The Yangjiabu Kite Festival, originating over 2000 years ago in Shandong Province, China, stands as a testament to the enduring cultural heritage and artistic traditions of kite flying. This research explores the historical origins, cultural symbolism, festival format, community engagement, and international exposure of the Yangjiabu Kite Festival, shedding light on its evolution and impact over time. Findings reveal the festival’s deep roots in ancient Chinese traditions, its role as a platform for showcasing cultural diversity and craftsmanship, and its significance in promoting tourism, cultural exchange, and soft power projection for Shandong Province. Lessons learned from the Yangjiabu Kite Festival offer valuable insights for cross-cultural application, event management, cultural diplomacy, and community development. Suggestions for future research include comparative studies, longitudinal assessments, audience research, and policy analysis to further explore the dynamics and implications of cultural festivals in a global context. Overall, the research underscores the importance of cultural festivals as vehicles for cultural preservation, tourism promotion, and intercultural dialogue, fostering mutual understanding and appreciation across borders.

The rapid rise of live streaming commerce in China has transformed the retail environment, with electronic word-of-mouth (eWOM) emerging as a pivotal factor in shaping consumer behavior. As a digital evolution of traditional word-of-mouth, eWOM gains particular significance in live streaming contexts, where real-time interactions foster immediacy and engagement. This study investigates how eWOM influences consumer purchase intentions within Chinese live streaming platforms, employing the Information Adoption Model (IAM) as theoretical framework. Using a grounded theory approach, this research applies NVivo for data coding and analysis to explore the cognitive and emotional processes triggered by eWOM during live streaming. Findings indicate that argument quality, source credibility, and information quantity significantly enhance consumer trust and perceived usefulness of information, which, in turn, drives information adoption and purchase intention. Furthermore, the study reveals that social interaction between live streaming anchors and audiences amplifies the influence of consumers’ internal states on information adoption. This study enhances the Information Adoption Model (IAM) by introducing social interaction as a moderator between consumers’ internal states toward live streaming eWOM and their adoption of information, highlighting the value of social interaction in live streaming. It also incorporates information quantity, showing how eWOM quantity affects trust and perceived usefulness. Furthermore, the study contributes to exploring how factors like argument quality, source credibility, and information quantity shape consumer trust and perceived usefulness, offering insights into the cognitive and emotional processes of information adoption in live streaming.

The research aimed to: 1) analyze components and indicators of digital transformation leadership among school administrators, 2) assess their leadership needs, and 3) develop mechanism models to promote this leadership. A mixed-method approach was applied, involving three sample groups: 8 experts, 406 administrators, and 7 experts. Data collection tools included semi-structured interviews, leadership scales, needs assessments, and focus group discussions, with analysis performed through construct validity testing, needs assessment, and content analysis. The findings revealed: 1) The components and indicators of digital transformation leadership showed structural validity, as confirmed by the model’s alignment with empirical data (Chi-Square = 82.3, df = 65, p = 0.072, CFI = 0.998, TLI = 0.997, RMR = 0.00965, RMSEA = 0.0256). 2) Among the leadership components, “innovative knowledge” ranked highest in need (PNImodified = 0.075), followed by “ideological influence” (0.066), “consideration of individuality” (0.055), “intellectual stimulation” (0.052), and “inspiration” (0.053). 3) Mechanism models for promoting leadership emphasized enhancing these five components to strengthen administrators’ skills in applying technology, managing teaching and development plans, and fostering innovation. Administrators were encouraged to tailor strategies to individual needs, inspire personnel, and create a commitment to organizational change and development. These mechanisms aim to equip administrators to effectively lead transformations, motivate staff, and drive educational institutions to adapt and thrive in evolving environments.

Since the proposal of the low-carbon economy plan, all countries have deeply realized that the economic model of high energy and high emission poses a threat to human life. Therefore, in order to enable the economy to have a longer-term development and comply with international low-carbon policies, enterprises need to speed up the transformation from a high-carbon to a low-carbon economy. Unfortunately, due to the massive volume of data, developing a low-carbon economic enterprise management model might be challenging, and there is no way to get more precise forecast data. This study tackles the challenge of developing a low-carbon enterprise management mode based on the grey digital paradigm, with the aim of finding solutions to these issues. This paper adopts the method of grey digital model, analyzes the strategy of the enterprise to build the model, and makes a comparative experiment on the accuracy and performance of the model in this paper. The results show that the values of MAPE, MSE and MAE of the model in this paper are the lowest. And the r^2 of the model in this paper is also the highest. The MAPE value of the model in this paper is 0.275, the MSE is 0.001, and the MAE is 0.003. These three indicators are much lower than other models, indicating that the model has high prediction accuracy. r² is 0.9997, which is much higher than other models, indicating that the performance of this model is superior. With the support of this model, the efficiency of building an enterprise model has been effectively improved. As a result, developing an enterprise management model for the low-carbon economy based on the gray numerical model can offer businesses new perspectives into how to quicken the shift to the low-carbon economy.

Introduction: New energy vehicles (NEVs) refer to automobiles powered by alternative energy sources to reduce reliance on fossil fuels and mitigate environmental impacts. They represent a sustainable transportation solution, aligning with global efforts to promote energy efficiency in the automotive sector. Aim: The purpose of this research is to investigate the influence of social demand on the business model of NEVs. Through a comprehensive analysis of consumer preferences and market dynamics, the research aims to identify strategies for driving the sustainable growth of the NEV industry in respond to societal demands. Research methodology: We conduct a questionnaire survey on 2415 individuals and evaluated that questionnaire data by multifactor analysis of variance to examine individual consumer characteristics. We employed NOVA to evaluate the differences in market penetration factors. Additionally, a regression analysis model is utilized to examine accessibility element’s effects on the consumer’s intensions to buy, addressing categorical and ordered data requirements effectively. Research findings: This research demonstrates that middle-aged and adolescent demographics show the highest willingness to purchase NEV’s, particularly emphasizing technological advancements. Consumer preferences vary based on focus like NEV type, model and brand, necessitating tailored marketing strategies. Conclusion: Improving perception levels and addressing charging convenience and innovative features are vital for enhancing market penetration and sustainable business growth in the NEV industry.