Labor investment efficiency reflects how effectively enterprises manage labor resources, directly influencing production efficiency and profitability. Efficient labor investment avoids waste, ensures optimal resource allocation, and supports social stability by promoting effective employment, especially in the context of an aging labor market. However, enterprises with high debt ratios often face inefficiency due to financing constraints, which hinder effective labor resource investment. The resource-based view theory suggests that alleviating financing constraints and optimizing resource use can improve labor investment efficiency. High resource richness can lead to agency problems, and resource uncertainty further impacts efficiency. Traditional studies focus on agency problems related to financing constraints and information asymmetry. This paper posits that enterprises with high debt ratios often experience inefficiency in labor investment, particularly when resources are abundant and environmental uncertainty rises. Additionally, as population aging progresses, technological advancements will interact with labor investment, with information technology reform helping companies enhance labor investment efficiency, thus better meeting future demands for new quality productivity.

Asset pricing has always been one of the core topics in finance research. Traditional asset pricing theory builds a multi-factor pricing model based on market and company fundamentals and verifies it through empirical data. However, financial markets often exhibit irrational characteristics, and market efficiency theory and investor rationality assumptions cannot fully explain abnormal phenomena in the market. Therefore, behavioral finance has gradually emerged, expanding the framework of asset pricing models by introducing investor behavior and emotional factors. This study aims to explore the impact of investor sentiment on Chinese stock market pricing. By analyzing the monthly data of the Chinese stock market, the traditional Fama-French three-factor model was constructed, and on this basis, the sentiment factor was added to propose a new four-factor model. Research results show that the sentiment factor (SENT) has a significant impact on the returns of small-cap stocks and low price-to-book ratio stocks, especially during periods of large mood swings. Changes in investor sentiment often trigger irrational trading, leading to stock price declines. Reverse fluctuations. Compared with the three-factor model, the four-factor model has a better fitting effect in explaining stock market returns, further proving the importance of emotional factors in the Chinese stock market. This study not only fills the gap in the existing literature on investor sentiment in the Chinese stock market but also provides a theoretical basis for localized adjustment of multi-factor pricing models.

The Belt and Road Initiative (BRI), proposed in 2013, has become a transformative global strategy fostering economic collaboration, infrastructure development, and connectivity across Asia, Europe, and Africa. However, as the emphasis on sustainable development grows, the integration of Environmental, Social, and Governance (ESG) practices within the BRI framework has emerged as a critical focus. This essay examines the current state of ESG implementation under the BRI, highlighting notable corporate case studies and regional variations. It identifies key challenges such as regulatory inconsistencies, cultural and social barriers, economic pressures, and a lack of expertise in participating countries. Building on these insights, the essay proposes strategies for improvement, including establishing regional ESG hubs, expanding multilateral financial support, sharing best practices, and developing global ESG monitoring systems. These measures underscore the importance of international cooperation and knowledge sharing in aligning BRI projects with global sustainability goals. The results help to learn more about how to include ESG factors in big international projects. They also give policymakers and other interested parties useful tips on how to get rid of problems and ensure long-term success.

In the Chinese market, there are many small and medium-sized enterprises with financing needs. Due to existing risk factors and the high cost of physical business outlets, however, financial institutions are unable to serve all those in need. Nevertheless, the total demand of such groups is huge, making the need for finance by the SME(small and medium enterprise) community cannot be ignored. This thesis adopts the method of literature analysis and review to mainly study what kind of problems will be encountered in the process of using digital technology to realize financial inclusion in China, and how the regulators and policymakers should manage the risks and formulate relevant policies in light of China's national conditions, so as to enable financial institutions to develop digital financial in a viable and effective way, and ultimately achieve the goal of providing financial services to all groups in the social strata at a low cost. This thesis finds that while strengthening regulation of digitalization in the financial sector in order to reduce risks, it is important to realize that the current lax regulatory environment is one of the key reasons for the rapid development of digital finance in China and that policymakers should weigh the pros and cons and find a compromise in the policymaking process.

In recent years, China's used car market has experienced significant growth, emerging as a vital channel for vehicle owners to both sell and purchase cars.The rise of used car trading platforms has significantly improved transaction efficiency. Researchers have found that exploring ways to enhance the resale value of used cars is of great significance for used car sales. Therefore, the theme of this paper is an analysis of the impact of vehicle condition on resale value based on the Dongchedi platform. The study utilizes a combination of research methods, beginning with the collection of multidimensional data from the Dongchedi platform, spanning from 2007 to 2023, with a sample size of 150 vehicles. Using Python's OLS regression analysis, it examines the extent to which various factors affect resale value. The study finds that factors such as "whether it is a new model," "whether it is being resold for the first time," and "whether it has leather seats" have a significant impact on resale value. Conversely, factors such as "fuel consumption per 100 kilometers," "whether the car is black or white," and "whether an inspection report is available" do not demonstrate a statistically significant impact on resale value. This findings offer references for merchants and platforms in optimizing the pricing of used cars and the information display strategies of user interfaces.

