This thesis will focus on the study of BAIC BJEV Back-Door Listing Motivation and Performance Analysis. Through reading the relevant literature, this paper understands the basic model. This thesis adopts the case study method, aiming to reveal the reasons and internal logic behind the back-door listing of BAIC New Energy. Including but not limited to market demand, consumer expectations, financial situation, etc., in order to understand the strategic choice of the enterprise more deeply. In addition, this thesis adopts the graphical method and indicator analysis to quantitatively evaluate BAIC New Energy Co., Ltd. after the back-door listing, and analyzes the effectiveness of the back-door listing method for BAIC New Energy Co. by comparing the past financial status, key business indicators and other factors, and then deduces the good and bad impacts of the back-door listing on the enterprise, which will provide lessons learned and feasibility analyses for the similar decision-making.

This study utilizes a variety of models testing for robustness, such as the PSM-DID approach, by analyzing market data from publicly traded companies over the period 2006 to 2022, while omitting any instances suspected of manipulating research and development activities. It delves into how the policy for certifying high-technology companies in China influences their innovative processes. Findings indicate that certification as a high-technology business significantly fosters innovation among Chinese firms, notably in the realm of inventing new patents. Such certification enhances company innovation both directly and indirectly. It is observed that, in comparison to major state-owned corporations, smaller private firms and those driven by shareholder incentives gain more advantages from being recognized as high-tech enterprises. This investigation adds to the academic discourse by offering an empirical analysis of China's policies aimed at bolstering innovation, thereby enabling a deeper insight into the factors propelling company innovation and the complex dynamics between government incentive programs and corporate innovative activities.

With the gradual development of low-carbon and environmental actions, the implementation of policies such as green credit has been effective. Based on the dataset of A-share listed companies spanning from 2009 to 2023, this paper focuses on the relationship between green credit policies and the debt scale of heavily polluting enterprises, and explores the role of ESG performance in this relationship through the evaluation of intermediary effects. To facilitate identification, we used the parallel trend test, dividing the data before and after the policy publication into two groups. This is more conducive to observing the effects and effects of policies. The findings indicate a clear suppression of the debt scale among heavily polluting enterprises following the enactment of relevant policies in 2012, highlighting the discernible impact of these policies. Finally, the enlightenment and suggestions are put forward based on the conclusion.

In the context of increasingly fierce competition in the automotive market, car dealerships are shifting from a "product-oriented" approach to a "customer-oriented" one. This paper establishes a customer profile tagging system based on car purchasing behaviors and customer attributes, and constructs a customer profile model through cluster analysis. However, traditional machine learning algorithms face limitations such as insufficient data, single sources, and incomplete tags. Additionally, data cannot be directly shared due to data security concerns. Therefore, this paper applies a FederatedKMeans algorithm, which combines federated learning and K-means clustering, to construct profiles. The superiority of this algorithm in terms of performance is demonstrated through empirical tests, and it is used for cluster analysis to categorize customers into different groups, providing corresponding marketing strategies.

As global climate change continues to intensify, carbon emission trading has garnered increasing attention from nations worldwide as an effective market-based mechanism. As the world's largest carbon emitter, China's establishment and development of a carbon emission quota futures market holds immense significance. In order to actively tackle climate change, promote the achievement of peak carbon neutrality in cities, enhance the control and management of greenhouse gas emissions, harmonize the regulation of pollutant emissions, and standardize carbon emission trading and associated activities, Beijing has formulated and issued specific Administrative Measures on Carbon Emission Trading. These measures are grounded in the Interim Regulations on the Administration of Carbon Emission Trading (Decree No. 775 of The State Council of the People's Republic of China), as well as the Decision of the Standing Committee of the Municipal People's Congress on the Pilot Work of Carbon Emission Trading in Beijing, which operates under the strict condition of controlling total carbon emissions. Additionally, these measures adhere to other pertinent laws and regulations and will take effect from May 1, 2024. Through these comprehensive measures, Beijing aims to further strengthen its commitment to sustainable development and mitigate the impact of climate change.

