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.

This article using thematic and content analysis investigated the contribution of innovation in achieving sustainable economic development. The objective of the bibliometric research was to assess the literature on this subject it identified research trends, ideas, and authors who contributed to this area so that future research and policy directions could be suggested. The data was derived from the Scopus database and was extracted between January 2020 and February 2024 by applying inclusion and exclusion criteria. The Scopus database search yielded 66 articles, published between 2020 and February 2024. Scopus analytics and Microsoft Excel were used for descriptive analysis and VOS Viewer software was used for network visualization of keywords. The descriptive analysis showed the trajectory of research, the prolific authors, their publication outlets, authors affiliation, and county of origin of the documents. The prolific visualization showed five clusters: red, green, blue, purple, and yellow. The main clusters are economic development, alternative energy, sustainable development, and innovation. This research showed where consideration should be given to drive sustainability and sustainable economic development. This research outcome will assist government agencies, corporations, and non-profit organizations in planning appropriate action and policies to support innovative and renewable energy initiatives so that participation in those fields could enhance the opportunity to achieve sustainable economic development.

Underground station passenger flow is large, the number of parcels carried by passengers is large and varied, and the parcels carried have an impact on the fire hazard and evacuation of the station. In order to determine the weights of the passenger luggage risk and environmental factor index system in the fire risk evaluation of underground stations in a more realistic way, an optimized and improved hierarchical analysis method for determining the judgement matrix is proposed, which improves the traditional nine-scaled method and adopts the three-scaled method for the four major categories of luggage, namely, handbags, rucksacks, portable power tools and trolley cases. The advantage of this method is that there is no need for consistency judgement in determining packages with a wide range of types and uncertain contents, thus simplifying the calculation. Meanwhile, the reasonableness and reliability of the method is verified by combining it with an actual metro station fire risk assessment system.

Objective: As the scale and importance of official development assistance (ODA) continue to grow, the need to enhance the effectiveness of ODA policies has become more critical than ever before. In this context, it is essential to systematically classify recipient countries and establish tailored ODA policies based on these classifications. The objective of this study is to identify an appropriate methodology for categorizing developing countries using specific criteria, and to apply it to actual data, providing valuable insights for donor countries in formulating future ODA policies. Design/Methodology/Approach: The data used in this study are the basic statistics on the Sustainable Development Goals (SDGs) published annually in the SDGs Report. The analytical method employed is decision tree analysis. Results: The results indicate that the 167 countries analyzed were classified into 10 distinct nodes. The study further limited the scope to the five nodes representing the most disadvantaged developing countries and suggested future directions for aid policies for each of these nodes.

In Ghana, youth unemployment remains significant challenges, with technical and vocational education and training (TVET) emerging as a potential solution to equip young people with practical skills for the job market. However, the uptake of TVET programmes among Ghanaian youth remains low, particularly among females. This study therefore explores the determinants that influence TVET choices among Ghanaian youth, with the goal of informing policy development to enhance participation in vocational education. Applying an enhanced multinomial logistic regression (MLR) model, this research examines the influence of socio-economic, demographic, and attitudinal factors on career decisions. The enhanced model accounts for class imbalances in the dataset and improves classification accuracy, making it a robust tool for understanding the drivers behind TVET choices. A sample of 1600 Ghanaian youth engaged in vocational careers was used, ensuring diverse representation of the population. Key findings reveal that males are approximately three times more likely to choose TVET programs than females, despite females making up 50.13% of Ghana’s population. Specific determinants influencing TVET choices include financial constraints, parental influence, peer influence, teacher influence, self-motivation, and vocational limitations. In regions with limited vocational options, youth often pursue careers based on availability rather than preference, which highlights a gap in vocational opportunities. Parental and teacher influences were found to play a dominant role in steering youth towards specific careers. The study concludes with recommendations for policymakers, instructors, and stakeholders to increase the accessibility, relevance, and quality of TVET programmes to meet the socio-economic needs of Ghanaian youth.

Young people are a traditional risk group for radicalization and involvement in protest and extremist activities. The relevance of this topic is due to the growing threat of youth radicalization, the expansion of the activities of extremist organizations, and the need to organize high-quality preventive work in educational organizations at various levels. The article provides an overview of research on the topic under consideration and also presents the results of a series of surveys in general educational institutions and organizations of secondary vocational education (n = 11,052), universities (n = 3966) located in the Arctic zone of the Russian Federation. The results of the study on aspects of students’ ideas about extremism are presented in terms of assessing their own knowledge about extremism, the presence/absence of radically minded people around them, determining the degree of threat from the activities of extremist groups for themselves and their social environment, and identifying approaches to preventing the growth of extremism in society. Conclusions are drawn about the need to improve preventive work models in educational organizations towards a targeted (group) approach.