This paper selected monthly time series data from both markets from January 2018 to December 2023. Data preprocessing and feature design were performed, and several experiments were carried out with LSTM, CNN-LSTM and Transformer as models. MAE, RMSE and LCE, which can achieve a lower 0.023, 0.031 and 0.018, respectively, with R2 =0.942, are achieved by TLAEFNA. The prediction accuracy and linkage feature capture are much superior to mainstream time series models, and are stable and robust when the data is insufficient and outlier interference is present. By implementing a visualization module, our algorithm intuitively presents linkage trends, attention weights and factor importance, which reveal the temporal and regional differences in the linkage between the real and securities markets and identifies the principal linkage factors such as housing price changes, real estate stock transaction volumes and funds and expectations transmission paths. This algorithm solves the black-box problem of machine learning that provides accurate and interpretable technical support for cross-market investment decisions, risk warnings and policy regulation.

Using 2014-2024 data from Chinese A-share listed companies, this research examines how inconsistent ESG ratings affect corporate supply chain resilience. Greater rating disagreement is linked to a notable drop in resilience. Industry competition amplifies this effect: higher concentration makes the negative impact stronger. The eastern region shows the strongest effect, while pollution level does not matter—heavily and lightly polluting firms are similarly affected. The results give fresh insight into ESG rating inconsistency and offer practical direction for regulators pursuing uniform ESG criteria, as well as for firms striving to boost supply chain resilience.

The relationship between supply chain finance and corporate off-site investment emerges a counterintuitive paradox: theoretically easing financing constraints to boost off-site expansion, yet in reality blocked by cross-domain trust fractures and institutional adaptation gaps. Using 2001–2024 A-share listed company panel data and a time-fixed effect model, this paper examines the impact, mechanism, and boundary conditions of supply chain finance on off-site investment scale and location choice. Results show a significantly positive effect, empirically supporting the core hypothesis. This effect operates through three pathways—reconstructing cross-domain credit evaluation, driving resource integration platforms, and upgrading cross-domain governance contracts—forming a closed loop of financial innovation, trust-capability reconstruction, and investment activation. Integrating financial geography, institutional theory, and social network theory, the study constructs a cross-domain supply chain finance analysis framework, fills the systematic research gap, and provides theoretical and policy basis for optimizing cross-regional capital allocation in building a unified national market.

Considering how deeply integrated is our dual-carbon objective with a digital economy now, what kind of corporate greenwashing would there be during that whole transition period into something called green development and maybe digital changes could give us some sorta tech route towards resolving this dilemma. A-Share companies from 2014 till 2023 as sample to explore what will happen after Digital Transformation of Corporate in Greenwashing through ESG information Disclosure along with ESG rating's mediating effect. It analyses the heterogeneous nature from three points: Region and industry technological characteristics, Pollution of industry. And also we have the following result here which indicates to me it's quite clear right away, if an organization does digital transformation they might actually reduce chances for it to just not look like there even existed this practice at all; furthermore those ratings given out concerning environmental standards can go from low up till really good when comparing everything about making money while trying one last chance instead than going over each others heads regarding doing more environmentally friendly things around here – because then nobody feels compelled anymore! From heterogeneity point-of-view view its inhibition of Digital change towards Green-washing shows strong signs within Companies found mainly inside areas where East exists alongside Tech Industry plus Pollutants Industries. And I passed robustness checks on my study. In this investigation is about showing digital transformations' environmental governance values for empirical support as well as references to both corporations for improving their disclosure practices and regulatory powers overseeing such actions called greenwashing and so forth helping our nation's growth towards becoming greener.

In August 2023, China's Ministry of Finance issued the Interim Provisions on accounting treatment of enterprise data resources, explicitly requiring that from January 1, 2024, qualified data resources of enterprises should be included in the balance sheet for confirmation. We regard the implementation of this policy as an exogenous shock event, select a-share listed companies from 2020 to 2025 as research samples, and use PSM-DID method to analyze the actual impact of policy implementation on stock price synchronization. The final core interaction coefficient is 0.079, which is significant at the level of 1%, indicating that the implementation of the data resource entry policy will significantly improve the stock price synchronization, this result is still valid after multiple robustness tests. The results of mechanism analysis are consistent with the expectation of noise trading theory: data assets are Intangible assets with high valuation difficulty, which will increase the uncertainty of market valuation on enterprises, it urges investors to be more inclined to follow the overall trading trend of the market, which will push up the synchronization of stock prices in the short term. This policy effect is more obvious in non-state-owned enterprises, which is related to the higher level of information asymmetry of non-state-owned enterprises themselves. This study fills the gap of relevant empirical research and can provide reference for regulatory authorities to adjust valuation standards and improve information disclosure rules.

