The fast fashion industry is gradually recovering from the epidemic’s impact, while new retailing will become a new opportunity for fast fashion brands. As a leading fast fashion brand, Zara has a distinctive industrial character. This paper summarizes the current situation of Zara in the Chinese market from the data by using case study analysis, further analyse its strengths and problems, and gives solutions accordingly. It is found that Zara’s hungry marketing, convenient address, and match sales have been effective, but it has also encountered many problems, for example, copyright disputes, non-durable products, environmental damage, timeliness and locality of fashion, and low marketing investment. For these issues, the article suggests piloting pop-ups, co-branding or purchasing copyrights, strengthening regulation and environmental protection, localizing products through delegation and co-creation, and providing a personalized shopping experience. If these approaches prove viable, they could be a significant reference for fast fashion brands in China.

China’s new media has developed rapidly in recent years, and society has entered the era of new media. At the same time, China’s economic level is developing rapidly, and people’s living standards are also greatly improved. The demand for luxury goods is greatly increased. The huge population makes China become the largest consumer of luxury goods. In this context, various luxury brands have different marketing strategies for the China market. As one of the world’s largest luxury goods companies, LVMH is bound to change its marketing strategy for China market. In addition to an overview of the topics and trends covered in the relevant literature, this paper mainly discusses the impact of new media on the luxury industry and how the luxury industry should change in the new media environment. For some academics and marketing managers of luxury brands, this paper can provide some theoretical basis and is of great reference for changing marketing strategies.

In recent years, the scale and number of mergers and acquisitions (M&A) between companies have been steadily increasing, with M&A becoming the primary choice for expanding their businesses. However, M&A between internet companies often involves many uncertainties. This paper first analyzes the operational strategies and merger motivations of Didi Chuxing and Kuaidi Dache (now DiDi and Dida respectively), and then applies the SWOT analysis method to analyze the strengths, weaknesses, opportunities, and threats of this merger event. Finally, the paper summarizes the pros and cons of this merger event and provides recommendations. The research findings of this paper indicate that the merger motivations of this merger event mainly include reducing market competition pressure, achieving resource integration while expanding market share, and seeking more development opportunities. The SWOT analysis shows that the strengths lie in resource integration and internationalization, the weaknesses involve strategic risks, the opportunities can be harnessed through synergy effects, and the threats involve potential negative impacts of monopolies on the market. By formulating the correct strategic theories, enhancing core competitiveness, and effectively utilizing synergy effects, the success rate of corporate mergers and acquisitions can be improved, providing feasible ideas for M&A in China's ride-hailing industry.

With the rapid growth of the gaming sector and advancements in technology, the global gaming market has reached unprecedented heights, capturing the attention of millions worldwide. Simultaneously, the concept of metaverse has become a topic of intense discussion, holding the promise of transforming virtual experiences. This paper study thoroughly examines Microsoft's strategic move to acquire Activision Blizzard, scrutinizing its multifaceted impact from various perspectives. Motivated by the pursuit of synergy effects, market expansion, and preparation for the metaverse, Microsoft aims to harness the potential of Activision Blizzard's intellectual properties and fortify its gaming portfolio, potentially positioning itself ahead of Sony in the fiercely competitive gaming console market. Nevertheless, the integration of diverse corporate cultures and the ever-present specter of antitrust scrutiny pose significant challenges on the horizon. This compelling case study offers invaluable insights into the decision-making processes of major corporations, shedding light on the intricacies of the dynamic gaming industry and the unfolding metaverse landscape. As the gaming realm and technology continue to thrive, this landmark acquisition becomes a pivotal example in understanding and navigating strategic business decisions in the rapidly evolving digital era.

With an increasing number of companies applying ESG-related activities, many researchers have recently focused on what effects could be brought to the firm’s value by the firm ESG performance. Researchers have two main views on this relationship. One view is that the ESG performance and disclosure of nonfinancial reports play an important role in improving a firm’s value and sustainable development. The other view is that ESG performance is not only meaningless for a firm’s value but also harmful to the firm’s value, especially for firms in developing countries. But firms they used for testing the relationship may belong to different industrial fields. So the firms used in this article would belong to the technology, energy, and finance fields To avoid the essential distinctions between different firms that belong to different industrial fields. After analyzing the MSCI EGS ratings history data over the last five years or since records began and the stock prices during the corresponding periods for these three industries respectively, the benefits on a firm’s value brought by the better ESG performance tend to be more obvious in the technology and finance industries than the firms in the energy industries.

