In recent years, with the rapid development of international investment, inevitably, the investment disputes between foreign private investors and the host country are increasing. From the results of the cases submitted to ICSID arbitration, it can be seen that the investor’s winning probability is extremely high, which leads to the imbalance of interests between investor and the host country, and it is difficult to protect the legitimate rights and interests of host country. In this case, the host country may initiate counterclaim arbitration proceedings against the investor’s arbitration request according to the provisions of international investment arbitration treaties, international investment agreements or domestic laws to offset the investor’s request. However, in the practice of examining and dealing with the counterclaim of the host country, the arbitration tribunal often has strict requirements on the jurisdiction and acceptance conditions of counterclaims. On the one hand, the counterclaim clauses involved in the convention are vague, and the standards of “connection” and “consent” are difficult to identify. On the other hand, the lack of investor’s obligation clauses in investment agreements makes it difficult to obtain strong legal support for counterclaims. In order to solve the application dilemma of the host country’s counterclaim rules in practice, the arbitral tribunal should give priority to factual relevance when judging whether the counterclaim is related to the original claim. The way of opposing the request for “consent” should be appropriately modified, and a broader identification standard should be adopted. On the one hand, the host country should strive to set up a special counterclaim clause in the investment agreement, and adjust the rights and obligations structure of both parties in international investment agreement.

This paper analyzes the impact of "Man, Machine, Material, Method and Environment" (4M1E) on the cost of manufacturing products. The research team aims to achieve cost reduction and competitive advantage by eliminating or optimizing non-value-added operations. The paper provides an introduction to the background and motivation of the study, research problem and objectives, and research framework. The objectives of the study include studying the proportion of "method and environment" in product cost and deducing the actual cost of the product, analyzing the cost impact index of 4M1E in product production, and promoting enterprise models for production management optimization, marketing strategy optimization, and environmental optimization to enhance enterprise competitiveness.

This study investigates the audit risks associated with data assets, which have become increasingly vital in the digital economy. As data assets differ significantly from traditional assets due to their intangibility, replicability, and complex valuation processes, traditional audit frameworks are inadequate for identifying and assessing the specific risks they pose. The research highlights the necessity of establishing a specialized audit framework tailored to data assets, cultivating multidisciplinary audit professionals, and adopting innovative audit technologies such as blockchain, AI, and RPA. These measures are essential for ensuring the accuracy, compliance, and security of data assets in financial statements. The study also addresses the importance of effective governance and management of data assets, emphasizing the role of internal controls and the potential risks of significant misstatements due to errors or fraud. The findings provide valuable insights for auditors and accounting firms, guiding them in adapting their practices to meet the challenges presented by data assets, thus safeguarding the integrity of financial reporting in the digital era.

Earnings management refers to the practice where companies manipulate financial statements to alter their true economic condition to achieve certain objectives. Earnings management impacts the quality of a company's financial reporting and market efficiency. It is closely related to factors such as fiduciary responsibility, corporate tax burden, relational transactions, internal controls, litigation risk, and CEO characteristics. The main methods include earnings manipulation, real activity earnings management, and accrual-based earnings management. Engaging in earnings management negatively affects the authenticity and reliability of a company's financial statements and information disclosure. Therefore, companies should improve internal control and supervision mechanisms to reduce the likelihood of adverse impacts.

This paper empirically analyzes the impact of digital transformation on green innovation using a sample of China's A-share listed companies from 2010 to 2022. The empirical analysis shows that digital transformation has a significant impact on green innovation technology. Further mechanism analysis concludes that digital transformation significantly increases investor attention, thereby strongly promoting the development of green innovation technology. This study indicates that in the context of digital transformation, enterprises should adopt green innovation technology as a driving development strategy to enhance corporate value and provide.

The research on the optimization of the internal management system and the sustainable development of universities is of great significance for improving the management level of universities and promoting their development. At present, there are many problems in the optimization of internal management system and sustainable development in Chinese universities, such as imperfect internal management system, lack of systematic and scientific internal management system, and failure to pay attention to information construction. In order to solve these problems, it is necessary to improve the internal management system of colleges and universities, construct the internal management system of colleges and universities, construct the information management system of colleges and universities, and establish and perfect the internal management and assessment system. Through these measures, the management level of Chinese universities can be improved and its sustainable development can be promoted. This paper analyzes the optimization and sustainable development of the internal management system in universities in order to provide reference for the healthy development of universities in China.

