As the natural environment deteriorates, electric vehicles will gradually replace internal combustion engines that use traditional fossil fuels. This paper compares traditional engines to alternatives regarding efficiency, emissions, price, and market share. In brief, alternative engines have advantages over traditional internal combustion engines in terms of efficiency, emissions, and long-term overhead, as evidenced by rising market share. In 2022, the share of electric vehicles in global sales has reached 14%. Compared to traditional internal combustion engine vehicles, electric vehicles have a higher well-to-wheel efficiency, up to more than twice of internal combustion engine vehicles. From a price perspective, electric vehicles have a higher original cost. However, lower maintenance costs allow electric vehicles to achieve the same cost as equivalent combustion engines in 5-8 years. Electric vehicles typically have low well-to-wheel and fuel emissions and are more sustainable. In the future, more research and development are needed for electric vehicles to make them suitable for most cities worldwide. At the same time, research into the traditional internal combustion engine should be addressed, as cleaner, more efficient engines such as the HCCI engines are already available for civilian use.

India is an important exporter of rice in the world. In 2022, India's total rice exports accounted for over 40% of the world's rice exports. With India's announcement of restrictions on rice exports, the import price of rice has also increased. As a populous country, although China has high grain production, due to factors such as food security and balancing international trade, China also imports a large amount of grain from other countries every year. Since 2022, many countries, including Russia, Brazil, and others, have also chosen to restrict grain exports due to certain factors. Although China's rice production can make it self-sufficient, the situation for other agricultural products is not the same. If the largest exporting country of some crops with low yields China restricts their export, it will undoubtedly have an impact on China's imports and market, as the difficulty of importing these crops has increased. This article aims to analyze the impact of grain export constraints on China through literature review to demonstrate the impact of grain export restrictions from other countries on China in order to draw attention to the impact of grain export restrictions on China.

The construction industry has faced a block in its development in recent years, and the need to enhance the value of construction industry enterprises is imminent. The U.S. construction market is one of the most prosperous markets in the world, so the study of enhancing the value of firms within the U.S. construction industry holds considerable importance. Many previous studies have focused only on qualitative factors, which has some limitations. Therefore, this study investigates how to enhance the market value of U.S. firms from the perspective of financial factors. This study uses regression analysis to select the financial data of 34 U.S. companies listed in the construction industry. Then the relationship between their EV/EBITDA, net profit margin, and gross profit margin is modeled, and four sets of linear regression equation models are established, revealing that net profit margin, gross profit margin, and enterprise value have a significant positive relationship.

This study aims to analyze the future trends of the Shanghai Composite Index (SSE Composite Index), a primary stock index on the Shanghai Stock Exchange (SSE). The SSE Composite Index not only serves as a crucial indicator of the Chinese capital market but also attracts global attention as a focal point in financial markets worldwide. Its fluctuations have broad impacts, influencing decisions of investors and the global economic environment. Due to the increasing limitations of traditional forecasting methods such as moving averages and exponential smoothing in the face of the complexity and uncertainty of financial markets, this paper chooses to employ the Autoregressive Integrated Moving Average (ARIMA) model for more accurate and sophisticated predictions. The paper provides a literature review to outline relevant studies, delves into the specific processes of data preprocessing and model establishment, and concludes with empirical analysis and result discussions. The study suggests that the ARIMA model remains effective and feasible in predicting the SSE Composite Index.

This article describes how e-commerce in China has developed in different periods of time, respectively, the stable development before the epidemic, like the three five-year plans, in China, the “five-year plan”, known as the Outline of the Five-Year Plan for National Economic and Social Development of the People’s Republic of China, is an important part of China’s national economic programme and is a long-term plan. It is a long-term plan, mainly for planning major national construction projects, the distribution of productive forces and important proportional relationships in the national economy, and for setting goals and directions for economic development. and the emergence of new retail, the time of the epidemic, although faced with the epidemic affecting the economic difficulties, but e-commerce also has its own unique advantages. The opportunities for e-commerce development in the post epidemic era and the future direction of development. E-commerce is an important part of the future market economy, and with China’s well-developed transportation industry, online retailing will become one of the most important ways to consume.