The definition of brand equity has been gradually improved, but the existing studies are mostly case studies and unilateral studies, and the studies that integrate and sort out brand equity from multiple perspectives are relatively rare. By reviewing and sorting out the international literature on brand equity, this paper summarizes the definition, components, evaluation methods and prospects of brand equity, in order to promote the better development of corporate brand equity. The article holds that it is very important to use publicity channels effectively to stimulate consumers, establish effective brand association, and enhance brand awareness and recognition to enhance brand value. In addition, brands need to segment the market and strengthen brand trust in a targeted way. And establishing a consistent and effective brand image helps to enhance brand awareness and brand recall, as well as promote brand loyalty. At the same time, for high-equity brands, brand extension and expansion is also particularly important.

Business platforms have now become an indispensable tool in people's lives. Amazon, a household name in e-commerce, has achieved success in markets all over the world, except in China. This paper finds that the main reasons for Amazon China's failure are the intense competition from local e-commerce giants and the cultural and consumer behavioural differences between Chinese and foreign consumers. For Amazon China, Alibaba, Pinduoduo are very challenging competitors. The cultural differences between Chinese and foreign consumers are reflected in the fact that Chinese consumers find it difficult to accept the e-commerce platform's fee-based and slow delivery service, and are unable to use Alipay and WeChat as payment tools. Moreover, the user pages of the Amazon shopping software do not match the aesthetics of Chinese consumers. In addition, the paper makes recommendations on how cross-border e-commerce business in China can be improved and adapted to the Chinese market to address these factors.

Climate change has recently become a critical global concern, and its potential impact on financial markets has attracted significant attention. The study investigates the relationship between rising temperatures and the S&P 500 index, aiming to understand the implications of temperature changes on stock market performance. This research applies the Autoregressive Integrated Moving Average (ARIMA) model to analyze the relationship, using the linear and dynamic regression models to forecast the S&P 500 according to the ARIMA-fitted values of temperature change in the future. The findings from the dynamic regression model indicate that the rising temperature positively impacts the S&P 500, while the linear regression models show no correlation between these two. The study's findings support investors and policymakers in gaining a more comprehensive insight into the relationship and applying it to business practices. Furthermore, the study offers guidance to develop risk mitigation strategies within the financial sector.

Stock market prediction has always been a prevailing topic among investors and researchers. Among numerous market index, the Shanghai Stock Exchange Composite Index (SSE Index) is recognized as one of the most indicative stock indexes in China's A-share market. As it is discovered that the fluctuations of SSE index and exchange rate (USD/CNY) displays highly similar pattern since the subprime mortgage crisis, this study aims to use macro variables (including exchange rate) to predict the SSE index based on ARIMAX model. The data are collected since 2006 and based on which ARIMA (14,1,4) model is generated. Distinct macro variables are added in this ARIMA model respectively and it concludes that the incorporation of exchange rate with certain lags can significantly increase the fitting degree. Cross validations on different lengths of validation sets are implemented, which shows that the model can make accurate forecast in relatively short term. The result manifests increasing accuracy when incorporating certain explanatory regressive factors, which might provide valuable and enlightening information in short term for researchers or investors.

This paper presents a detailed analysis of unemployment rate forecasting, a critical subject for various stakeholders including policymakers, businesses, and individuals. Amid significant economic events such as the global financial crisis and COVID-19 pandemic, the need for precise unemployment forecasts has become crucial. The research utilizes an Autoregressive Integrated Moving Average (ARIMA) model to analyze US unemployment rate data from 2000 to 2023, sourced from the Federal Reserve Economic Data (FRED). The paper identifies seasonality patterns, executes appropriate data transformations, and incorporates the Box-Jenkins methodology for ARIMA model identification. The findings reveal the model's resilience, demonstrating accurate forecasts despite significant disruptions. These insights offer valuable contributions in understanding labor market dynamics, facilitating informed decision-making and strategic planning. The paper highlights the robustness of ARIMA models, and their potential to adapt to rapid changes in the economic landscape, thereby proving invaluable in forecasting unemployment rates.

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.

Virtual items are very popular nowadays, this article will study the skin of Counter Strike-Global Offensive (CS:GO) with an unbiased perspective and official data. A lot of the data comes from the numbers Valve cooperation (VALVE) publishes. In addition, the soaring price of the CS:GO skin market in recent years has already diffraction some of the conclusions, and this article will prove the conjecture about the infinite financial value of virtual goods is correct. Furthermore, CS:GO skin is not subject to the constraints and regulations of the market rules, and the attributes of other virtual items are consistent, and in many ways can be found similarities. Through the official data, the research results are obtained: CS:GO skin profit space is large, but there are unpredictable risks. The article will reflect the financial properties of the entire virtual goods market through the CS:GO skin. This article does not give any advice on financial transactions and accepts no responsibility for any losses.

