To elucidate the dynamic equilibrium between urban land use efficiency (ULUE) and ecological carrying capacity (ECC) and to devise a bi-dimensional regulatory strategy that enhances economic performance while establishing ecological safeguards, this study employs panel data from the Beijing-Tianjin-Hebei (BTH) urban agglomeration spanning the period from 2014 to 2023. Utilizing the SBM-Undesirable model, comprehensive index method, and coupling coordination degree model to construct the ULUE and land ecological security index systems, we assess the spatiotemporal dynamics of ULUE-ECC coupling coordination within the BTH region. Results indicate a differentiated evolutionary trend among the 13 cities' coupling coordination indices from 2014-2023. Beijing and Langfang exhibited persistently high coupling coordination, while Tianjin and Shijiazhuang showed significant increases in coupling coordination. Conversely, cities like Tangshan and Hengshui experienced degradation in later stages. Spatially, regional coordination displays a "core-periphery" gradient, with central cities maintaining high-quality coordination while south-central Hebei and resource cities exhibit moderate dysfunction. Cross-sectional data from 2023 reveal an overall evolution toward higher-order coupling coordination, with an increased proportion of high-quality coordinated cities. However, localized ecological security risks are evident, exemplified by Tangshan's plummeting coupling coordination index, underscoring the staged imbalance between ULUE and ecological protection.

With the rapid development and maturation of the cryptocurrency industry, a large number of enterprises have emerged and come to the forefront in the market. Coinbase, a leader in the cryptocurrency exchange industry, has navigated volatile markets and evolving regulations through robust compliance strategies, continuous technological advancement, and user-centric services. Through a literature review, this paper investigates Coinbase’s business evolution, international expansion, and risk management frameworks, aiming to identify factors contributing to its sustained competitiveness. Meanwhile, by synthesizing industry reports and comparative analyses with peers such as Binance and Kraken, the research underscores Coinbase’s role as a compliance-driven innovator, offering a replicable model for digital asset platforms. Findings highlight the critical interplay between regulatory credibility, technological excellence, and user experience in fostering long-term competitiveness. These insights provide guidance for stakeholders seeking effective platform governance and plans to navigate the crypto economy’s complex landscape.

Drawing upon panel data from 41 prefecture-level cities in the Yangtze River Delta region spanning 2013 to 2022, this research employs a spatial Durbin model to examine how the digital economy affects new quality productivity. The results demonstrate that the digital economy substantially boosts local new quality productivity while simultaneously generating beneficial spillover effects for adjacent cities. Heterogeneity analysis indicates these positive impacts are particularly pronounced in both economically advanced areas and those receiving limited government financial support. Mechanism analysis further confirms that the digital economy drives new quality productivity growth and creates spatial spillovers through elevating regional innovation capacity. These findings elucidate the digital economy's operational mechanisms and practical impacts on new quality productivity enhancement, offering valuable insights for the Yangtze River Delta region to achieve high-quality development through digital economic advancement.

This study analyzes consumer preferences for Nintendo gaming consoles using conjoint analysis. Six factors—IP exclusivity, hardware performance, third-party support, storage expansion, backward compatibility, and pricing—are examined through a survey (N = 660). Regression analysis reveals that price is the most influential factor, while third-party support, storage expansion, and backward compatibility negatively impact preference. Surprisingly, IP exclusivity and hardware performance show no significant effects, indicating that Nintendo’s appeal relies more on affordability and gameplay experience than technical specifications. These insights highlight the importance of strategic pricing and innovation while suggesting that traditionally perceived weaknesses, like hardware limitations, may not be critical concerns for Nintendo’s target audience. The study also offers practical recommendations for Nintendo’s future market strategies.

Currently, the core directive of China's economic trajectory is "high-quality development", shifting corporate mandates from singular economic performance to integrate with environmental, social, and governance (ESG) factors. This paradigm aligns with the internationally advocated ESG principles. And domestic corporate ESG rating systems are becoming increasingly sophisticated, positioning ESG ratings as a potentially crucial metric for corporate evaluation. This study, utilizing data from Chinese A-share listed companies spanning 2010 to 2022, employs a two-way fixed-effects model, with corporate growth serving as a mediating variable, to investigate the impact of media attention on corporate ESG performance. The empirical findings reveal a significant positive correlation between media attention and corporate ESG performance. Mechanism testing indicates that media attention significantly enhances corporate growth. Heterogeneity analysis demonstrates a more pronounced impact of media attention on non-state-owned enterprises and those located in western regions. This research provides empirical evidence supporting the influence of media attention on corporate ESG ratings, offering a basis for governmental measures to regulate media organizations and refine ESG rating systems. Furthermore, it offers guidance to corporations on enhancing the diversity of ESG practices and effectively leveraging media engagement.