Public-Private Partnership (PPP) projects represent a pivotal strategy in addressing infrastructure funding shortages. Originating in the 1980s, the PPP model gained traction globally, with China entering its standardization phase in 2014. However, the extensive scale, prolonged construction periods, and diverse stakeholders involved in PPP projects introduce multifaceted risks. To navigate these challenges, the Ministry of Finance emphasized the need for accurate risk identification in 2019. This paper integrates the "accurate identification" theory with big data technology, providing a theoretical foundation and technical support for precise risk assessment in PPP projects. The 5V characteristics of big data—scale, diversity, low-value density, data validity, and rapid processing—enable cost-effective and efficient risk analysis. Key risks, including financial, government credit, pricing mechanism, force majeure, and approval delays, are identified. The "accurate identification" theory and big data facilitate not only risk identification but also preventive measures. This comprehensive approach aims to enhance decision-making, reduce conflicts, attract social capital, and improve the overall efficiency of PPP projects.

This paper aims to investigate the factors driving the rapid development of the Chinese economy. Utilizing univariate linear regression, we examine the impact of compulsory education in China on its economic growth, utilizing data from the National Bureau of Statistics of China spanning the years 1983 to 2006. Additionally, we conduct robustness tests and heterogeneity analyses using variables such as the number of middle school students, Chinese GDP, and the time span from 1983 to 2022. Our analysis also delves into industry-specific variations and expenditure-based approaches. Our findings are summarized as follows: 1. Compulsory education in China exhibits a positive influence on its economic growth. 2. According to the robustness test, the baseline conclusion of this paper is robust. 3. Compulsory education plays a pivotal role in the tertiary industry and net exports but exerts fewer effects on the second industry and investment and contributes a little to the first industry and consumption.

Survivorship bias frequently engenders an inclination to disproportionately concentrate on instances of achievement while inadvertently disregarding the less conspicuous instances of failure; within the realm of new enterprises, where aspirations for achievement permeate, this cognitive bias can engender excessive self-assurance and disregard for the genuine obstacles at hand. This article examines the prevalence of survivorship bias in the context of startups when most newly established enterprises experience failure. It also underscores the significance of mitigating survivorship bias by drawing upon historical and present business illustrations. This study delves into the narrative of Vine, a social media platform that, despite its initial potential, fell short of attaining the level of success achieved by its counterparts. This case study highlights the importance of examining successful and unsuccessful initiatives to develop a comprehensive grasp of the obstacles and possibilities within the realm of entrepreneurship. Moreover, survivorship bias has implications that extend beyond the realm of startups and can significantly impact decision-making processes inside financial institutions. This is particularly evident in evaluating investment groups, where performance assessments sometimes exclusively consider the entities that have managed to survive. Consequently, this approach has the potential to introduce a bias that may lead to an excessively optimistic interpretation of the data. This paper proposes the adoption of a complete methodology that considers both successful and unsuccessful cases in order to enhance decision-making in the field of entrepreneurship, thereby mitigating the potential biases associated with survivorship bias.

This research employs a two-dimensional perspective that integrates stakeholders and the entire project lifecycle. It utilizes social network analysis methods and Ucinet6 software to establish a network model of quality management risks in the context of Engineering Inherent Defects Insurance (IDI), Engineering Quality Liability Insurance, and Engineering Quality Assurance Insurance. The study calculates and analyzes the centrality, group density, and cohesive subgroups within the risk network. It identifies key influencing factors and, based on the analysis results, proposes strategies and recommendations. This research provides vital decision support for the future development of the construction industry. The study reveals that three key factors, namely, inadequate construction organization management, unclear construction scope definition, and improper maintenance of construction machinery, are closely related to quality management risk factors. These risks can be effectively mitigated through measures such as strengthening the training of management personnel, implementing relevant regulations, and regular maintenance of construction machinery.