In recent years, the market for freshly made tea has boomed, attracting many emerging brands such as MIXUE Ice Cream & Tea (MIXUE). In the face of fierce competition and the challenge of homogeneous products, MIXUE needs to continuously optimize its marketing strategies to maintain its competitive advantages. This study takes MIXUE as the research object, adopts the SWOT model, aims to analyze the success of its marketing strategy, and puts forward optimization suggestions. Through the SWOT model analysis, the potential problems with the current marketing strategies of MIXUE are revealed. At present, the brand maintains a certain low-end market advantage in the freshly made tea market, but faces the disadvantages of fierce homogeneous competition and a relatively single market model. Its products are seriously homogeneous, food hygiene and safety problems are frequent, there is a lack of innovation in publicity methods, the low-price strategy affects the long-term profitability of the stores, and it lacks reasonable operation of its own online channels. These problems make MIXUE face development obstacles and risks. At the same time, this paper proposes improvement strategies in terms of enhancing innovation, strengthening food safety management, improving personnel management and after-sales service, optimizing cost performance, broadening price range, and increasing brand promotion channels, so as to enhance marketing power and competitiveness. It provides new ideas for improving its marketing power and competitiveness, and also has reference significance for the development of the entire tea industry.

Housing policy be identified that the prescriptive measures established by the government for addressing housing problems and interventions nowadays. By formulating and implementing housing policies tailored to the country's specific characteristics, these policies serve to guide the development of the housing industry, manage the housing resources, and ensure a fair resolution of the housing problem. However, research and professional analysis of housing demand within a particular city is a challenging task. Our report explains Hong Kong's housing allocation mechanism from a market design perspective by analyzing arguments and historical digital evidence from relevant and reliable literature. And then we have modeled and evaluated the mechanisms of Hong Kong public rental housing allocation. We conclude that although the mechanism itself can be improved, but the housing issues in Hong Kong is more about other external factors. So, this report provides a more detailed view of Hong Kong's public housing policy compared with previous papers.

With the aging of the population and the improvement of organ transportation technology, the demand of organs such as kidney, cornea, liver, and heart are increasing dramatically. Until February 29, 2024, there are in total 51196 volunteers who have done their donation, 157204 organs have successfully transported to the patients in need. However, under the great increase in the demand of organ donation, the supply of organ is still way above the amount of demand. In China, only 0.05% of the population have registered of being a volunteer in organ donation. The great shortage becomes more significant after China banned the use of organs from executed prisoners as a source of organ donation since 2015. Under the circumstances of having shortage of organ donation, it becomes more important for a country to have clear incentive and allocation mechanisms in organ donation. In this essay, the result would be carried out through comparing the incentive mechanisms of organ donation in Spain, the USA and China, find out the advantages of mechanisms in Spain and the USA, the potential issues of organ donation system in China. As a result, find valid approaches for the improvements of Chinese organ donation system.

Electric vehicles are attracting increasing attention worldwide due to concerns about climate change and sustainability. However, global adoption of electric vehicles is still relatively low. This paper will investigate and analyze the public awareness of new energy vehicles in the United States and China, compare the differences in public awareness between the two countries, analyze the reasons for the differences, and suggest suggestions to improve public awareness of new energy vehicles. The study finds that, on the whole, the Chinese public's awareness of new energy vehicles is higher than that of the American public. The main reasons for the difference include the influence of cultural background and values, the role of media publicity and education, and the differences in policy and market environment. To improve public awareness of new energy vehicles, the United States needs to strengthen publicity and education, and improve policies and infrastructure, while China needs to increase media publicity, improve policy guidance, and improve product and service quality.

This paper delves into the strategic integration of Transaction Processing Systems (TPS) within the digital transformation initiatives of the retail sector, focusing on enhancing business performance through advanced business modelling, information system modelling, and leveraging data visualization for business intelligence. We examine strategic frameworks such as the Value Discipline Model and the Agile methodology to align TPS integration with business goals, emphasizing the importance of agility and continuous improvement. The impact of TPS on retail operations is quantitatively assessed through key performance indicators, revealing significant enhancements in transaction processing times, inventory management, and financial reporting accuracy. Challenges including legacy system integration, data security, and skill gaps are addressed through practical solutions like APIs, encryption methods, and comprehensive training programs. Furthermore, we explore the architectural design principles of TPS, emphasizing scalability, resilience, and adaptability, alongside effective data integration and management strategies that ensure data consistency and accessibility. Performance evaluation methodologies are also discussed, employing mathematical models for predicting system behavior and optimizing throughput, latency, and reliability. Case studies highlight the transformative power of data visualization tools in retail, showcasing their impact on operational efficiency and decision-making. This comprehensive analysis underscores the pivotal role of TPS in driving digital transformation in the retail industry, offering a roadmap for organizations aiming to enhance their competitive edge in the digital era.

