In this paper, a kernel Extreme Learning Machine (KELM) model based on vector weighted average algorithm is proposed for the prediction of national tax revenue ratio, which provides a new way of thinking and method for tax revenue prediction. By analyzing the correlation between each index and tax share, it is found that gasoline price and life expectancy are significantly positively correlated with tax share, while fertility rate and birth rate are significantly negatively correlated. The model shows excellent predictive performance on both training set and test set, with an R² of 0.995 in training set and 0.994 in test set, indicating that the model has excellent generalization ability. In addition, the root mean square error (RMSE) of the training set and the test set are 0.185 and 0.177, respectively, and the relative prediction deviation (RPD) is 14.234 and 13.178, respectively, which further verifies the high accuracy and stability of the model. Scatter plots of actual predicted versus actual values show that the model is able to accurately capture trends in tax shares with little prediction error. In summary, the optimized KELM model proposed in this paper not only has excellent performance on known data, but also has good expansion ability, and can be effectively applied to the tax share prediction of unknown data, providing a reliable tool for relevant policy making and economic analysis. The research of this paper provides a new technical path for the field of tax forecasting, which has important theoretical significance and practical value.

Based on a structural equation model (SEM), this study takes the Jellycat brand as the research object to explore the factors influencing consumers’ purchase intentions toward plush toys. First, grounded theory was applied to categorize the results of in-depth interviews, and a questionnaire was designed accordingly. A random sampling survey was then conducted in selected urban districts of Shijiazhuang. Based on the survey data collected, a structural equation model was constructed, incorporating four variables: perceived usefulness, perceived ease of use, brand value alignment, and price perception, all of which are hypothesized to influence purchase intention. Subsequently, the model was used to analyze the degree of influence and standardized path coefficients of these four variables. The results show that brand value alignment, perceived usefulness, price perception, and perceived ease of use are all highly correlated with consumers’ purchase intention. Finally, based on the path analysis results, the study proposes multidimensional and constructive suggestions for plush toy brands, including developing brand values, optimizing product design, and balancing brand positioning with value for money.

This study used service design theory as guiding methodology and focused on the intersection of intangible cultural heritage and disability services. It explored how to realize the two-way value creation between the development of intangible cultural heritage and the employment of people with disabilities through digital platforms. This passage first examined and analyzed the current situation and dilemmas in the development of intangible cultural heritage and disability services. After learning about the gaps and disconnections in relevant industries, the author's team understood the needs of each user through user interviews, and designed a service system map with a logical chain of 'Co-creative Design—Processing and Production—Public Welfare Dissemination—Consumption and Donation'. The Kano questionnaire was designed and distributed to understand users' concerns about the platform's functionality. User requirements were classified and ranked using the Kano model to propose the functional modules and priority settings included in the app for intangible cultural heritage helping people with disabilities. This has led to the conception of a prototype platform for cultural services helping the disabled that can be co-created by multiple parties. The design met the needs of creators, consumers and social expectations. It provided ideas for the research and development of intangible cultural heritage helping people with disabilities APP, and promoted the dynamic inheritance of intangible cultural heritage and social integration and self-worth of the disabled.

In the context of the digital economy, Enterprise Digital Transformation (EDT) is widely regarded as a key pathway to achieving sustainable development and enhancing competitiveness. This paper systematically reviews recent empirical studies on the digital transformation of Chinese enterprises, examining the driving roles of multiple factors such as policy support, digital finance, environmental pressure, and geographical location. It also summarizes the economic outcomes of EDT, including improvements in productivity, promotion of green innovation, enhancement of investment efficiency, and mitigation of greenwashing behavior. The findings suggest that the main drivers of EDT include policy and regulatory frameworks, financial mechanisms, and managerial attention to environmental issues, while its effects are primarily reflected in green performance and innovation efficiency. This study provides theoretical insights and policy implications for understanding the digital transformation pathways of enterprises in developing countries and for formulating high-quality development strategies driven by digitalization.

