In the realm of financial analysis, discerning the correlation between total revenue and Earnings Per Share (EPS) serves as a pivotal indicator of a corporation’s financial stability and potential for growth. This research navigates through the divergent pathways of the tech and pharmaceutical industries, elucidating a marked correlation in the former and a distinctly subdued one in the latter. By immersing into an incisive analysis that encompasses industry-specific attributes, market dynamics, and financial protocols, this paper not only shines a light on the disparities in the revenue-EPS correlation across these industries but also posits that the divergences can be substantially attributed to the disparate R&D investment strategies and regulatory environments that inherently characterize them. The encapsulated findings offer a refined lens through which the financial undercurrents of pivotal industries can be examined, providing foundational insights for investors and policy-makers alike.

Under the background of global politicisation and economisation, international trade has become the main mode of communication among countries. With the explosive growth of international trade volume, human society will face trade discrimination and inequality, so human beings have set up the International Trade Organisation (ITO), which supervises the process of international trade and formulates the relevant international economic laws in order to better guarantee the sustainability of the economic cycle and protect the rights and interests of the disadvantaged countries. However, as time goes by, we can see that in reality most developing or third world countries are still unable to defend their legitimate interests and are at a disadvantage in most transactions. So this study will be based on the difference in the strength of the different countries and the structural shortcomings of the Global Trade Organisation. This paper will analyse why disadvantaged countries are still unable to obtain equal opportunities for development in the international community, which now has a more comprehensive legal system.

The sharing economy create a new model for the society to provide the properties with different status which is not be full-utilized by the host. Airbnb is a typical example, which allows the host to provide their rooms to the customers. Our work focus on the micro level to show the relation. Using the anonymous data of properties in New York City from Airbnb, we estimate the effects of properties’ status on market performance and supply behaviors. Our result shows that the higher daily rates would lead to higher booking numbers. However, the extra fee such as clean fee and Security Deposit will do negative effects on number of booking. Further more, Convince and information availability cause better performance. Supply behaviors will not be changed easily. However, we found that the weekend, higher price and lower annual revenues will lead to higher probability of block.

In this paper, we performed bitcoin price prediction based on bitcoin price dataset using Support Vector Machine model, Random Forest model, Neural Network model, XGBoost model and LightGBM model and evaluated the performance of these models. We divided the Bitcoin price dataset into training and test sets in a ratio of 7:3, where 70 were used as the training set and 30 as the test set. The models were trained with the training set and tested with the test set using the stock price change (yield) as the target variable and other variables as input variables. By comparing the MSE, RMSE, MAE, MAPE and R² of the different models were evaluated and it was found that XGBoost has the best performance and the best prediction. The performance of the other four models ranged from good to poor, including LightGBM, Random Forest, Support Vector Machine and Neural Network. Among them, the neural network, whose MSE is tens of times higher than the other four models, performs the worst. The research results in this paper can provide reference value for future Bitcoin price prediction, and also provide some reference for choosing appropriate machine learning models.

Behavioral finance challenges traditional financial theories by questioning the assumption of investor rationality, highlighting the influence of cognitive biases, emotions, and psychological factors on decision-making. This deviation from conventional models like the Efficient Market Hypothesis recognizes the complexity of human decision-making in financial contexts. The field focuses on key phenomena: loss aversion, market anomalies, the framing effect, and the endowment effect. Loss aversion reveals a stronger reaction to losses than equivalent gains, influencing overly cautious decisions. Market anomalies, such as momentum and trend reversals, challenge efficient market expectations. The framing effect shows how decision-making is swayed by information presentation. The endowment effect impacts perceived asset value, affecting financial decisions. These biases significantly impact investor behavior, potentially leading to suboptimal portfolio choices. Recognizing these biases is crucial for making informed financial decisions. Behavioral finance research has profound implications, emphasizing the integration of behavioral insights with traditional models. Future studies should explore cumulative behavioral effects, conduct cross-cultural analyses, and investigate diverse market conditions for more effective investment strategies and regulations. Understanding global financial behavior through behavioral finance is essential for comprehensive insights into market dynamics and decision-making processes.