With the rapid advancement of large language models (LLM) technologies, new technical support and research paradigms have emerged for traditional accounting and finance studies. Despite these opportunities, scholars in the fields of accounting and finance often encounter challenges when navigating the extensive and complex domain knowledge of large language models, as well as the ever-evolving academic literature. To address this gap, this paper conducts a qualitative survey on the applications of large language models in early accounting and finance researches. This paper is structured into three main sections. First, it delves into the definition, underlying principles, and developmental trajectory of large language models. Second, it synthesizes the latest research on large language models applications in accounting and finance, categorizing these studies into three major domains, including sentiment analysis, report analysis and practical works. Finally, the paper highlights emerging trends and potential research directions, aiming to provide a comprehensive guide for future scholarly exploration in this dynamic field. Although it still has many shortcomings such as high cost and black box of process, the application of large language modeling provides a new technical support for text analysis in accounting and financial research, and also improves the actual efficiency of accounting and auditing.

This study investigates the impact of non‑performing loan (NPL) ratios on the price‑to‑book (P/B) ratios of financial institutions, using Ping An Insurance Company of China as a case study. Based on data from 2018 to 2024 and examining landmark real‑estate non-performing loan events—such as the defaults Baoneng Group and China Fortune Land Development—the research identify a clear three‑phase dynamic: (1) Stabilization (2018–2020), when NPL ratios remained below 2% and P/B ratios hovered between 1.8 and 2.2; (2) Divergence (2021–2023), marked by NPL surges from 1.8% to 6% alongside a steep P/B decline from 2.0 to 0.5; and (3) Partial Recovery (2024), with NPLs retreating to 4% and P/B ratios stabilizing near 1.0. Empirical analysis confirms a significant negative correlation between rising NPL ratios and P/B ratios, driven by increased loan‑loss provisions, asset impairments, and deteriorating market sentiment. These findings highlight the importance of robust credit risk management and early warning mechanisms to preserve asset valuations. The study concludes with policy recommendations for financial institutions and regulators, including enhanced risk monitoring, diversified credit exposures, and strengthened supervisory frameworks to mitigate the adverse valuation effects of non‑performing loans.

China's swiftly aging population has considerable health issues, wherein comprehensive pension insurance is crucial for alleviating physical and mental health deterioration among the elderly. This study takes data from the 2018 China Health and Retirement Longitudinal Study (CHARLS), concentrating on persons aged 60 and older, and performs Ordinary Least Squares (OLS) regression to assess the effects of pension insurance tiers. The findings indicate that comprehensive pension insurance markedly enhances both physical and mental well-being, with more pronounced impacts noted among urban dwellers and non-isolated seniors, largely mediated by self-assessed health status. These findings highlight systematic inequalities in benefit allocation. Policymakers must emphasize the expansion of rural coverage, expedite multi-pillar pension changes, and include community-based eldercare services to guarantee sustainable and equitable health results for China's aging demographic.

This paper focuses on constructing a criminal law regulatory framework for brushing and credit manipulation behaviors from the perspective of data crimes, conducting multidimensional analysis of such activities. Firstly, it elaborates on the research background, pointing out that brushing and credit manipulation behaviors hinder the healthy development of e-commerce, while existing civil and administrative regulatory mechanisms face implementation challenges and criminal legislation lags behind. These activities infringe upon the legitimate rights and interests of consumers, business operators, and e-commerce platforms, while also undermining fair competition order.Subsequently, the paper analyzes the constitutive elements and social harms of brushing and credit manipulation, exploring controversies surrounding criminal law intervention. The identified contributing factors include inadequate supervision by e-commerce platforms, complexities in applying criminal law to different entities, discrepancies in judicial rulings, and ambiguity in the definition of criminal offenses. To address these issues, this paper proposes constructing a criminal law regulatory framework for brushing and credit manipulation from the perspective of data crime. It puts forward solutions including strengthening supervision of e-commerce platforms, clarifying legal responsibilities of all entities, unifying judicial adjudication standards , and improving the application of relevant criminal charges. The objective is to effectively curb brushing and credit manipulation, thereby safeguarding the fair competition order in the e-commerce market and protecting the legitimate rights and interests of consumers.

Against the backdrop of worsening global ecological and environmental problems and the "dual carbon" goal, the promotion of agricultural green production technology is of great significance for achieving sustainable development. This article takes 200 households in Hongdong County, Shanxi Province as the research object. Based on the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM), a questionnaire survey and logistic regression model are used to systematically analyze the willingness of farmers to adopt green agricultural production technologies and its influencing factors. Research has shown that high upfront costs and insufficient market premiums are the main obstacles in economic factors; The perception of technological complexity significantly reduces the willingness to adopt; Policy support, especially subsidy policies, has the strongest effect on promoting adoption willingness; 50% of farmers in social networks have a neighborhood demonstration effect, and the significant improvement in environmental awareness promotes adoption. Based on this, policy recommendations such as increasing financial subsidies, optimizing the technical training system, and strengthening the social network dissemination effect are proposed to provide a theoretical and practical basis for the green transformation of agriculture.