Project management is an indispensable aspect of business that depends heavily on the capabilities and characteristics of the project managers, with his/her personality traits playing an essential role in leading their project to its goals. This paper explores the critical role of the project manager's personality traits and cultural background in the success of project management and emphasizes its influence on team dynamics, stakeholder engagement, and overall project environments. The Big Five personality traits provide a framework for understanding these influences. The paper also delves into how the Myers-Briggs Type Indicator (MBTI) impacts project management approaches, specifically the Extraversion/Introversion and Judgment/Perception dimensions. In addition, the paper examines the impact of global and cultural differences on project manager traits and management styles, emphasizing the need for project managers to adapt to different cultural contexts in a world where understanding and leveraging cultural differences is critical to project success and the achievement of broader strategic goals. This comprehensive analysis offers insights into the multidimensional role of project managers within today's highly dynamic global project management environment.

Controlling risk is one of the most crucial steps when constructing investing portfolios. This paper started with tactical asset allocation (TAA), which investors would prefer compared to other long-term strategies within an acceptable range of risk. According to the report from Faber, his quantitative marketing timing model can manage risks, which means it can be applied to improve the process of portfolio construction, and the shining point of the model is that investors would choose the way that minimizes the loss if the draw-down of return is unavoidable when facing the volatility of a market. This paper evaluated Faber’s timing model by applying it to China’s capital market, where there are supposed to be more extreme cases. Also, since there are relatively few studies examining the timing effect and combining it with asset allocation as a reference in China, this paper studied one experiment in 2017 by two scholars who were familiar with the local market to prove that timing strategies also require timely adjustment of tactical asset allocation to achieve better returns. On the other hand, when there are signs that the economic environment is going to experience a recession, investors could get inspiration from this paper on how to promptly adjust the factors in the timing model to better adapt to the changing market.

Many of today's firms are suffering from leverage imbalance. A company's debt can negatively impact its performance when it deviates from its target leverage. Thus, this paper discusses adjusting the firm's capital structure to an optimal one. Combining stakeholder theory and signaling theory, this paper discusses how and under what circumstances ESG may have an impact on capital structure, from which the paper proposes the following conjectures: whether ESG can have a significant impact on a firm's target leverage; how ESG can affect a firm's capital structure when the firm has an asymmetry of information; and whether ESG can be tailored to economic environments that can have an impact on a firm's capital structure changes have an effect. After the inference of this paper, ESG can effectively influence firms' capital structure and accelerate the adjustment speed of firms' leverage to target leverage under the state of firms' information transparency. ESG will be more effective in regulating firms' target leverage in the downturn of the economic environment. The analytical framework of this paper may also be effectively applied to other research directions, such as corporate investment decisions, cash holdings, and dividend policies.

Gross Domestic Product (GDP) is the core indicator of national economic accounts, which reflects the economic capacity of a region. It is necessary to have an accurate forecast of GDP. GDP prediction plays an important role in formulating economic policies. By predicting the growth trend of GDP, the government can make correct adjustments and regulate economic activities. This paper takes Guangdong Province and Shandong Province as examples, aiming to establish their GDP models respectively, and obtains their important economic factors on the basis of the models. Firstly, the correlation test and stepwise regression method were used to screen out the variables with significant impact on GDP, and then ridge regression was used to solve the multicollinearity to make the model more accurate. Finally, the similarities and differences of important economic factors in the two provinces were compared. The important economic factors of these two provinces can reflect the characteristics of the economic development of China's north and south, which is conducive to promoting the coordinated development of regional economy and win-win cooperation.

This article explores two key theories in behavioral finance: Subjective Expected Utility Theory (SEUT) and Prospect Theory, outlining their development as responses to historic economic paradoxes, challenging traditional notions of rationality in economic decision-making. SEUT extends the concepts of expected value and rational choice, incorporating individual utility functions and subjective probabilities. Despite its comprehensive approach, SEUT struggles to explain certain behaviors under risk and uncertainty. Prospect Theory, conceived by Kahneman and Tversky, offers an alternative. It introduces decision weighting, focusing on how individuals differently perceive gains and losses relative to a reference point. This theory explains human biases like loss aversion and framing effects, which SEUT overlooks. Through practical examples and empirical studies, the article demonstrates scenarios where human behavior deviates from SEUT predictions, influenced by psychological factors. However, both theories provide insights into economic decision-making, they have their respective strengths and limitations. The article suggests a more integrated approach, recognizing the complexities of human decision-making in economic contexts.

