By virtue of its mature, multi-fragmented synergistic profit system, the Japanese anime industry has secured its position as a global leader. Using literature review and case study methods, this study analyzes the five core profit models of this industry: the production committee model, character merchandising, global windowing strategy, transmedia development, and cinema–music collaboration. In light of the challenges faced by China’s animation industry, such as lack of synergy across the industrial chain, delays in derivative product development, and weak international expansion capabilities, targeted optimization paths are further proposed: building a production committee–type industrial alliance, implementing synchronous development of films and derivative products, establishing a full-cycle IP management system, and enhancing cultural translation and international operation capabilities. This study provides a development framework with both theoretical value and practical guidance for China's animation industry to break through the bottleneck of profitability and enhance its international competitiveness.

China is currently grappling with a critically low fertility rate and rapidly aging population, both of which pose significant threats to its long-term socioeconomic sustainability. Despite the relaxation of the one-child policy, the fertility outcomes remain far below replacement levels, indicating that policy alone is insufficient. This study shifts focus from fertility intentions to the realization of these intentions, examining the impact of regional income inequality on the fertility gap—defined as the difference between an individual's ideal and actual number of children. Using panel data from the China General Social Survey (CGSS) spanning 2013 to 2023, this research employs a two-way fixed effects model at the province and year levels. Results indicate that higher regional income inequality significantly widens the fertility gap, primarily through intensifying individuals' sense of relative deprivation and lowering their perceived socioeconomic status. Furthermore, the heterogeneity analysis indicates that this negative impact is more pronounced among urban residents, individuals aged 30-40, and those residing in the eastern regions of China. These findings underscore the need to address economic inequality and implement targeted policy interventions to foster a more fertility-supportive environment.

This passage examines how the Myers-Briggs Type Indicator (MBTI) influences policy implementation, focusing on the mediating role of cognitive styles and adaptive strategies. In recent years, the Myers-Briggs Type Indicator (MBTI) has attained unprecedented global popularity, transcending the boundaries of professional fields and social contexts. It is developed by Isabel Briggs Myers and her mother Katharine Cook Briggs based on Jung's theory of psychological types. Building on Jung’s foundational framework, their work transformed it into a practical, accessible tool—one designed to systematically categorize and explain the nuanced variations in individual personalities. Its widespread adoption is evident across diverse domains. Through formal studies, it can be concluded that S-type individuals, with detail-oriented cognitive styles, tend to enforce policies rigidly, while N-type individuals, favoring holistic thinking, are more innovative. Connected with the "ambiguity-conflict" model, further patterns emerge: J-type personalities excel more in low-ambiguity, structured policy environments, whereas P-type personalities perform better in flexible, experimental settings. These MBTI-related differences collectively give rise to biases in policy implementation. This research enriches policy implementation literature by integrating personality psychology, offering insights for aligning individual traits with policy demands to optimize execution.

Climate change and global energy security have emerged as core challenges for countries worldwide, rendering energy transition a pivotal strategy to achieve low-carbon development. As a pioneer in renewable energy development, Germany achieved significant progress in energy transition during Angela Merkel's tenure, providing valuable experience for China. This study aims to systematically analyze the policy framework, implementation paths, as well as effectiveness and limitations of Germany's energy transition under Merkel's administration. By combining the current status of China's energy transition, it further puts forward targeted insights to offer references for China's achievement of the "dual carbon" goals. This paper adopts research methods including literature analysis, data analysis, and case study methods. So, In Germany, legislative safeguards, the participation of multiple stakeholders, and the setting of phased goals have been crucial to its success; however, high costs and unbalanced sectoral transition stand out as its prominent limitations. For China, the study concludes that it should balance the clean utilization of coal with the development of renewable energy, improve the legal system, activate market forces, and deepen international cooperation to advance the energy transition in a steady manner.

In recent years, the digital economy industry in China has developed vigorously, gradually becoming an important supporting force to promote China's economy, and the development of the digital economy has also affected China's labor market. This paper focuses on the impact of digital economy development on China's labor employment and corresponding strategies. First, this paper cites relevant data to clarify the significant role of the digital economy in economic growth, as well as the current status and structural contradictions in labor employment. Subsequently, it analyzes the impacts of the development of the digital economy on labor employment from both positive and negative perspectives. Positively, it creates job opportunities, enhances employment efficiency, and improves workers' skills. On the negative side, it gives rise to structural unemployment, exacerbates employment inequality, and brings to the fore challenges related to rights protection. Finally, it proposes measures such as strengthening digital skills training and promoting industrial integration, emphasizing the need for multiple measures to achieve a positive interaction between the two.