Environmental, social, and governance (ESG) practices are becoming essential components in modern corporate strategy and investor decision-making. This paper explores the strategic value of integrating ESG policies into business operations to promote long-term sustainability and mitigate environmental, regulatory, and reputational risks. Drawing from a comprehensive review of existing literature and industry case studies, the study argues that ESG implementation can enhance operational efficiency, attract sustainable investment, and build stakeholder trust. Companies such as IKEA and H&M are used as real-world examples to illustrate the potential benefits and challenges associated with ESG transformation. Although some researchers question the short-term financial returns of ESG adoption, the long-term strategic advantages, including improved brand resilience and access to green capital, are significant. The paper emphasizes that ESG programs are most effective when they align with a company's core capabilities and market positioning. In an era of heightened stakeholder expectations and evolving regulatory environments, ESG integration is not only a moral imperative but a business necessity. The study concludes that firms adopting ESG proactively are better positioned to achieve sustainable growth and competitive differentiation.

In the rapidly evolving digital economy, startups and small businesses face significant challenges in striking a balance between cost efficiency and effective customer engagement. WhatsApp, traditionally known as a peer-to-peer messaging platform, has emerged as a transformative e-commerce solution for new brands seeking to establish a market presence. This research brief examines how WhatsApp's business features, including chatbots, personalized communication, and real-time interactions, enable startups to reduce operational costs, enhance customer loyalty, and reach diverse markets. Case studies from Mexico, Indonesia, and the Middle East demonstrate WhatsApp’s potential in engaging older adults, rural populations, and underserved communities, contributing to inclusive economic growth. The findings suggest that WhatsApp is not merely a messaging app but a strategic asset that supports sustainable development and long-term success for emerging brands in the global digital landscape.

With the development of big data technology, enterprise strategic management faces a major opportunity to transform from experience-driven to data-driven approaches. This paper analyzes the application scenarios and technical pathways of big data in strategic management, and proposes methods for optimizing enterprise strategy. These methods include building an enterprise-level data resource pool, applying machine learning to assist strategic formulation, and establishing a data-driven performance evaluation system. By introducing heterogeneous data integration, real-time collection, and intelligent analysis techniques, the scientific rigor of strategic planning and the agility of execution are enhanced.

This paper develops an evaluation system for digital economy development comprising 5 primary indicators and 13 secondary indicators, and applies the entropy method to calculate the overall digital economy development index in China from 2014 to 2022. Simultaneously, female employment—including its quantity, structure, and quality—is incorporated into the evaluation framework for precise measurement. Theoretical and empirical analyses reveal that the digital economy exerts a significant positive impact on the quantity, structure, and quality of female employment. Moreover, digital economy development not only increases the number of female-friendly jobs but also enhances their quality. The degree of influence varies by education level, age, and industry, with highly educated and younger women benefiting the most. Overall, the impact of the digital economy on female employment exhibits diversity and differentiation.

This paper reviews the development of Macao’s marine economy over the 25 years since its return to China, with a particular focus on its economic structure, industrial layout, future development potential, and possible challenges. Although Macao is a coastal city endowed with relatively abundant marine resources, the development of its marine economy has lagged behind. By analyzing the current state, opportunities, and challenges of Macao’s marine economy, this study explores how policy support and technological innovation can be leveraged to promote its sustainable development.

The green finance reform and innovation pilot zone policy aims to alleviate financial constraints on green technological innovation along the new energy vehicle (NEV) industry chain through diversified financial instruments. Based on data from listed NEV companies on the Shanghai and Shenzhen A-share markets from 2012 to 2022, this study uses a quasi-natural experiment involving three batches of pilot zones (established in 2017, 2019, and 2022) to construct a staggered difference-in-differences (DID) model to assess the policy's impact on green technological innovation. Results show that the pilot zone policy significantly promotes green technological innovation among NEV-related enterprises. The policy indirectly drives innovation by increasing R&D investment. However, financing constraints weaken the policy’s effects, while firms with stronger financing capabilities benefit more. The policy impact is more pronounced for state-owned and central-western enterprises. This study provides three key insights for optimizing green finance policy: addressing financing difficulties of non-state-owned enterprises, improving the financial support system, and implementing regionally differentiated support strategies.