Water conservancy construction projects involve the use and management of natural water resources through artificial means to meet the needs of human society for water use and security. These projects encompass flood control and disaster mitigation, water supply, irrigation, hydropower generation, navigation, ecological protection, and other aspects. They are a vital part of national infrastructure, significantly contributing to socio-economic development and safeguarding people's lives and property. With the continuous increase in national investment, the management level of these projects is also improving.Auditing water conservancy construction projects involves reviewing and supervising their authenticity, legality, and effectiveness. It is a crucial component of project management. This paper draws on years of practical experience in auditing water conservancy projects, clarifying the audit methodologies and addressing common issues. It conducts in-depth research and analysis of typical problems and proposes a series of countermeasures and suggestions. These aim to enhance audit verification capabilities, better fulfill audit supervision duties, and promote the high-quality development of water conservancy construction project audits.

This article aims to explore the specific paths and methods of integrating ideological elements into the construction of management courses. By analyzing the characteristics and needs of the management course, combined with the requirements and objectives of ideological education in the course, a set of integration strategies including course objectives, content setting, teaching methods, etc. has been proposed. In practice, the comprehensive improvement of students' ideological and moral literacy and management ability can be promoted through case teaching, discussion classes, practical activities, and other methods. At the same time, this article also introduces relevant measures in curriculum evaluation and teacher team building to ensure the realization and sustainable development of integration effects. Through exploring the construction path of management courses and taking the integration of ideological elements into the curriculum as the starting point, this paper deeply analyzes the inherent connection between management and ideological theory, as well as the challenges and solutions that may be encountered during the integration process. Through case analysis and literature review, a series of feasible paths and methods have been proposed, aiming to promote the organic integration of management and ideological theory, and provide reference and inspiration for improving the quality and effectiveness of university education.

It is particularly important to identify and prevent telecom scams that trick victims into transferring funds through phone calls, Internet and text messages. Based on the collected data, a prediction model of telecom bank card fraud is established in this paper. In the analysis, we first checked the data missing through Pandas and missingno library, and conducted Pearson correlation analysis, and found that the ratio of transaction amount has a strong positive correlation with fraud. In terms of data preprocessing, outliers are defined and data are cleaned by box diagram, missing values are processed by KNN filling, and data is normalized by Yeo-Johnson transformation. Then, the importance of features is calculated by random forest and GBDT, and the features with greater influence are selected. In the model training, XGBoost, LightGBM and CatBoost integrated learning algorithms were selected, and the optimal model configuration was obtained through parameter optimization, and finally integrated into BaggingClassifier. The model performance evaluation shows that the prediction accuracy of the model established in this paper is up to 99.99%.

Chengdu is deeply studying and implementing Xi Jinping's ecological civilization thought and the important instructions of General Secretary Xi Jinping on the construction of park cities during his inspection in Chengdu, Sichuan, vigorously promoting the construction of park communities. Yulin Street is one of the most representative urban streets in Chengdu. Trying to build a park community in the Yulin area not only conforms to its actual situation and needs but also complies with Chengdu's current development policies. Digital governance can be regarded as an innovative and efficient community governance model. This paper introduces this concept into the practice of park community construction, focusing on the dimensions, practical paths, and value orientations of digital governance empowerment. Through empirical research such as interviews, this paper understands the current status of community governance in Yulin Street and explores the empowering role of digital governance in enhancing resident participation, optimizing community services, improving the community environment, and addressing economic and development issues. Furthermore, it proposes specific strategies to promote the construction of a park community in Yulin Street. This paper aims to provide new ideas and references for the transformation of traditional urban communities into park communities, to offer a more comprehensive understanding of the value of digital governance, and to provide strong support for building a livable, harmonious, and modern urban community.

This study explores personalized recommendation strategies within Amazon's product review system using the Logistic Regression algorithm. By analyzing user behavior and review data, a predictive model was developed to forecast user preferences for specific products. The research employed extensive real-world data and validated the model's effectiveness and accuracy through empirical analysis. Findings indicate that the proposed personalized recommendation system significantly enhances user experience and increases product sales. The study contributes an effective recommendation algorithm for e-commerce platforms, offering practical implications for enhancing user engagement and optimizing marketing strategies in competitive markets.

Economic globalization promotes trade globalization, and trade globalization prompts countries to pursue trade facilitation and liberalization. Against this background, CISG came into being in 1980. With the advent of a new round of industrial change and technological revolution, cross-border e-commerce relying on Internet technology has become a new growth point of international trade. Based on the prerequisites, limitations and subjective conditions of the CISG IPR security regime, the paper analyzes the feasibility of applying the CISG IPR security regime to cross-border e-commerce, focuses on the OEM issue in the application of the CISG IPR security regime to cross-border e-commerce, and finally proposes the direction of China’s reform and coping strategies, with a view to contributing to the development of cross-border e-commerce in China.

