Against the context of further expansion of digital economy plus industrial restructuring and upgrade, digital supply chains serve as a core pillar to raise the overall development standard of industrial networks and strengthen supply chains' ability to withstand market shocks. This paper takes China's digital supply chain as its research object, deeply analyzing the practical difficulties faced by enterprises, technologies, collaboration, and industries, and proposing targeted solutions. The study finds that China's current digital supply chain is characterized by policy-driven growth, leading enterprises, and the practical application of technologies, with significant achievements in large-scale applications. However, it still faces problems such as insufficient transformation momentum, fragmented technology application, prominent information barriers between upstream and downstream sectors, and lagging standards and regulatory systems. For digital supply chains to achieve robust and sustainable progress, businesses ought to lay out long-term strategies, upgrade internal capabilities, speed up technological integration and data interoperability, create mutually beneficial industrial cooperation ecosystems, and perfect industry norms and relevant regulations. The conclusions drawn from this research can offer actionable guidance for domestic firms and industrial clusters to carry out digital upgrades across their supply networks.

During the 2026 Spring Festival, China launched a pilot policy in 50 cities allowing consumers to scan QR codes on receipts for random cash rewards, supported by 1 billion yuan in central funds. This study examines how this micro-level tool simultaneously stimulates consumption and enhances tax administration, thereby driving economic growth. The research identifies a unique dual-channel mechanism. On the consumption side, the policy leverages the mental accounting effect, in which consumers categorize lottery winnings as Windfall Gains, thereby significantly increasing their marginal propensity to consume (MPC). Furthermore, these immediate cash inflows effectively alleviate liquidity constraints for low-asset groups, enabling small incentives to be converted into immediate spending. On the taxation side, the lottery incentives establish a Reverse Supervision mechanism that transforms consumers into real-time auditors. Combined with conditional cooperation, requesting invoices becomes a personal choice and then a widespread social norm, thereby improving tax compliance and expanding the tax base. In conclusion, the policy triggers a virtuous cycle in which increased household consumption (C) and expanded government spending (G) collaborate to drive endogenous growth in national income (Y). These findings provide practical insights for developing economies facing the dual constraints of tax leakage and insufficient domestic demand.

As a vital component of the national economy, the real estate sector sees housing price fluctuations that not only on the functioning of the property market itself but also, through channels such as the wealth effect, credit constraints, further influence economic development. This paper focuses on the U.S. housing market and discusses how changes in housing prices may affect economic growth, people's daily lives, social inequality, population movement, and regional development. Housing prices are not only a market indicator. To examine this issue, the paper reviews existing studies, compares relevant indicators, and uses quantitative analysis based on publicly available data. A time-series regression model is also built to explore the possible links between housing prices and broader economic outcomes. The results show that rising housing prices may support economic growth in the short run through the wealth effect and real estate investment. But if housing prices increase too quickly, they can also create heavier housing burdens for families and reduce their ability to spend on other goods and services. High housing prices may also affect young families' willingness to have children or move to other places. In addition, rapid increases in housing prices can make the wealth gap between homeowners and non-homeowners even larger. On the other hand, falling housing prices may help some people afford homes more easily. However, if the decline is too sharp, it may also create pressure on financial stability and negatively affect regional economic development.

As a deep cultural norm, the traditional gender concept continues to affect the career development of married women in China. This study focuses on the core issue of "how traditional gender concepts hinder the career promotion of married women in China." Based on gender theory, role conflict theory and concept system mutual construction theory, this study constructs a three-dimensional chain analysis framework of "concept internalization-family division of labor-organizational evaluation," and systematically reveals the internal mechanism by which traditional gender concepts hindering the career promotion of married women. The study yields three main findings. First, traditional gender concepts constitute a compound system of barriers through three paths: concept internalization, family division of labor, and organizational evaluation, each acting on individual psychology, family interaction, and organizational structure. Secondly, the three paths are nested and circularly strengthened, forming a vicious cycle of "concept internalization → housework division → organizational evaluation → re-internalization", which makes the traditional gender concept self-reinforcing. Thirdly, the hindering effect shows significant group heterogeneity, and married women with lower educational levels and young children face more severe promotion difficulties. Based on the above conclusions, this study puts forward intervention suggestions from the four dimensions of concept remodeling, family support, organizational change and social policy.

