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.

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.

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.

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.

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 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.

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 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.

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.