With China entering a new era of green, low-carbon, and circular development, the green economy has emerged as a powerful force driving economic transformation. Within this realm, green bonds have increasingly captured the market's attention. This paper adopts a case study approach, focusing on the Three Gorges Group's issuance of green convertible bonds. It examines the details and motivations behind the group's issuance, analyzes its short-term excess yield and long-term debt repayment, operational, and profitability capabilities. Furthermore, the study evaluates risks faced by the Three Gorges Group in issuing green bonds, including interest rate, credit, liquidity, and policy risks. Based on these findings, the paper provides recommendations and insights to guide other enterprises and investors, offering valuable experience in this field.

With the global economy increasingly relying on scientific and technological innovation, technology and finance's efficiency has become a key factor to enhance regional competitiveness.As an important province in western China, Guangxi faces both opportunities and challenges in its technology and finance development.Based on the data envelopment analysis (DEA) model, this paper makes an empirical measurement and evaluation on the efficiency of technology and finance, Guangxi, and deeply explores its influencing factors. In the specific research, this paper first constructs an efficiency evaluation system of technology and finance, which includes input and output indicators, and makes an empirical analysis of technology and finance's efficiency by using CCR and BCC DEA models.Through data collection and arrangement, we have made a comprehensive description of the input-output status of technology and finance, Guangxi, and made a scientific evaluation of the efficiency by using an empirical model.It is found that the efficiency of technology and finance shows a certain trend of improvement, but there are still obvious regional differences and deficiencies.Specifically, the efficiency of technology and finance in some areas or fields is high, while that in others is low.In addition, this paper also reveals the key factors affecting the efficiency of technology and finance, which provides a theoretical basis for improving the efficiency. Based on the empirical results, this paper puts forward some countermeasures and suggestions to improve the efficiency of technology and finance.Including strengthening the construction of scientific and technological innovation system, establishing the core position of scientific and technological enterprises and optimizing the business environment in Guangxi.These suggestions are aimed at providing practical guidance for policy makers to promote the healthy development of technology and finance.Generally speaking, through the empirical analysis based on DEA model, this paper makes a comprehensive evaluation of the efficiency of technology and finance, Guangxi, and puts forward some targeted countermeasures and suggestions.

With the acceleration of the global economic integration process and the continuous development of information technology, the competition among automobile enterprises is becoming increasingly fierce, and innovation is becoming the main theme of the survival and development of automobile enterprises.Innovation is a necessary way for automobile enterprises to enhance their core competitiveness, which can help them improve their production and management capabilities and form sustainable long-term competitive advantages.The automobile industry of our country has also entered a new stage of the development of the automobile industry, and the objective needs of the upgrading of the automobile industry have higher requirements for the innovation ability of our automobile enterprise.This paper discusses the impact of ESG (environmental, social and governance) performance on BYD's innovation ability.By collecting indicators such as R&D investment and number of professional applications of BYD Auto from 2013 to 2022, and using Eview12.0 software, the relationship between ESG performance and enterprise innovation ability is analyzed.The research results show that ESG performance has a significant positive impact on BYD Auto's innovation ability.The results of this paper are helpful for enterprises to deeply understand the relationship between ESG performance and enterprise innovation ability, and provide reference for enterprises to formulate sustainable development strategy.

In this study, we evaluated the performance of various machine learning and time series models for predicting Nasdaq stock prices. The models used included Random Forest, Support Vector Machine (SVM), Bayesian Regression, ARIMA, Recurrent Neural Network (RNN), and Decision Tree. We assessed the models using Mean Squared Error (MSE) and Mean Absolute Error (MAE). Random Forest showed promising results with an MSE of 980.67 and an MAE of 18.46. ARIMA and Bayesian Regression exhibited higher errors, with ARIMA showing an MSE of 9763.61 and an MAE of 56.46, and Bayesian Regression with an MSE of 9937.30 and an MAE of 56.63. SVM and Decision Tree had the highest errors, with SVM at an MSE of 28651.85 and an MAE of 136.49, and Decision Tree at an MSE of 439626.21 and an MAE of 518.28. RNN excelled with the lowest errors, achieving an MSE of 4.94869e-05 and an MAE of 0.00464 on the training set, and an MSE of 7.81471e-05 and an MAE of 0.00538 on the test set. The results indicate that the proposed RNN algorithm is effective and outperforms the other models.

