This article focuses on the impact of artificial intelligence, or AI, on the application of commercial big data and its functional dimensions, and explores all its specific values in the retail industry. First of all, this article elaborates in detail on the connotations of artificial intelligence and commercial big data, their respective characteristics, and development situations. It also analyzed a transformation model such as "data - algorithm - business value" formed after the integration of the two, which has brought about significant changes to the traditional analysis methods. This article then specifically elaborates on the role that artificial intelligence can play in customer analysis, how it functions in marketing optimization, what assistance it offers to operational efficiency improvement, as well as its roles in risk control and dynamic cycle mechanisms. Subsequently, it discusses the application strategies in different scenarios, demonstrating the feasibility of these strategies from the perspectives of technology, cost, and benefit. This article summarizes the research results, points out the limitations of the research and the future development direction. These contents can provide some references for enterprises to formulate intelligent data strategies.

In the rapidly evolving digital reading market, Tomato Novel—a core platform under ByteDance—faces the critical challenge of improving user stickiness. This study explores the current status and issues of Tomato Novel in terms of user engagement, real-time feedback, personalized recommendations, and sense of community belongingness from an interactive marketing perspective. Findings reveal improvement opportunities in Tomato Novel’s interactive features, feedback mechanisms, personalized algorithms, and community culture. For instance, its comment and rating systems lack interactivity, feedback channels are obscure, personalized recommendation accuracy needs enhancement, and strategies to foster community belongingness are ineffective. To address these, the study proposes: integrating with platforms like Douyin to elevate user interaction; leveraging AI to optimize feedback mechanisms; refining personalized recommendation algorithms for precision; and adopting WeChat Reading’s'Co-Reading’feature to create a Tomato-Douyin user book circle, thereby strengthening community ties. These actionable pathways offer key strategies for Tomato and other digital reading platforms to optimize interactive marketing.

The global aging population has been intensifying the demand for innovative elderly care solutions, with technology-driven entrepreneurship emerging as a key response. However, current approaches tend to prioritize technological progress over human factors, resulting in an imbalance in service delivery and a gap with real needs. This study explores the integration of technology and humanism in elderly care entrepreneurship through business model innovation, leveraging the Business Model Generation framework. Based on the framework of business model theory, this study proposes a technology-humanity balance model that emphasizes the integration of humanistic values into scientific and technological applications to meet the functional and spiritual needs of the elderly through case studies and theoretical integration. The findings highlight that business model innovation, especially through the value proposition and customer relationship dimensions of the Business Model Canvas, can effectively harmonize technological efficiency with humanistic care, achieve the dual drive of “function + emotion”, provide practical reference for technology-based elderly care entrepreneurs, and contribute to academic discussion and practical application.

In the aftermath of the COVID-19 pandemic, insurance has become increasingly essential in helping individuals mitigate financial shocks from unexpected adverse events. Nevertheless, insurers face the persistent challenge of premium pricing calibration, a process imperative for maintaining financial solvency and actuarial equity. Among various machine learning techniques, the Bayesian framework stands out due to its unique ability to incorporate new data in real-time, making it particularly suitable for dynamic risk environments. This study conducts a systematic review of Bayesian methodologies, emphasizing their deployment in risk assessment and actuarial pricing. It examines the strengths of Bayesian methods in uncertainty modeling across high-stakes industries, as well as their limitations—such as computational complexity, lack of interpretability, and sensitivity to prior assumptions. Furthermore, the investigation interrogates cutting-edge innovations—such as hybrid Bayesian-machine learning hybrids and Bayesian AI—designed to mitigate aforementioned constraints and extend the operational scope of Bayesian frameworks. This study concludes that while the Bayesian framework offers a powerful approach for dynamic risk modeling, its future practicality hinges on the development of hybrid models that can effectively balance predictive accuracy, interpretability, and computational feasibility. Future research should focus on real-world case studies to further validate these advancements.

Leveraging emerging blockchain technology and visionary metaverse concepts, digital collectibles have emerged as an indispensable force in the digital economy. However, developing markets are increasingly exposed to issues such as information asymmetry, technical vulnerabilities, and market manipulation, leading to disorder and hindering sustainable economic growth. The underdeveloped regulatory framework has yet to resolve these challenges effectively, making standardized development imperative. By constructing a multi-stage Stakelberg game model to analyze strategic interactions among regulators, platforms, investors, and consumers, this study proposes recommendations including appropriate policy intensity, optimized trading mechanisms, rational investment practices, and consumer education to facilitate the standardized evolution of the digital collectibles market.

