With the rapid development of social media and the widespread adoption of the internet, short video platforms have become an important part of consumers' daily lives. They have also become a significant medium for information acquisition, social interaction, and consumption decision-making. The rise of short video platforms has played a crucial role in the purchasing decisions of Generation Z. This study focuses on four key pathways: emotional arousal, social identity, platform algorithms, and user-generated content (UGC). It also explains them through real-life case studies. The research finds that short video platforms have changed the purchasing paths of Generation Z.This transformation is driven by immersive content, algorithm-driven distribution, and strong interactive features. Emotional drive, herd mentality, personalized recommendations, and trust in UGC jointly influence consumer behavior. Based on this, this paper proposes these recommendations: platforms need to enhance advertising transparency and standardize commercial content labeling. It should increase algorithm transparency and grant users the power to self-manage their data and guide consumers like Generation Z towards rational consumption.

Under the impact of iterations in artificial intelligence and big data technology, the traditional management accounting education system, centered on cost accounting, budgeting, and performance evaluation, fails to meet the new demands of enterprises for “data insight, algorithm mastery, and cross-domain collaboration” due to its static, isolated, theoretical, standardized, and process-oriented training orientation. This has resulted in a serious mismatch between learning and application. This paper mainly focuses on the theme of “AI empowering the transformation of the management accounting education system”. Through system architecture design, it explores three core issues: how the curriculum system can break through disciplinary barriers, how the school and enterprise can be upgraded synchronously, and how the traditional score-based evaluation mechanism can shift towards data-driven ability profiling. Add AI and data courses, intelligent iterative traditional courses, project-based flipped classrooms, teacher AI empowerment and school enterprise co-construction laboratories, and a data-driven multi-dimensional evaluation loop. Research has shown that this path can systematically enhance students’ abilities in AI and big data analysis, modeling, and coping with many contemporary uncertainties and risks, achieving a transition from “knowledge transmission” to “value creation” in management accounting education.

With the advent of the digital age, the digital economy has gradually become an important engine for meeting the people's growing needs for a better life, and its mutual complementarity with common prosperity has become an important guarantee for the high-quality development of the economy and society. Therefore, this paper focuses on the empowerment of the digital economy on the realization of common prosperity under its empowerment. The study finds that China's digital economy and common prosperity show an overall positive trend but with regional differentiation. It clarifies the development paths in the eastern, central and western regions, as well as the existing problems in coordination and the dimensions of assistance. It is pointed out that in the future, efforts should be made to promote the prosperity of the digital economy, optimize the industrial structure and market, and enhance innovation capabilities, so as to promote common prosperity.

This paper aims to explore the effectiveness of stock price prediction models based on ensemble algorithms by predicting the trends of the CSI 300 Index components. The study utilizes 20 feature variables from 242 trading days of the CSI 300 components in 2024, totaling 72,504 data points. Regression interpolation, DBSCAN and wavelet thresholding methods are employed to enhance data stability and quality. During the model construction phase, this study transforms the stock price prediction problem into a binary classification problem, using the direction of price changes in the denoised closing prices as classification labels. Two ensemble learning algorithms—Random Forest and XGBoost—are employed for modeling. Random Forest achieves predictions by constructing multiple decision tree models, with parameters set to n_estimators=500 and max_features=4. XGBoost further optimizes the boosting tree model and determines the optimal parameters through grid search. Both models use a 2:1 ratio to divide the training set and validation set, respectively, for model training and evaluation. XGBoost achieves a prediction accuracy of 55.76%, slightly higher than Random Forest's 55.46%.

In the context of the turbulent international economic situation, digital transformation promotes the deep integration of digital technology and production development, and provides new tools for enterprises to cope with increasingly frequent external shocks. This paper empirically examines the role of digital transformation in relation to the resilience of manufacturing firms based on microdata from 3,670 A-share listed manufacturing firms from 2013 to 2022. The outcomes reveal that by making firms more agile and responsive, digital transformation improves corporate resilience; however, heterogeneity analysis illustrates that digital transformation serves a more substantial part in boosting the resilience of state-owned enterprises (SOEs). The aforementioned results offer small-scale proof that enterprise resilience has been enhanced by digital transformation.