This article is based on the background of economic development and economic development is an important factor for a country or region to achieve prosperity and sustained growth. With the advancement of globalization and the rapid development of science and technology, economic development has become one of the top priorities for many countries. and reviews 12 literature on the economic development of China and other countries. It provides detailed reviews and suggestions on the ARDL model, multiple linear review model, spatial analysis method, and DSDM model to analyze economic growth factors, economic growth factors in some regions of China and Europe, and economic growth factors in fisheries, coal industry, tertiary industry, and tourism, The conclusion was drawn that China’s overall economic development prospects are good and there are great opportunities, and the economic specialization of the European Union cannot ensure economic growth. Suggestions were given for the economic development of some industries, environmental economy, and green economy in China.

In an effort for future investment implications, the current study examined the relationship between historical Quantitative Easing (QE) programs and the stock market. This study analyzed weekly basis data in the United States between 2007 and 2023. Through a Vector auto-regression (VAR) model, a significant rise following a quick drop in stock prices to a positive shock in QE was discovered, indicating lagged response. Further robustness check proved the validation of relationship, by sectioning the whole data set into 4 periods corresponding to four QE programs, except relatively insignificant effects in QE2 and QE3 periods. These lagged responses were pointed out firstly in this paper and connected with policy motivations and contemporaneous economy environment across programs. The findings may enable investors to anticipate market movements and generate respectable returns in the event of such unconventional money shocks.

After discovering the existing problem in the HK distribution center of ABC, our research team got in touch with the staff of the warehouse and then completed the diagnosis of the problem as well as the consideration of optimization actions through the interview, combined with literature analysis. Our team interviewed 4 employees and summarized the current workflow and existing workarounds in the warehouse. In the current working environment, employees are under high work pressure, a high error rate, and the workflow does not match the work system. We put forward the system optimization suggestions for integrating Personal Digital Assistant (PDA), Warehouse Management System (WMS), and Ultra Wide Band (UWB) positioning technology and make corresponding adjustments in both equipment and management, hoping to get the expected outcomes of the intervention.

The current research suggests the presence of asset mispricing by indicating that stock prices may not necessarily reflect underlying fundamentals. Additionally, prior studies often underestimate the importance and overlook contributions from resources to the returns. In this article, we propose the effect of intangible assets into asset pricing in the context of varying investor sentiment and long-term investment horizon. Drawing from the recourse-based view of intangible assets within firms, we can better assess a firm’s growth and stock returns. We conclude that the Capital Asset Pricing Model (CAPM) should incorporate the influence of intangible assets. These assets can reduce operational risk, thus affecting idiosyncratic risk.

Logistics has become an integral part of the market economy, influencing the development of various industries and serving as an essential component of people’s lives. Against the backdrop of global economic downturn following the COVID-19 pandemic, understanding the effects of China’s logistics industry development on resident consumption becomes crucial. This paper employs a simple linear regression model and utilizes provincial panel data from 2005 to 2022 to explore the impact of logistics industry development on resident consumption in China. Furthermore, it employs heterogeneity analysis methods to study this relationship from different regional, temporal, and consumption perspectives. The findings of this study reveal that (1) there is a positive relationship between logistics industry development and resident consumption, (2) the effect of logistics industry development on increasing resident consumption levels is most significant in the eastern region of China, (3) the positive impact of China’s logistics industry development on resident consumption increased after the introduction of free shipping by Taobao in 2008, and (4) the positive impact of China’s logistics industry development on rural consumption is greater than that on urban consumption.

Strategically, Apple specializes in research and development to gain a wide range of high-quality product recognition and a large number of loyal fans, gaining customer loyalty. At the same time, the sales team caters to the overall strategic policy of the company, providing higher quality service (apple care) and warmer service. Moreover, in the performance evaluation, if the relevant indicators have a strong correlation between the company's strategy and the interests (performance) of each team and individual, it will promote the collaborative development of the company and sales team.At the same time, in empowering the sales team, clear goals will be set within the team, giving the group consistent direction