With the rise of the Industrial Revolution, economic development and technological progress have been accompanied by increasingly severe environmental issues. Global warming poses threats and adverse impacts on humanity's long-term development. Many countries have begun taking measures to curb pollution, and the actions of developed nations have provided valuable experience for Developing a green financial system for a sustainable future. Therefore, green finance has emerged. Regarded as the world's largest industrial producer, there is a relatively high proportion of industrial carbon emissions in China. To achieve sustainable goals, China needs to focus on measures addressing industrial carbon emissions. In 2017, China launched the policy to set up pilot zones for green finance reform and innovations, aiming to explore effective pathways for green finance development through local pilots (GFPZ), thereby reconciling economic growth with environmental protection. The empirical strategy of this research is based on a difference-in-differences (DID) model, a quasi-experimental design used to estimate the policy's causal effect on industrial carbon emission intensity (ICEI). What is more, a conclusion could be found verified by the research---- this policy accounts for lessening industrial carbon emission intensity, and this effect could remain statistically significant under the employment of robustness tests.

As China's economy continues its rapid growth, hydropower station construction has emerged as a crucial pathway for converting regional resource advantages into economic benefits. Drawing on regional economic development theory and the characteristics of the hydropower industry, this study examines the Dachaoshan Hydropower Station as a case study. Through multiple research methodologies including case analysis and literature review, we analyze the mechanisms through which hydroelectric facilities influence local economic development from both direct and indirect dimensions. Our findings reveal that during the construction phase, hydropower stations effectively stimulate the development of local construction, building materials, and related industries through large-scale investment, while creating substantial temporary employment opportunities. During the operational phase, they provide stable employment positions and considerable tax revenue contributions, becoming an essential pillar of local government finances. From an indirect perspective, hydropower station construction drives the extension and development of related industries, optimizes regional infrastructure conditions, promotes green upgrading of industrial structures, and achieves sustainable regional economic development. The study also addresses the negative impacts on river ecosystems caused by hydroelectric facility construction and human control, as well as social issues related to resettlement. Our comprehensive assessment demonstrates that hydroelectric facilities significantly promote regional economic and social development, with positive effects substantially outweighing negative impacts. However, establishing comprehensive ecological compensation mechanisms and resettlement security systems remains necessary to achieve an organic unity of economic, ecological, and social benefits.

In the process of transitioning from traditional services to capital intermediation and wealth management, securities firms are facing increasingly complex risks, such as market volatility and credit defaults. Based on this, this study explores the risk management challenges faced by securities companies in the transformation of financial markets. Based on the method of literature analysis, this paper identifies five main risk categories faced by securities firms, namely, credit risk, liquidity risk, operational risk, technical risk and compliance risk, and deeply analyzes the multidimensional nature of risk driving factors, from external shocks to internal defects. This paper innovatively proposes a three-pillar risk management approach: (1) Technology Enablement Pillar, which significantly enhances risk identification transparency through the deployment of artificial intelligence real-time monitoring systems and blockchain regulatory technology solutions; (2) Governance Strengthening Pillar, which relies on the three lines of defense model and forward-looking stress testing to improve the risk management architecture; and (3) Compliance Innovation Pillar, which draws on the Sharia review mechanism of Islamic finance to develop a cross-cultural compliance monitoring system. Chinese securities firms need to upgrade their risk management system architecture,.This discovery is not only important for maintaining the stability of the capital market, but also provides Eastern experience for global financial regulatory reform.

Dividend policy constitutes a vital component of financial management for listed companies. As a key element of corporate finance, it directly influences shareholders’ investment decisions and serves as a crucial benchmark for evaluating a company’s value. Consequently, the rational implementation of dividend policy has become a significant topic within the field of corporate finance. This paper employs a single-case study method, focusing on Kweichow Moutai Co., Ltd. as the research object explore the motivations behind its high cash dividend policy and the subsequent market responses it triggered. The research indicates that Moutai’s high cash dividend policy is the result of a balance among multiple factors, is well - aligned with the company’s operational scale and cash flow status, and thus exhibits strong rationality. This study not only provides valuable references for formulating high dividend policies within the baijiu industry, but also offers a basis for investors to evaluate corporate value, and help capital markets in evaluating the worth of high-quality enterprises.

In recent years, the coffee industry in China has been expanding continuously, and consumers' demand for coffee has also been increasing significantly. However, the industry is also facing multiple challenges. Therefore, it is of practical necessity to study the main problems it is currently facing and analyze its solutions. This article focuses on studying the development status of the coffee industry in China and summarizes the three major problems at present: Firstly, the industry is highly homogeneous, and the competition is extremely intense, which has brought negative impacts; Secondly, the upstream supply chain of the domestic coffee industry is fragile. Most coffee enterprises rely on imported raw materials. Thirdly, at present, it is difficult to develop the lower-tier markets and change consumers' perceptions regarding coffee. In response to the above issues, this article has proposed corresponding solutions. Studies have shown that through brand innovation to reduce homogeneity, shorten the supply chain, receive government support, integrate into the lower market and reduce the development costs in that market, etc., it is possible to effectively alleviate the current predicaments faced by the Chinese coffee industry. This article effectively clarifies the problems currently faced by the Chinese coffee industry and provides several solutions. The research results can help the Chinese coffee industry alleviate some of the problems it is currently encountering, remove obstacles, and facilitate its faster development, as well as promote the more prosperous development of the industry.