While WeChat is one of the top instant messaging software in China in terms of daily active user and active user, Tencent’s other messaging program, QQ was fading into obscurity. However, Tencent still retains the normal operation of QQ, even though it is not as welcomed as it was first launched. Therefore, this paper analyzes the operation of QQ through functions, user groups, positive competition and revenue generating. In addition, it provides explanations of Tencent’s product management (seven principles for product creation) and innovation strategies (imitative strategy, collaborative innovation, independent innovation, and diversification) by literature review and theoretical analysis. Tencent’s choice to retain QQ is related to the company’s strategy, which can be reflected in two aspects: product management and innovation. In the process of development, companies need to retain the prior market and innovate by learning from the failures of the current base. In addition, the current users and products of the enterprise provide a wide range of market research basis, which is one of the enterprise’s resources and can provide enterprises with better product innovation and management of the platform.

The emergence of artificial intelligence (AI), blockchain, big data analytics, and the Internet of Things (IoT) has had a substantial impact on corporate governance practices in recent years, offering both opportunities and challenges for companies worldwide. These technologies improve transparency, efficiency, and decision-making processes in businesses by providing real-time data analysis, automating repetitive operations, and enhancing communication channels among stakeholders. However, the adoption of these technologies also raises significant concerns regarding privacy, data security, and the ethical application of AI, which calls for a meticulous reassessment of governance frameworks to effectively address these concerns. This essay uses the research method of literature review to explore the integration of modern emerging technologies and corporate governance, not only using emerging technologies to assist corporate governance but also supervising the implementation of emerging technologies through corporate governance. This research is conducive to promoting the further improvement of the modern corporate governance system and ensuring that companies maintain a high level of adaptability, sustainability and resilience in a dynamic environment.

Cryptocurrency market has striking development and aims to build open, transparent and efficient financial market. More applications are tried to build on blockchain and using cryptocurrency in multiple scenarios, and DeFi ecosystem is set up. Many niche cryptocurrencies related to DeFi market may have wide utility and demand in the future. Therefore, more research is needed to focus these cryptocurrencies and try to establish sturdy price prediction. In this study, two cryptocurrencies, Binance Coin (BNB) and Huobi Tokens (HT), which are rooted in two crypto exchange platform are used for price prediction based on three machine learning models, i.e., Random Forest (RF), Long Short-Term Memory (LSTM) and Extreme Gradient Boosting (XGBoost). Four prediction windows are selected (1, 3, 7 and 30 days span). The results for different prediction window are compared and discussed. 1 day prediction window outperforms all prediction windows with the average MSE 0.0117. Additionally, RF and XGBoost outperform LSTM with lower MSE and more stable performance, while RF and XGBoost have average MSE 0.0157 and 0.0158 separately. The research tries to predict cryptocurrencies that based on relatively niche market and discuss the performance in comprehensive ways, aiming at providing novel insights into cryptocurrency price prediction.

As China's aging population deepens, pension issues have become a major topic of national and social development. Based on an in-depth analysis of developed countries' pension policies and diversified pension models, this paper addresses the current issues such as insufficient pension service supply and pension funding gaps in China, proposing a series of practical policy suggestions. The study draws on foreign diversified pension models and their security systems and, combined with the rapid development of China's economy, especially the tertiary industry, discusses how the government can guide pension industry policies, bridge pension funding gaps, and promote innovative development in the pension service industry. These suggestions aim to provide theoretical support and practical guidance for the reform of China's pension system, pushing China's pension undertakings to a higher level, with significant social significance and practical value.

The integration of culture and tourism promotes the realization of rural revitalization. In recent years, many examples in China have achieved rural revitalization by developing a new model that integrates agriculture with tourism, deeply exploring local cultural characteristics. This paper focuses on Chengzi County Village in Yangli Town, Laiwu District, Jinan City, Shandong Province, known as the "Millennial Ying City." Utilizing the SWOT model and conducting field surveys, this study comprehensively analyzes the future development of experience-based cultural tourism in Chengzi County Village. Recommendations are proposed for future development, including creating a "1+N" cluster of experience-based cultural tourism projects, incubating distinctive cultural tourism brands, leading with talent, and improving tourism infrastructure. The study concludes that the opportunities and strengths of developing experience-based cultural tourism in Chengzi County Village generally outweigh the threats and weaknesses.