This study analyzes Japan's environmental parameters, focusing on rainfall patterns, surface temperature dynamics, vegetation distribution, forest cover, snow cover extent, and water resource availability. Using a qualitative analytical approach, the research addresses Japan’s geographical diversity, complex socio-institutional frameworks, and specific policy contexts. The primary emphasis is on surface temperature trends, examined through publicly available meteorological datasets and policy analysis. Results reveals two major patterns: (1) long-term warming since the 20th century (Greater Tokyo Area up 3°C in 100 years, driven by urban heat islands); and (2) spatial disparities (e.g., more summer extreme heat in subtropical Kyushu, shortened cold seasons in Hokkaido). Ecological impacts include altered temperate forest phenology (e.g., earlier beech flowering), reduced alpine snow affecting meltwater-dependent rivers, and higher forest fire risks in drought-prone areas. Policy gaps are evident: inadequate regional differentiation in national climate policies (e.g., uniform emission targets ignoring urban-rural thermal gaps); poor integration of meteorological data into micro-ecosystem protection (e.g., neglecting heat-induced agricultural pests); and insufficient urban planning regulations for heat island mitigation (e.g., limited green infrastructure mandates).

Amidst the wave of the digital economy, the data element is fundamentally reshaping the corporate competitive landscape. Emerging "Ultra-fast Fashion" retailers, epitomized by SHEIN, have risen rapidly through a unique data-driven business model, posing both a challenge and a complement to traditional theories of core competence. This paper aims to dissect the internal composition of "Data-Driven Core Competence" (DDCC) and systematically unveil its formation mechanism and evolutionary path from "data to value." Employing an in-depth single-case study methodology, this research analyzes multi-source secondary data on SHEIN. The findings propose a four-stage dynamic evolution model for DDCC formation: "Data Sensing – Algorithmic Insight – Capability Embedding – Value Co-creation." This model reveals that DDCC is not a static resource but a dynamic capability system, continuously self-reinforced and propelled by a "Data Flywheel." Through digital management that transcends organizational boundaries, SHEIN deeply integrates supply chain members, global consumers, and data elements into a cohesive digital ecosystem, thereby unifying distributed production with centralized management. This has enabled the company to successfully exploit the "attitude-behavior gap" among Gen Z consumers regarding sustainability perceptions and consumption patterns. Theoretically, this study integrates the Resource-Based View (RBV) and the Dynamic Capabilities View (DCV) in the digital consumption context, thereby deepening the understanding of core competence. Practically, it provides an actionable strategic framework and implementation path for enterprises seeking digital transformation, particularly those in cross-border e-commerce and traditional manufacturing.

Yang, drawing on his inframarginal economics framework, argued that China's dual-track reforms would fail without constitutional shock therapy, predicting that the absence of proper institutional transitions would lead to corruption and economic stagnation. Conversely, Lin's New Structural Economics advocated for gradual reform based on comparative advantages, arguing that late-comers could benefit by developing industries aligned with their factor endowments. This essay examines the 2002 to 2003 debate between economists Justin Yifu Lin and Xiaokai Yang regarding China's economic reforms and late-comer advantages. Through an analysis of recent empirical evidence (2020-2025), this essay demonstrates that Yang's predictions largely failed to materialize: China's dual-track system succeeded despite lacking constitutional transformation, with state-owned enterprises contributing positively to growth and anti-corruption campaigns improving productivity. However, Lin's framework also proves insufficient in explaining China's success. The paper concludes that economic forecasting necessarily sacrifices scientific rigor in favor of broad generalizations, suggesting that economics should focus on explaining existing phenomena rather than predicting uncertain futures.

Based on existing literature on green supply chains in cross-border e-commerce and relevant data results, this study constructs an improved G-SCOR model that integrates cross-border indicators (such as carbon tariff sensitivity). To scientifically quantify greenness, the research first combines the Analytic Hierarchy Process (AHP) and entropy weight method to determine the weight of indicators, and then establishes a fuzzy comprehensive evaluation model. It applies and validates the model through practical examples from JD.com and Amazon. The results show that Amazon achieves a 90% carbon reduction primarily through sea transportation (accounting for 65%), with AI optimization reducing mileage by 19%, but the packaging recycling rate is only 52%; JD.com's policy-driven recycling rate reaches 74%, and blockchain reduces dispute-related returns by 30%. The model scoring reveals a dual-path differentiation: policy-driven (JD.com) excels in recycling and planning, while market-driven (Amazon) excels in logistics efficiency. The conclusion calls for the establishment of standardized carbon accounting protocols and international EPR mutual recognition to promote cross-border green collaboration.

Throughout recent global shocks, the economy was impacted by recessions and widespread unemployment caused by quarantine measures and social restrictions, with the tertiary service and healthcare sectors being the most severely impacted. This study, based on secondary data, summarizes the effects of the economic downturn on the labor market and analyzes employment trends and inequalities among female workers. Using data from the International Labour Organization (ILO), it examines gender consistency, employment biases against women, and underlying causes of inequality from sociological and ethical perspectives. The results indicate that the unemployment wave triggered by the economic recession is not directly correlated with impacts on women’s employment. Instead, the main factors contributing to female unemployment are the need for flexible working hours and the time costs associated with childcare. To lower the risk of unemployment among women, targeted employment policy support should be provided at the policy level, while female workers need to enhance their competitiveness, such as by acquiring digital or AI-related skills, to adapt to the changing labor market.