The chain-oriented development of China's catering industry has maintained a continuous accelerating trend, and the deep penetration of digital technology is fundamentally reconstructing the underlying operation logic of the entire industry. Nevertheless, most chain catering enterprises have fallen into the cognitive misunderstanding of "high investment with low conversion" in the process of scale expansion. The popularization of digital tools including scan-code ordering and intelligent inventory management has not completely solved the core pain points in the industry, such as low ordering efficiency, high food material loss, and weak control capacity of headquarters. This paper selects Hefu Noodle, the benchmark enterprise in the domestic high-end pasta track, as the research sample. By combing the development context of the catering industry and the public operation data of the enterprise, combined with consumer evaluation data from the Dianping platform, this paper explores the action path of digital full-link transformation on enterprise operating efficiency, and verifies the moderating effect of consumer perceived value in this influence mechanism. The research results show that digital operation can achieve effective efficiency improvement from three dimensions: front-end customer service, mid-end supply chain management, and back-end enterprise management. Consumer satisfaction and repurchase intention can significantly amplify the enabling effect of digitalization. Meanwhile, factors including store opening years, operation scale and city level will lead to the heterogeneity of digital transformation effects. On this basis, this paper puts forward targeted practical suggestions, so as to provide reference for the digital transformation practice of similar chain catering enterprises.

With the rapid development of the digital economy and artificial intelligence, generative artificial intelligence (genai) has a profound impact on the brand strategy and market management of the luxury jewelry industry. As a tool, AI has the technology of content generation, database mining, and intelligent algorithms, which have changed the promotion and production of brand content in the luxury jewelry industry, and also promoted systematic changes such as market insight into consumers, user relationship management, and brand value communication. Based on the review method, this paper reviews the application progress of generative AI in luxury brand strategy and market management in recent years, focusing on the mechanism of brand marketing, consumer experience upgrading, brand value, market management, and brand authenticity maintenance. The analysis found that generative artificial intelligence, through big data planning and intelligent generation technology, has improved the overall upgrading of the luxury jewelry industry, optimized the market response ability and user demand of the luxury jewelry industry, and tested the scarcity and value shaping of luxury jewelry. On this basis, this paper further constructs the integration analysis of generative AI on luxury brand strategy, so as to provide theoretical reference and strategic enlightenment for future related research and enterprise practice.

This paper uses a tripartite game model to examine the dynamics of pricing power within the Chinese live-streaming e-commerce system, including anchors, platforms, and consumers. It investigates the impact of the concentration of power in the so-called super anchors on the resulting competition of a race to the bottom in terms of pricing, on the example of Meione (Li Jiaqi). The analysis shows that there is a strategic stalemate: anchors are competing over traffic by claiming the lowest price, platforms are competing over gross merchandise value (GMV), and consumers are competing over the highest utility. This is a cyclical phenomenon where brands lose value, which puts small and medium enterprises at a disadvantage and exposes platforms to systemic risks, which makes the status quo not sustainable. The result is a re-creation of the price that leads to deep discounting becoming the standard practice, which reduces innovation in the industry and long-term growth. To eliminate this dilemma, the paper introduces a transition to a paradigm and platform-led decentralization of value-led pricing and proposes exclusive services instead of discounts and brand-led broadcasting. The paper redefines the pricing crisis as a multi-stakeholder strategic game, which provides a systematic structure and practical measures to create a more balanced, innovation-friendly market in the post-traffic e-commerce world.

As a cornerstone of the capital market, bank stocks not only serve as the foundation of the financial ecosystem, but reflect market expectations for macroeconomic policies through their price fluctuations. This study focuses on stock price of six major state-owned banks in China from 2025 to 2026, screening for significant variables impacting daily closing prices. Since traditional OLS models often struggle with multicollinearity, this research uses LASSO model for variable selection and prediction, along with 10-fold validation and bootstrap examination to verify coefficient robustness. The results demonstrate that the study model can effectively explain stock price fluctuations using relevant variables and performs stably across different dimensions, which can provide empirical insights for both investors and regulators.

Dual Period: Digital & Environmentally Friendly Development Era. If we take digital transformation as a major catalyst that can push firms along the road where they will continue to make greener innovations, then such an idea does appear rather interesting both academically and commercially at this time. Use China A-shares listed companies from 2015-2024 for testing whether our theory holds true. We see that(1)Digital transformation makes corporate green innovation higher; every extra piece of digitization within any company leads to about .047% increase in its own particular worth.(2)Test on mediation says digital transformation raises corp green innov level via increasing inv efficiecy; (3). Analysis shows difference is good for people who don't pollute much, lots of R&D spending helps make things less bad. And these kinds of discoveries tell you some underlying reasons or causes why such a thing actually happens because of this type of change coming into being through improvements related to how much one might consider putting money towards something.