In this study, the researcher will assess the marketing strategy analysis of Pinduoduo, a Chinese e-commerce giant that, over the past few years, has gained prominence and increased its market share against traditional e-commerce companies such as Alibaba and JD.com. In this study, the researcher will examine the effectiveness of the evolving online marketplace, focusing on the company’s unique business model and strategies such as time-limited instant kills and social media marketing to develop a better understanding of the impact and success of Pinduoduo’s approach. The methodological approach that the researcher will use is a comprehensive literature review and the SWOT model to understand Pinduoduo’s digital marketing strategies. The literature review approach will focus on the core business model of the company, while the SWOT model will be instrumental in analyzing market positioning and segmentation. The key questions in this study include: conducting an assessment of the efficacy of Pinduoduo’s marketing plan; understanding its digital marketing trends; and drawing insights from global success stories in the industry. Pinduoduo’s marketing strategies that have led the company to effectively engage users, specifically those from low-tier cities, include time-limited instant kills, daily cash rewards, and subsidies. The SWOT analysis has helped the company identify strengths, such as market differentiation, and weaknesses, such as high unit prices. In conclusion, Pinduoduo’s success will be based on its ability to successfully navigate the sinking market and its successful utilization of its strategic innovations, making it a formidable player in the digital era.

To prevent over expansion of property bubbles in China, housing purchase restriction policies were put into effect in 2010. Nevertheless, to be adaptable to economic conditions at that time, there was firstly a relaxation of housing purchase restriction policies in 2014 and after that, several more adjustments were made. By analyzing the financial indicators of the main real estate enterprises in A-share market, this paper wants to find the general trends and common features of those corporations under policy adjustments and changeable market environment. The analysis results show that the majority of firms kept high levels of debt and inventory all the time and from 2014 to 2019, most companies’ net income margins, net income and operation revenue generally kept increasing. However, as the Coronavirus pandemic broke out at the end of 2019, those profitability measures started to decrease widely and sequentially, even with a new round of policy easing. Facing with this situation, it is suggested that to prevent debt risks, property enterprises could take deleveraging and destocking into consideration and to achieve a soft landing of the housing market, new ways of policy adjustment could be implemented by the government.

Canada has been at the forefront of mitigating climate change by adopting strategies that align with the international objective of limiting global warming. For instance, the Canadian government has intervened in the transport sector by enacting vehicle emission reduction policies such as the ZEVs policy that encourages the adoption of EVs, FCVs, and PHEVs. The policy aligns with the Canadian government’s ambitious target of getting more ZEVs on Canadian roads as a strategy to achieve “100 percent zero-emission vehicles by 2040, with interim goals of 10 percent by 2025 and 30 percent by 2030”. However, although ZEVs offer Canada an opportunity to reduce its GHG emissions in the transport sector, there has been concern about the upfront costs associated with adopting ZEVs, which continue to be a major deterrent despite their operation and maintenance costs being low. The following research paper conducts a CBA on ZEVs compared to CVs in Canada in terms of ownership costs and environmental impact.

From the perspective of supply chain management, the silicon carbide supply chain currently exists in the technical force is low, the development situation is poor, as well as the traditional silicon-based devices still occupy the relevant areas of the market, silicon carbide in addition to the urgent need for breakthroughs in the field of technology, due to the adjustment and transformation of the industrial structure as well as the upstream production capacity expansion makes the silicon carbide industry is also faced with the lack of supply chain management capabilities and the backwardness of the management structure. This is also the core element that this paper will focus on. The research theme of this paper is how to complete the transformation and upgrading of the silicon carbide supply chain through the role of digital intelligence, to effectively increase the production capacity of silicon carbide and change the current production dilemma. To this end, this paper focuses on the feasibility of solving the existing problems of the silicon carbide supply chain by upgrading the supply chain empowered by Digital Intelligence. The results of this paper are based on the successful reform experience of the steel industry, through management restructuring, supply chain expansion, industry chain extension, improving industrial technology, manufacturing to service transformation, and the combination of digital intelligence technology for industrial restructuring, to increase the production capacity of the silicon carbide industry.

The role of social media in marketing and e-commerce has grown exponentially as the Internet has had a transformative influence on consumer behavior. And, the trend of online shopping is gradually becoming the dominant way of consumption and surpassing the traditional sales model, particularly in the context of the significant impact of the COVID-19 pandemic. The article highlights key findings related to the efficient use of social media as a marketing channel, customer engagement strategies, selection of social media platforms, and maximizing return on investment through the literature review and theoretical analysis. This research also illustrates the practical implications of these trends with a case study of Amazon's online versus traditional brick-and-mortar retailing. In addition, the article underscores the importance of understanding and leveraging the power of social media platforms for businesses looking to thrive in the digital age. It predicts a promising future for social media platform sales with continued growth and evolving opportunities for businesses.