marketing strategy of luxury brands in the Chinese market is relevant to the development status and prospects of the brand and the industry. This paper provides an overview of the current situation of the Chinese luxury market. It analyses luxury brands marketing strategies in the bag category from four perspectives: product strategy, pricing strategy, promotional strategy, and placing strategy. The study identifies brand marketing problems within the Chinese market, including unregulated marketing practices, failed localisation, and ineffective consumer targeting. Based on these issues, the paper provides suggestions for luxury bag brands to strengthen internal management and localisation, as well as to increase the use of technology in order to keep up with the times and meet the diverse needs of consumers. Analysing the marketing strategies of luxury bag brands in the Chinese market can provide a reference for the industry and promote its development.
Revisiting the Anchoring Effect: Summary and Outlook
Authors: Ding Jie
Published: November 2023

The practical application of anchoring effect has been paid much attention in the commercial field. Research in recent decades has shown that the effects of anchoring are very powerful. In different contexts, it can be manifested through a wide range of decision-making tasks in different groups. There are many forms of "anchoring" that influence people's thinking and judgment, such as casual comments from friends, numbers on TV, and fixed opinions about people's skin color, appearance, and clothing may affect your thinking and judgment on a certain issue before you realize it. One of the most common types of "anchoring" in business decisions is based on past events and trends that lead to poor decisions. This paper discusses the anchoring effect in many different fields and tasks under the influence of anchoring, and how the anchoring effect is related, developed, and further influenced. This paper also focuses on the judicial decision and consumer price negotiation to explore the influence of anchoring effect. Finally, we look at the effects of anchoring from these two perspectives.
China's Bond Market: The Current Situation, Problems, and Countermeasures
Authors: Zhou Yining
Published: November 2023

It is undeniable that the bond market plays a key role in the social economy as a whole. Economic development and the state of the bond market often reflect the state of the country's financial markets. Bond markets in China have developed rapidly and have a large financing capacity. In recent years, however, the volatility of the bonds in China has gradually increased due to epidemics, policies and funds, etc. The bond market has undergone a drastic adjustment. This paper describes the current bond market situation in China, analyzes the problems, and proposes solutions for the market. The main problems are the credit risks in bond rating and the impact of political risks on bond market. This paper provides advice on credit risk from the perspective of creating a credit environment, improving data quality, and strengthening regulation. This study has a positive impact on China's bond market's development.
Comparative Analysis of the Success and Challenges of Starbucks Marketing Strategies in China
Authors: Qumu Zhiyue
Published: November 2023

Starbucks Corporation is an American coffeehouse chain founded in 1971. It is currently the biggest and one of the most well-known coffeehouse chains in the world, with over 35,000 stores worldwide. China has been ranked the second-biggest market for Starbucks after its home country since its first appearance in 1999. As a foreign brand, Starbucks marketing strategies in the Chinese market have been fundamental to the brands success. This paper analyses how Starbucks Chinas localisation of its product, placing strategies, and digitalisation of its marketing strategies have led the coffeehouse chain to succeed in the market. Then, this paper looks at the challenges Starbucks faces from local and international competitors and challenges arising from economic instability. Finally, the paper also provides recommendations to the company regarding its marketing strategies. It is believed that Starbucks China will need to continue strengthening its efforts to diversify its products, adjust its pricing strategy, and optimise its customer experience to succeed.
US Inflation Analysis and Forecast Based on US-China Trade Perspective
Authors: Zhang Kaichen
Published: November 2023

Since the US initiated the trade war and sought the decoupling of trade between China and the US, the US economic and financial situation has taken a sharp turn and inflation has remained high. So, this article studied the inflation analysis of the United States from the perspective of Sino-US trade and made a forecast. This paper constructs an ARIMAX model to empirically analyze the relationship between US-China trade and US inflation. The study shows that there is a significant positive correlation between China's export price index and the US CPI, which shows that China and the US are important stakeholders of each other. Because the United States is one of the largest economies, its economic development is of great significance to the world economic pattern and affects the whole world. Through the economic and trade cooperation between China and the United States, the inflation rate of the United States will be reduced, and the economic growth of the United States will be promoted.
Research on Carbon Tax in China under Carbon Neutrality
Authors: Zhou Jiajie
Published: November 2023

Carbon neutrality has become one of the main goals of addressing climate change on a global scale. As an economic means in China, a carbon tax can promote the transformation of energy structures and reduce greenhouse gas emissions by imposing a certain fee on carbon dioxide and other greenhouse gas emissions. This paper studies how to carry out the energy transition and realize the sustainable development of the country. This paper establishes a theoretical framework for carbon neutrality, carbon tax policy, and energy transition, and elaborates on the reasons for energy transition, the impact of energy transition on the market, the path to carbon neutrality, and China's carbon tax policy. Evaluate China's energy consumption structure from economic, environmental and policy perspectives. This article found that the biggest impact on China's energy consumption structure is the industrial growth rate, followed by GDP, and then carbon dioxide emissions. In order to achieve the long-term goal of global carbon neutrality, the government needs to introduce relevant policies.
Dior China Cultural Trend Marketing Analysis
Authors: Hou Lin
Published: November 2023