The British Empire is known for its large territory ranging all the way from the Americas to Oceania, with dozens of colonies that brought the empire great wealth and capacity to industrialize and mass produce. Based on data and information on the amount of British colonial production, this article focuses on calculations and estimations of the total colonial gain of the empire above. By estimating the amount of production in selected significant colonies, and then converting the results into the desired unit of measurement, a calculated value of colonial wealth can be achieved. The resulting values reveal that the British Empire is estimated to have generated more than 35 trillion British pounds, 56 million pounds of tobacco, 54 million tons of sugar, 173 million tons of rubber, 39 million tons of wool, and 26 million Terawatt hours of oil. Through calculations of the total colonial gains of the British Empire, the effect of colonization on the mother country and its influence on the modern world can be more easily and directly seen.

Since August 2022, the British pound exchange rate has continued to decline due to multiple factors such as the global epidemic and the Russia-Ukraine war. Against the background of the cost of living crisis with high inflation, especially the sharp rise in energy costs, the British government issued a new tax cut, namely the mini-budget, but the implementation effect is very poor; Subsequently, the Bank of England adopted successive interest rate hikes in an attempt to stabilize the value of the pound and temper the general situation of inflation. This paper critically evaluates the impact of the fluctuation of the value of sterling on the activities of commercial banks in the financial market and analyzes the reasons, advantages, and disadvantages. Commercial banks can benefit from sterling volatility in several ways, such as generating higher trading revenues, enhancing asset liquidity, attracting more capital inflows and trading opportunities, and increasing equity market capitalization. On the other hand, a similar sterling appreciation could have multiple negative effects on commercial banking operations, including risk management, net profits, policy interest rates, and international competition. For the development prospects of commercial banks, it is recommended that in the context of the overall global economic downturn, timely adjust their operations and strategies to adapt to these changes, to withstand the business risks related to exchange rate fluctuations, such as changes in interest rates, interest spreads, and capital costs.

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.

To improve the efficacy of stock prediction strategies, researching sector rotation is essential. This study addresses the sector rotation problem in the A-share market and proposes an approach that leverages LSTM and random forest models to forecast sector rotation trends. Extensive evaluations are conducted to assess the models' prediction accuracy, comparing different evaluation indicators. The random search algorithm is employed to optimize model parameters, while the adaptive learning rate Adam algorithm is utilized to enhance convergence performance. The final experimental results demonstrate the remarkable accuracy of the LSTM model, achieving an impressive 88% accuracy in predicting sector rotation in the A-share market. Meanwhile, the random forest model achieves an accuracy of 86%. Furthermore, a combination of the bagging algorithm based on LSTM and random forest (LSTM-RF Bagging model) is employed for in-depth research, which exhibits even better performance with an accuracy of approximately 89%. The predictability of A-share market sector rotation is evident, and both LSTM and random forest models, along with new combination, prove to be suitable for forecasting. The findings in this paper serve as a valuable reference for investors, aiding them in making informed decisions regarding sector selection and asset allocation.

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.

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.

Currently, the continuous rise in housing prices in China has brought about social issues regarding housing fairness. Therefore, it is of practical significance to study the influencing factors of China's real estate prices and the effects of these factors. This article first identifies ten variables that have a significant impact on housing prices through analysis, and then conducts empirical analysis separately for the eastern and central-western regions. Based on the correlation and model multicollinearity tests, two corresponding models are established. Subsequently, this article uses a multiple linear regression model for regression and uses a test set to verify the model's effectiveness, conducting quantitative analysis. Combining the analysis results, the factors that have a significant impact on housing prices in the eastern region of China are identified as the sales area of commercial housing, rental prices, and unemployment rates. In the central-western region, the factors with a significant impact on housing prices are disposable income and real estate development costs. Based on these conclusions, this article proposes relevant policy suggestions, which are expected to provide a basis for differentiated macro-control policies by the government.

Cross-market risk conduction is an important risk source in the global investment market. In recent years, the global market risk linkage cause-d by major public health emergencies has attracted much attention. This paper selects the COVID-19 epidemic as an example, and uses the shipping market as a representative indicator of the global economy to try to analyze the complete path of the epidemic impact from the global economy to the Chinese stock market. From the perspective of behavioral finance, it analyzes the role of investor sentiment in this risk linkage. The empirical results show that the transmission of epidemic risk between Chinese stock markets deviates from the global economic fluctuations but has regularity, and the momentum effect brought by investors ' overconfidence and overreaction makes the stock market reaction short-term and volatility amplification. Risk aversion and limited attention make the market volatility caused by the deterioration of the epidemic greater than the mitigation. This paper creatively conducts a full-path study on the transmission of epidemic risk between macro-economic and stock markets, and uses behavioral finance theory to quantitatively verify the impact of investor sentiment, which provides a theoretical basis for cross-market risk transmission research.