The purpose of this study is to examine the impact and mechanisms of social media on branding in small and medium-sized catering firms. The paper identifies the importance of SMEs in today's market and the rise of social media in brand building. The research question of this paper is "how social media affects brand building in small and medium-sized catering enterprises", which aims to reveal the mechanism of its influence and provide practical guidance. This study adopts a theoretical research method, through literature review and theoretical analysis, to systematically sort out the relevant theories of brand building in small and medium-sized catering enterprises and the role of social media. It is found that social media has an important impact on brand building, including enhancing brand awareness, strengthening brand loyalty, and reinforcing brand storytelling. Finally, this study summarises the key role of social media in brand building of small and medium-sized catering enterprises and provides guidance for practice, while looking forward to future research directions.

The need of efficient management systems for success is highlighted by the globalization of investment banking, which is being driven by market liberalization and technology improvements. Both Goldman Sachs and CITIC Securities make interesting case studies because they have different histories, approaches, and market positions that illustrate how the dynamics of the global financial system are changing. Investment banking globalization's dynamics, impacts, and strategies are explored through a comparative analysis of CITIC Securities and Goldman Sachs. This research employs qualitative methods, examining organizational structures, revenue sources, market presence, and management mechanisms by collecting market analysis, annual reports released by the two investment banks, and some pieces of literature on the topics researched. Findings reveal CITIC Securities' domestic focus and regulatory challenges contrasted with Goldman Sachs' global reach and operational flexibility. Strategic recommendations emphasize enhancing CITIC Securities' international presence and revenue diversification for sustained growth and competitiveness in the evolving financial landscape.

The Nasdaq Composite is one of the world's most watched stock indices and assumes an important role in the global financing trading process. Forecasting of stocks has always been the focus of scholars' research, but due to factors such as market sentiment fluctuations, it is difficult to obtain effective forecasting results using a macro approach. With the help of technological development, data has become more accessible. Scholars have started using statistical models to make predictions on stock prices. This study uses autoregressive integrated moving average (ARIMA) prediction model to forecast the Nasdaq composite index. After parametric statistics, fitting and residual tests, it was determined that the ARIMA (2,1,2) model produced the most accurate predictions. The results of this study enriched the prediction results of the relevant Nasdaq Composite Index for the ARIMA model, broadened the field of application of the ARIMA model, and provided investors with investment strategy references.

The issuance of luxury jewelry futures has garnered attention due to investors seeking diversified investment options and higher returns. This study aims to explore the significance and purpose of issuing luxury jewelry futures. The study focuses on the impact of luxury jewelry futures issuance on investors and the market, addressing key opportunities and challenges. The main objectives include analyzing the effects on market liquidity, risk management, and market transparency. This study employs a literature review and analysis approach, integrating theoretical frameworks with empirical data to comprehensively evaluate the current status and future trends of luxury jewelry futures. Analysis of the luxury jewelry futures market reveals both opportunities and challenges. While luxury jewelry futures provide investors with new avenues for investment, they also face limitations such as liquidity constraints, pricing complexities, high market risks, and information asymmetry. Consequently, investors need to carefully assess market conditions and devise appropriate investment strategies to mitigate risks and achieve favorable returns.

Many majors are currently trending towards integrating and innovating with one another. Today in the 21st century,in order to discover significant value in the prominent sectors of high-tech and finance, it is vital to integrate them. This article employs the method of case analysis to study the development of different high-tech companies worldwide and their incorporation into business. It turns out that in the current global context, the combination of technology and finance is undoubtedly an efficient and resource-saving developmental approach. Moreover, it is also the driving force for the emergence of large enterprises. This essay employs literature analysis and case analysis to examine three instances of utilizing financial approaches to support the technological revolution. The companies mentioned include Tesla, General Motors, Siemens and OPenAI. By analyzing the synergy between emerging high-tech enterprises and their business models, we can gain insights into the future trajectory and utilization of science and technology. This understanding helps us explore how business drives technological advancements and innovation, offering valuable research perspectives for the future growth of both technology and business.