As a typical social enterprise, MYBank has gone through a tumultuous development process. Compared with the traditional banking model of "deposit+loan+intermediary business", MYBank adheres to the development orientation of "inclusive finance, serving small and micro businesses, and serving agriculture, rural areas, and farmers", create a new model of "310" Internet loans, and strive to become a real "preferred bank for small and micro businesses". Under the fierce competition in the financial industry, MYBank is facing numerous challenges. In terms of business scale, technical issues such as the limited identification range of the "Great Sparrow" have become the primary challenge. It's both an opportunity and a challenge, pressure and motivation. In the midst of unprecedented changes, MYBank still needs to further enhance their technological innovation capabilities, adheres to an open platform approach, and provides meticulous financial services to small and micro operators.

With the development of Internet and E-commerce, picture advertising, as an important form of display advertising, has the characteristics of high visibility, strong readability and easy to obtain user recognition. An increasing number of Internet companies are paying attention to what kind of advertising pictures can attract more clicks. Recently, Deep Learning has been employed in automatic feature extraction, and has made remarkable achievements in the fields of computer vision, speech recognition, natural language processing and artificial intelligence. Compared with traditional shallow model, deep learning can automatically extract more complex features from simple features, which reduces the intervention of artificial feature engineering to a certain extent. Based on deep learning technology, this paper studies the prediction model of click through rate (CTR) for advertising, and proposes an end-to-end CTR prediction depth model for display advertising, which integrates the feature extraction of display advertising and CTR prediction to directly predict the probability of an advertisement image being clicked by users. This paper studies the deep-seated nonlinear characteristics through the multi-layer network structure of deep network, and carries out several groups of experiments on the private display advertising data set of a commercial advertising platform. The results show that the model proposed in this paper can effectively improve the prediction accuracy of CTR compared with other benchmark models.

This paper investigates the multifaceted economic impacts of artificial intelligence (AI) with a primary focus on productivity, labor market dynamics, and policy implications. The proliferation of AI technologies has ushered in a new era of automation and intelligence augmentation, reshaping various aspects of the global economy.

The research begins by elucidating the significance of AI as a transformative technology. It underscores how AI systems, including machine learning, natural language processing, and robotics, have the potential to revolutionize industries, enhance productivity, and create new economic opportunities.

One central theme of the study is the examination of AI's influence on productivity. It explores how AI-powered automation and decision-support systems can streamline operations, reduce inefficiencies, and boost overall productivity in diverse sectors, ranging from manufacturing to healthcare.

Furthermore, the study delves into the labor market dynamics in the AI era. It analyzes the impact of automation on employment, job displacement, and the need for reskilling and upskilling of the workforce. It also explores the emergence of new AI-related job roles and the potential for AI to augment human capabilities.

A significant aspect of the research is the discussion of policy implications. It addresses the role of governments and institutions in shaping AI adoption, regulation, and ethical use. It explores policy considerations related to data privacy, AI ethics, and the promotion of AI research and development.

Through an analysis of case studies and industry trends, the paper identifies successful models of AI implementation, highlighting best practices and lessons learned. It also emphasizes the importance of ethical AI deployment to mitigate societal challenges.

In conclusion, this paper contends that AI's economic impacts are far-reaching, with the potential to enhance productivity and reshape the labor market. It underscores the need for proactive policy frameworks that balance AI innovation with ethical considerations and labor market stability.

This paper explores the strategic dimensions of marketing for social and environmental causes, emphasizing the delicate balance between profit and purpose in contemporary business practices. In an era marked by growing societal and environmental concerns, organizations are increasingly recognizing the need to integrate social and environmental responsibility into their marketing strategies.

The research begins by highlighting the evolving landscape of corporate social responsibility (CSR) and sustainability in the context of marketing. It underscores how consumers, stakeholders, and regulatory bodies are demanding more ethical and sustainable business practices.

One central theme of the study is the examination of strategic marketing approaches that align profit-making with societal and environmental impact. It explores how businesses can harness the power of purpose-driven marketing to create meaningful connections with consumers while advancing social and environmental causes.

Furthermore, the study investigates the role of storytelling and brand narratives in conveying a company's commitment to social and environmental responsibility. It analyzes successful campaigns and strategies that effectively communicate a brand's values and purpose.

A significant aspect of the research is the discussion of ethical marketing practices. It addresses issues related to greenwashing, authenticity, and the responsibility of organizations to uphold the integrity of their social and environmental claims.

Through an analysis of case studies and industry trends, the paper identifies successful models of strategic marketing for social and environmental causes, highlighting best practices and lessons learned.

Additionally, the study emphasizes the importance of measuring the impact of purpose-driven marketing initiatives. It discusses key performance indicators (KPIs) and metrics to assess the effectiveness of campaigns in driving both profit and positive societal outcomes.

In conclusion, this paper contends that strategic marketing for social and environmental causes offers a unique opportunity for organizations to align their profit motives with a higher purpose. It underscores the transformative potential of purpose-driven marketing in fostering a more sustainable and responsible business landscape.