With the advancement of artificial intelligence (AI) technology, the infringement of personal acoustic rights has become an increasingly severe issue. Objective factors, such as the ease of collecting voice data, have contributed to the frequent emergence of cases involving the infringement of personal acoustic rights through generative AI. In particular, the collection of voice data by smart energy devices has led to numerous legal and ethical issues. This paper examines the development and current status of legal frameworks protecting acoustic rights in Chinese law. It explores how the rise of AI and smart devices has challenged existing regulations and created new risks for personal acoustic rights. In response, this study advocates for the establishment of a robust voice licensing system, the incorporation of watermarking technology in AI-generated audio, and stricter regulatory oversight on usage scenarios and generated content. By implementing these measures, the study aims to strengthen the legal and technological safeguards for acoustic rights, ensuring effective protection in the age of AI.

With the wide application of social media in today's society, brands gradually regard it as an important publicity channel. Among them, co-publishing content with celebrities has become an effective strategy to enhance the brand's influence on social media, and achieved remarkable results. Therefore, the in-depth study in this field is of great significance. Although the existing research mostly focuses on the celebrity joint effect of luxury brands, ordinary products and brands are equally worthy of attention. This study focuses on beverage brands in particular. Because drinks are daily consumer goods, their taste cannot be directly experienced through social platforms. Therefore, cooperation with celebrities has become an indispensable means in the promotion of beverage brands.Based on the theory of social identity, this paper discusses the relationship between the joint promotion of beverage brands and celebrities and the growth of likes, comments and shares on social platforms. The research mainly collects data from Weibo platform, and uses regression analysis for empirical research. The results show that all the dependent variables are significantly improved, indicating that joint promotion with celebrities is helpful to enhance brand influence and competitiveness. However, when the content contains elements such as money or lottery, which may violate the public's perception of celebrity images, the social identity effect will be limited. In view of this phenomenon, we use social identity theory to explain it in detail, and suggest that beverage brands should avoid introducing such elements into the promotion content when cooperating with celebrities in order to maximize the cooperation effect.

This paper examines the impact of behavioral biases on the attitudes and intentions of both institutional and retail investors towards Environmental, Social, and Governance (ESG) investing. Behavioral biases, such as loss aversion, overconfidence, and confirmation bias, can significantly influence investment decisions, often leading to irrational behavior in the face of complex and uncertain information related to ESG factors. By avoiding behavioral biases, investors can more easily make rational decisions based on available data and logical processes. This study primarily focuses on overconfidence and the disposition effect, emphasizing how these biases affect investors' perceptions. Additionally, the paper underscores the importance of recognizing and addressing behavioral biases and outlines methods to do so. The study shows that behavioral biases, particularly representativeness bias, significantly influence retail investors, often leading them to make decisions against market trends and potentially resulting in losses. In contrast, while institutional investors are also subject to behavioral biases, their expertise enables them to effectively mitigate or even leverage these biases to achieve positive outcomes. Ultimately, the paper calls for further research into the ways that behavioral finance can inform practices that enhance the adoption of sustainable investment strategies among all types of investors.

In 1994, China implemented a major tax reform aimed at ensuring a stable budget for both central and local governments, laying a solid foundation for the country's sustainable development. In order to stimulate local governments' investment enthusiasm in key economic areas, especially in agriculture, the central government has carefully planned a series of special transfer payment policies. These policies not only provide the necessary financial support for local governments, but also set clear conditions for local governments to ensure the corresponding expenditure of local budgets before obtaining specific transfer payments. This special transfer payment system has played an important role in promoting China's rapid economic growth. In order to deeply understand the effect of this system, this paper constructs an incentive response theoretical model to deeply analyze the response mechanism of local governments to special transfer payments. The results of the model show that only when the amount of special transfer payments exceeds a certain threshold can local governments effectively stimulate their spending behavior. In addition, this incentive effect is particularly evident in areas with relatively backward economies.

With the development of internet technology, a lot of IP images have been loved by the public, and the commercial value derived there from has gradually emerged. Faced with a multielement consumer market, more and more companies want to get more benefits launching co-branded products through IP collaborations. The essence of IP collaboration is cooperative game between two enterprises. they will strive for optimal resource allocation through continuous strategy formulation and adjustment, jointly enhancing their respective brand values, broadening market shares, and ultimately achieving a win-win situation. This paper employs cooperative game theory to quantitatively analyze the decision-making behaviors of two enterprises in IP collaboration. By constructing a game matrix, it intuitively reveals the positive impact of IP collaboration on corporate revenue growth. Then, this paper analyzes the reasons for the success of the collaboration between Luckin Coffee and Moutai through the cooperative game approach, focusing on aspects such as partner selection, resource sharing, and strategy formulation, and finally puts forward corresponding suggestions.