With the rapid development of artificial intelligence (AI) technology, more and more fields are beginning to use AI technology. Based on this, this paper studies the role of AI personalized recommendations and AI customer service systems in improving consumer satisfaction in e-commerce shopping, and adopts a questionnaire survey method to conduct empirical research on sample data. The results indicate that AI personalized recommendations and AI customer service systems have a significant positive impact on consumer trust, which in turn further influences consumer satisfaction. Consumer trust plays a significant mediating role between AI personalized recommendations and AI customer service systems, and consumer satisfaction. Furthermore, consumer trust has a significant positive impact on consumer satisfaction. Therefore, e-commerce platforms and merchants should pay more attention to consumers' needs and feedback regarding AI personalized recommendations and AI customer service systems in the future. By improving the user experience for consumers, it can further enhance their trust and satisfaction.

With the rapid growth of the sports industry, the scale and complexity of sports events have significantly increased. Consequently, risk management has become a critical component in ensuring the safety and efficient organization of such events. This study investigates risk management practices in sports event planning by employing a combination of literature review and case study methodology to systematically analyze the types, causes, and corresponding mitigation strategies of event-related risks. The research emphasizes key issues such as the systematic identification of potential risks and the establishment of effective risk assessment and response mechanisms. Through the examination of representative domestic and international event cases, this study reveals that risks associated with sporting events are characterized by diversity and dynamism. Therefore, a comprehensive management framework encompassing risk identification, evaluation, response, and continuous monitoring should be established. Technological advancements and interdepartmental collaboration play a pivotal role in enhancing the effectiveness of risk management systems. Nevertheless, this study acknowledges certain limitations, including restricted data coverage and insufficient exploration of emerging risks. Future research could focus on developing predictive risk models through the integration of artificial intelligence and big data analytics.

The rapid development of China’s new energy vehicle market has enabled Tesla to reposition itself as a technology leader and a strong competitor to local peers in the Chinese market. This study takes the 4P theory (product, price, channel, promotion) as a driving force to explore how Tesla can formulate a localized marketing mix strategy based on the complex and highly competitive Chinese market. Specifically, the survey found that Tesla maintained its technological leadership through OTA upgrades and rapid product iterations; its pricing strategy flexibly combines penetration and psychological pricing, with particular benefits derived from localized production. In terms of distribution, Tesla adopts a direct sales model and integrates online platforms with offline experience centers to enhance customer control engagement and brand control. In terms of promotion, the brand relies on social media dissemination, user content and Musk's personal influence to create an "earned media" effect. This paper not only provides an empirical case for understanding how multinational brands adapt to the Chinese new energy vehicle market, but also provides a reference path for domestic brands in the fierce market competition. At the same time, this study enriches the applicability and practical significance of the 4P theory in the high-tech industry under the background of digitalization.

The global entertainment industry is growing fast, and social media is now widely used. Because of this, fan culture has become an important part of the economy. It is still not clear how celebrity influence shapes fan tourism behavior. This study looks at fan tourism, which is travel driven by emotional connections to idols. It examines how idol attractiveness, social media interactivity, and emotional involvement affect the intention to travel. The study used both questionnaires (n=100) and interviews. The results support the research model. The findings show that idol attractiveness and social media interactivity both increase emotional involvement. In turn, emotional involvement strongly increases travel intention. This means that an idol's authenticity and skills, together with the interactive nature of platforms like Weibo and Douyin, are important for building deep emotional ties that lead fans to travel. Based on these results, the study suggests several strategies for tourism stakeholders. These include working with local celebrities and influencers, creating fan-focused travel products like "Follow the Idol's Footsteps" tours, using social media to share fan-made content to build emotional connections, and adding emotional storytelling to marketing campaigns.

With the advent of the new retail era and the development of the e-commerce economy, online shopping has become a new way of consumption for residents, and a growing number of silver-haired groups are starting to explore online shopping. The silver economy presents enormous potential in the context of online shopping. This paper focuses on the silver-haired generation and establishes a model to analyze the characteristics and influencing factors of their online purchasing behavior. The independent variables of the model are the silver-haired generation's willingness to engage in interaction on online shopping platforms and their perceived value, the mediating variable is customer satisfaction, and the dependent variable is their purchase intention. Based on the model, this study designed a questionnaire validation and data analysis, and concluded that the silver-haired generation's willingness to interact on online shopping platforms and their perceived value increases their purchase intention by enhancing customer satisfaction. On the basis of this conclusion, this paper suggests that online shopping platforms can increase interaction and explanation to control the silver-haired customers' perception of functional, economic, social, and other values to enhance their satisfaction, and drive them to generate purchase intentions, thereby stimulating the vitality of the silver economy.