With the development of green finance and the progress of global climate governance, climate-related financial instruments, especially energy and carbon derivatives, have become increasingly important in modern financial markets. This paper examines the pricing mechanisms and risk management of derivatives under uncertainty in the carbon market. By combining literature review with market analysis, this study synthesizes classical derivative pricing models including the Black–Scholes and Heston frameworks, and extends their applicability to the pricing of energy, weather, and carbon derivatives. This paper further analyzes the structural differences across these markets and identifies key sources of risk, including volatility, policy uncertainty, and liquidity constraints. The results indicate that carbon risk has become a key new element in the pricing of derivatives and in portfolio management. This study finds that effective carbon risk mitigation can be realized via integrated strategies including cross-hedging, asset diversification, and scenario-based stress testing. This paper contributes to the literature on climate finance by offering a systematic framework for understanding derivative pricing and risk management under carbon market uncertainty.

In the context of the rapid development of global social e-commerce and TikTok Shop's breakthrough in business format based on content planting, this paper takes TikTok Shop as a research case to explore the influence mechanism of platform algorithm, talent and live broadcast on consumers' purchasing behavior. Based on literature review and industry open data analysis, the research finds that: firstly, platform personalization algorithm relies on users' browsing and interactive data to accurately push goods, which leads to a large number of unplanned impulse consumption; Second, bloggers rely on content credibility and circle influence to build user trust, and rely on word of mouth to drive product transformation; Third, live real-time interaction and limited-time concessions create a consumer atmosphere, further stimulating instant orders. At the same time, the existing algorithms of the platform induce four kinds of shortcomings: irrational consumption, uneven quality control of goods, privacy leakage and false propaganda of talents, which restrict users' retention for a long time. This study enriches the consumption theory of discovery e-commerce, which can provide practical reference for TikTok and similar content e-commerce to optimize platform rules, improve quality control and privacy management, and refine operations.

With the intensification of global consumer electronics market competition, AIoT and intelligent vehicles have become core growth tracks for technology enterprises. As a leading Chinese technology brand, Xiaomi Corporation relies on the "Hardware + Internet + New Retail" business model to build a diversified layout covering smartphones, AIoT devices, internet services and smart vehicles, and further launches the Human-Car-Home full-scene ecological strategy. Based on literature research, case analysis, PEST and Porter's Five Forces models, this paper systematically analyzes Xiaomi's business model, competitive advantages and operational challenges. This study finds that Xiaomi's core competitiveness stems from ecological synergy and efficient supply chain cost control, while it faces bottlenecks including insufficient high-end brand influence, continuous capital pressure of the vehicle business, global geopolitical risks and multi-business management challenges. This paper puts forward targeted optimization strategies for Xiaomi's sustainable development, and provides practical references for the transformation of similar consumer electronics enterprises.

Using literature analysis, comparative analysis, and framework construction, this study examines how several research streams respond to concrete problems in enterprise financial supervision. Regulatory technology is used to explain how compliance review can move from checking documents to tracing transaction data. Big data accounting helps clarify why financial evidence now includes not only vouchers and ledgers, but also contracts, delivery records, electronic invoices, payment data, tax declarations, and system logs. Continuous auditing addresses the problem of delayed risk detection by showing how abnormal transactions may be identified during the business process rather than only after closing or reporting. Audit analytics provides methods for comparing cross-system evidence and identifying inconsistencies among business flow, invoice flow, fund flow, tax flow, and accounting flow. Enterprise risk management is used only as a supporting perspective to explain how these financial risks can be classified, escalated, reviewed, and corrected inside the enterprise. This study finds that financial risk increasingly appears as inconsistency among business flow, invoice flow, fund flow, tax flow, and accounting flow.

As a new type of productive force in the era of the digital economy, computing power has become the core engine driving enterprises' artificial intelligence (AI) innovation. However, existing literature mostly focuses on policy effects at the macro level, and research on how computing power specifically drives enterprises' substantive innovation at the micro level is still relatively lagging. Based on the data of A-share listed companies from 2017 to 2023, combined with manually collected IDC licenses, this paper constructs an enterprise computing power database and empirically tests the impact of computing power deployment on digital technology innovation. The study finds that: ① Computing power deployment significantly promotes enterprises' substantive innovation by expanding the breadth of AI technology application and the degree of digital transformation. ② Mechanistically, computing power breaks the "data silos" by lowering technical thresholds, expanding application scenarios, and improving data integration capabilities, reconstructing the logic of R&D and production, thus forming a dual empowerment path. ③ Heterogeneity analysis shows that the innovation effect of computing power is more significant in non-state-owned enterprises and high-tech enterprises due to fewer institutional barriers and higher technical sensitivity. This study fills the micro-empirical gap in computing power economics, provides policy basis for optimizing computing power resource allocation and promoting high-quality enterprise development, and emphasizes the need for differentiated support for non-state-owned enterprises and high-tech enterprises to strengthen the synergy of data factors.