The development history of Dior brand in China market can be traced back to 1980s, when Dior was one of the first international luxury brands to enter the China market. After more than 30 years' efforts, Dior brand has occupied an important position in China market, and according to the characteristics and changes of China market, effective cultural trend marketing strategies have been formulated. This thesis analyzes the cultural trend marketing strategy of Dior brand in Chinese market, and mainly discusses the following aspects: Dior brand's products, prices, channels and promotion strategies, similarities and differences between Dior brand and Chinese traditional culture, Dior brand's attention and adaptation to the young consumer market, and Dior brand's competitive advantage and future vision in Chinese market. The article points out that Dior brand has won the recognition and love of consumers in China by combining Chinese cultural elements, innovating product design, improving service quality, enhancing value expression, and using various media platforms to attract and interact with consumers, and has become the representative of luxury goods industry in China.
The Advantages and Challenges Faced by Business Analytics in the Context of Big Data
Authors: Dong Xiaotian
Published: November 2023

In recent years, with the booming development of big data technology, data acquisition and data analysis have become more convenient and efficient, and business data analysis is gradually being widely used in various industries. This paper analyses how business analytics can seize the opportunities for better development in the era of big data, and also explains the challenges faced by business analytics in the era of big data and provides corresponding solutions. The article finds that big data can help business analytics better predict market trends, optimise marketing strategies, provide visual analysis reports, and detect fraud risks; at the same time, the problems of data quality, data security, data processing speed, and data processing capacity arise; finally, the article puts forward ways to solve these problems from the perspectives of improving the quality of data, improving the level of protection, improving the speed of processing, and improving the capacity of analytics, which provides diversified ideas for people.
Optimizing Operations Management and Business Analytics Strategies under Uncertainty: Dynamic Programming
Authors: Yi Ran
Published: November 2023

Dynamic programming is a method used in mathematics, management science, computer science, economics, and bioinformatics to solve complex problems by decomposing the original problem into relatively simple sub-problems. Dynamic programming is often applicable to problems with overlapping subproblems and optimal substructure properties. This paper employs a comprehensive research approach of literature review, as well as empirical analysis and case studies to investigate the topic and demonstrate the practicality and effectiveness of dynamic programming in solving complex decision-making problems. However, the curse of dimensionality poses challenges when dealing with high-dimensional decision spaces, requiring approximate dynamic programming methods, including reinforcement learning algorithms. Therefore, when dealing with more complex dynamic programming problems, it is also essential to use program construction tools such as Python to help design a program that can optimize the problem. Therefore, in the learning of dynamic programming, in addition to the correct understanding of basic concepts and methods, specific problems must be analyzed and dealt with in detail, models should be built with rich imagination, and solutions should be solved with creative skills.
Elaborating ESG Of TESLA Based on Information
Authors: Zheng Yixuan
Published: November 2023

Sustainable development is now a hot topic in the world. In view of the serious problems in environment, society, financial market and other aspects, international organization, countries and even enterprises around the world have put forward ESG and other sustainable development action plans, so that human beings can develop sustainably. Therefore, the research theme of this paper is Tesla's ESG performance in 2022 The research method of this paper is as follows: Firstly, massive data about Tesla's ESG in 2022 and ESG of other three companies are collected, and then the ESG of Tesla company is analyzed and the ESG form of Tesla company is compared with that of other three typical companies. This paper draws a conclusion on the defects and advantages of Tesla's 2022 ESG and their differences between other companies ESG, which provides valuable reference materials for future scholars studying Tesla ESG and the whole situation of world range companies ESG.
Changes in Early Redemption Rules for Convertible Bonds and an Examination of the Effect of Forced Redemption
Authors: Shuran Ying , Jing Dai
Published: November 2023

In 2022, the Shanghai Stock Exchanges and Shenzhen Stock Exchanges (SSE and SZSE) made a series of amendments to the convertible bond trading rules and self-regulation of listed companies. In addition to this, SSE and SZSE made more detailed requirements on the time and process for listed companies to exercise their rights for convertible bond redemption in advance. By summarizing and analysing the data of convertible bonds listed by the Shanghai Stock Exchanges and Shenzhen Stock Exchanges in China in the past 10 years, this paper introduces the background of the convertible bond market, analyses the characteristics of convertible bonds redeemed early and the impact of early redemption of convertible bonds on listed companies, and explores what kind of forced redemption effect has been produced by the new changes of convertible bond regulations. The paper also explores the implications of the forced redemption effect on investors by considering the changes in the convertible bond market since its inception.
Market Fluctuations and the Crocs' Resurgence
Authors: Peng Yirui
Published: November 2023

This paper delves into the reasons for the decline in sales of Crocs and the reasons for its counterattack. The decline in sales of Crocs was mainly affected by changing fashion trends and consumer preferences, a lack of effective marketing and promotion strategies, and the proliferation of copycat shoes in the market. However, Crocs managed to fight back by focusing on providing a comfortable foot feel, shifting marketing strategies and leveraging the influence of social media, as well as the unique characteristics of Crocs. This reversal not only led to the economic recovery of the shoe industry and workshops but also regained the importance of Crocs in the field of culture and fashion. There are a few suggestions to pay attention to for the future prospects and sustainability of Crocs: First, pay close attention to changes in consumer trends and adjust product design and promotion strategies in time to adapt to changes in market demand. Secondly, pay attention to the safety of Crocs, continuously improve the comfort and quality of products, and ensure consumer satisfaction and trust. Finally, strengthen intellectual property protection, prevent infringement of counterfeit products, and maintain brand image and market share. By proactively addressing these critical issues, Crocs can secure its future growth and continue to succeed in the highly competitive footwear market.