Recognizing the discipline category of the abstract text is of great significance for automatic text recommendation and knowledge mining. Therefore, this study obtained the abstract text of social science and natural science in the Web of Science 2010-2020, and used the machine learning model SVM and deep learning model TextCNN and SCI-BERT models constructed a discipline classification model. It was found that the SCI-BERT model had the best performance. The precision, recall, and F1 were 86.54%, 86.89%, and 86.71%, respectively, and the F1 is 6.61% and 4.05% higher than SVM and TextCNN. The construction of this model can effectively identify the discipline categories of abstracts, and provide effective support for automatic indexing of subjects.

Outsourcing logistics operations is a common trend as businesses prioritize core activities. Establishing a sustainable partnership between businesses and logistics service providers requires a systematic approach. This study is needed to develop a more effective and adaptive framework for logistics service provider selection by integrating diverse criteria and decision-making methodologies, ultimately enhancing the precision and sustainability of procurement processes. This study advocate for leveraging industry-based knowledge in procurement, emphasizing the need to define decision-making elements. The research analyzes nearly 300 logistics procurement projects, using a neural network-based methodology to propose a model that aids businesses in identifying optimal criteria for evaluating logistics service providers based on extensive industry knowledge. The goal of this study is to develop and test a practical model that would support businesses in choosing most suitable criteria for selection of logistics service providers based on cumulative market patterns. The results of this study are as follows. It introduces novel elements by gathering and systematizing unique market data using developed data processing methodology. It innovatively classifies decision-making elements, allocating them into distinct groups for use as features in a neural network. The study further contributes by developing and training a predictive model based on a prepared dataset, addressing pre-defined goals, expectations related to green logistics, and specific requirements in the tendering process for selecting logistics service providers. Study is concluded by summarizing suggestions for future research in area of adopting neural networks for selection of logistics service providers.

Industry 4.0 is revolutionizing businesses’ operations and relationships with the communities to which they cater. The widespread use of computing and network programs compels firms to digitize their operations and offer novel goods, solutions, and business for practice. Universities appear to be slow to adapt to the changes in the education sector. This study suggests using consolidated digital transformation sources to evaluate the level of ability that universities have achieved in the implementation of digital procedures and to compare it to that of other business sectors across all cities and provinces in Vietnam. The text outlines specific factors that universities should consider when implementing the model. Although the objective with the expectation of education from digital transformation is high, compare it with other industries. And the scores achieved in structural agility and create of benefit for the transformative goals are 3.4, but the score of benefit of technologies is 3.0 lower than. Additionally, the organizational component’s scores were primarily focused on leadership and culture, digital strategy, market digitalization, dynamic and digital capabilities, and strengthened logistics within each industry during the digital transformation. Our findings indicate that universities lag behind other industries, perhaps as a consequence of inadequate leadership and cultural shifts. This is exacerbated by a lack of innovation and inadequate financial assistance.

Short-form content has the potential for virality and broad sharing, allowing businesses to reach large audiences in a short period of time. This type of content has transformed traditional marketing approaches, capturing the attention and curiosity of Generation Z, thereby leading to the rise of digital marketing. As Generation Z is the next generation of consumers and their purchasing power increases as they enter the workforce, marketers need to understand the factors influencing their attitudes and purchase intentions. This study aims to explore the relationship between the growing presence of short-form advertising content in corporate marketing strategies and consumer behavioral intentions. To achieve this, the sub-characteristics of short-form content were categorized into expertise, ease of use, and entertainment value, while information reliability was set as a mediating variable. Data was collected through a survey of 256 adults residing in Busan and Gyeongnam, and analyzed using SPSS 28.0. The findings of the study revealed that most sub-characteristics of short-form content advertisements positively influenced both recommendation and purchase intentions. Additionally, information reliability was identified as a significant mediating factor between short-form content and consumer behavioral intentions. These results provide important insights for corporate marketers and advertising professionals, as they offer valuable guidance on how to influence consumer purchase intentions effectively.

Currently, numerous companies intend to adopt digital transformation, seeking agility in their methodologies to reinvent products and services with higher quality, reduced costs and in shorter times. In the Peruvian context, the implementation of this transformation represents a significant challenge due to scarcity of resources, lack of experience and resistance to change. The objective of this research is to propose a digital transformation model that incorporates agile methodologies in order to improve production and competitiveness in manufacturing organizations. In methodological terms, the hypothetical deductive method was used, with a non-experimental cross-sectional design and a quantitative, descriptive and correlational approach. A questionnaire was applied to 110 managers in the manufacturing sector, obtaining a Cronbach’s alpha coefficient of 0.992. The results reveal that 65% of the participants consider that the level of innovation is regular, 88% think that the competition in their companies is of a regular level, and 76% perceive that the level of change is deficient. The findings highlight the importance of digital transformation in manufacturing companies, highlighting the adoption of agile methodologies as crucial to improving processes and productivity. In addition, innovation is essential to developing high-quality products and services, reducing costs and time. Digital transformation with agile methodologies redefines the value proposition, focusing on the customer and improving their digital experience, which differentiates companies in a competitive market.

The importance of tourism to nations’ socioeconomic development cannot be overemphasised as it has proven to be a significant source of revenue for many countries globally. However, sub-Saharan nations like Nigeria have not tapped into the unlimited potential of tourism in their development drive, hence the continuous grappling with underdevelopment challenges. This study examines how tourism impacts socioeconomic growth in Nigeria, focusing on well-known tourist destinations in Lagos State, Nigeria. The study adopts quantitative and qualitative mixed-method research using survey questionnaires and in-depth interviews to elicit responses from visitors at the tourist centres and the tourists’ operations. Data were analysed using simple percentages of frequency distribution tables and thematic analysis. The Neo-liberal theory was adopted as a theoretical framework for the study. The findings highlight the need for better infrastructure, security measures, destination awareness, better housing, financial help, the development of a competent workforce, solid governmental policies, the conservation of cultural and natural assets, and encouragement of collaboration. Future studies may focus primarily on three areas: the evaluation of tourism’s economic impacts, the effectiveness of specific tourist development programs, and the role of tourism in community empowerment.