This study aims to analyse the current state of library and information science (LIS) education in South Korea and identify educational challenges in building a sustainable library infrastructure in the digital age. As libraries’ role expands in a rapidly changing information environment, LIS education must evolve. Using topic modelling techniques, this study analysed course descriptions from 37 universities and identified 10 key topics. The analysis revealed that, while the current curricula cover both traditional library science and digital technology topics, focus on the latest technology trends and practical, hands-on education is lacking. Based on these findings, this study suggests strengthening digital technology education by incorporating project-based learning; integrating emerging technologies, such as data science and artificial intelligence; and emphasising community engagement and soft skills development. This study provides insights into improving LIS education to better align with the digital era’s evolving demands.

Promoting travelling intention within social media is significant for stakeholders to grasp a new tourism market and cultivate a new model for development of tourism industry. This study aims to understand path of destination image affecting travelling intention, and to investigate the mediation role of perceived value, furthermore, to uncover the role of moderator of situational involvement. This paper conducts a survey on tourists visiting Guilin, collecting 435 questionnaires, and uses the structural equation modeling method to explore how the image of the tourism destination affects tourists’ willingness to travel. The research results indicate that cognitive image, emotional image, and projected image all have a significant positive impact on perceived value, perceived value as a significant mediator to bridge the relationship among the destination image and tourists’ travel intention. Furthermore, situational involvement plays a negative moderating role in the mediating effect of emotional value. This study endeavor will serve to enrich the understanding of perceived value theory, destination image theory, and tourism consumer behavior theory. It will also provide theoretical foundations and policy recommendations for guiding tourism consumer behavior, analyzing destination image perception, and destination marketing.

The objective of this research is to assess the current state of e-banking in Saudi Arabia. The banking industry is rapidly evolving to use e-banking as an efficient and appropriate tool for customer satisfaction. Traditional banks recommend online banking as a particular service to their customers in order to provide them with faster and better service. As a result of the rapid advancement of technology, banks have used e-banking and mobile banking to both accumulate users and conduct banking transactions. Nonetheless, the primary challenge with electronic banking is satisfying customers who use Internet banking. Thus, the current study seeks to determine what factors affect e-payment adoption with e-banking services. mobile banking, e-wallets, and e-banking, as well as the mediating role of customer trust, can drive e-payment adoption. We distributed the survey online and offline to a total of 336 participants. A convenience sampling technique was used; structure equation modeling (SEM), convergence and discriminant validity; and model fitness were achieved through Smart PLS 3. The findings have shown that mobile banking, e-banking, and e-wallets are three significant independent variables that mediate the role of customer trust in influencing e-payment adoption when using Internet banking services. They should emphasize trust-building activities, specifically in relation to the new ways of e-payment such as e-banking, m-payments, NFC, and e-proximity, which will further help reduce consumer perceptions of risk. The system developers should design user-friendly applications and e-payment apps to enhance consumers’ belief in using them for payment purposes over any Internet-enabled device. They should promptly respond to consumers in cases of failed e-payment transactions and be able to promptly demonstrate transparency in settling claims for such failed transactions. Future studies could benefit from implementing probability sampling to facilitate comparisons with non-probability sampling studies. This study selected responses from only Saudi Arabian adopters of mobile payment technology. We need to conduct research on non-adopters and analyze the results using the model we proposed in this study. Due to time and resource constraints, in depth research using a mixed-methods approach could not be conducted. Future studies can utilize a mixed-methods approach for further understanding.

This study employed the theory of planned behavior to examine how green urban spaces influence walking behaviors, with a focus on Chongqing’s Jiefangbei Pedestrian Street. Using structural equation modelling to analyse survey data from 401 respondents, this study assessed the relationships between attitudes, subjective norms, perceived behavioral control, walking intentions, and actions. The results revealed that attitudes toward walking (β = 0.335, p < 0.001) and subjective norms (β = 0.221, p < 0.001) significantly predict walking intentions, which strongly determine actual walking behavior (β = 0.379, p < 0.001). Moreover, perceived behavioral control exerts a direct significant impact on walking actions (β = 0.332, p < 0.001), illustrating that both environmental and social factors are crucial in promoting pedestrian activity. These findings suggest that enhancing the appeal and accessibility of urban green spaces can significantly encourage walking, providing valuable insights for urban planning and public health policy. This study can guide city planners and health professionals in creating more walkable and health-conducive urban environments.

The study documents the model of the knowledge transfer process between the University, the Vocational Training Center and the industrial actors. The research seeks to answer to the following questions. Where is new knowledge generated? Where does knowledge originate from? Is there a central actor? If so, which organization? Hypotheses tested by the research: H1: Knowledge starts from the higher education institution. H2: Most “new knowledge” is generated in universities and large multinational companies. H3: The university is a central actor in the knowledge flow, transmitting both hard and soft skills, as well as subject (‘know-what’), organizational (‘know-why’), use (‘know-how’), relational (‘know-who’), and creative (‘care-why’) knowledge. The aim of the research is to model the way of knowledge flow between the collaborating institutions. The novelty of this research is that it extends the analysis of the knowledge flow process not only to the actors of previous researches (higher education institutions, business organizations, and government) but also to secondary vocational education and training institutions. The methodology used in the research is the analysis of the documents of the actors investigated and the questionnaire survey among the participants. Knowledge transfer is the responsibility of the university and its partner training and business organizations. In vocational education and training, knowledge flows based on the knowledge economy, innovation and technological development are planned, managed and operational. The research has shown that knowledge is a specific good that it is indivisible in its production and consumption, that it is easy and cheap to transfer and learn.

The Consumer Price Index (CPI) is a vital gauge of economic performance, reflecting fluctuations in the costs of goods, services, and other commodities essential to consumers. It is a cornerstone measure used to evaluate inflationary trends within an economy. In Saudi Arabia, forecasting the Consumer Price Index (CPI) relies on analyzing CPI data from 2013 to 2020, structured as an annual time series. Through rigorous analysis, the SARMA (0,1,0) (12,0,12) model emerges as the most suitable approach for estimating this dataset. Notably, this model stands out for its ability to accurately capture seasonal variations and autocorrelation patterns inherent in the CPI data. An advantageous feature of the chosen SARMA model is its self-sufficiency, eliminating the need for supplementary models to address outliers or disruptions in the data. Moreover, the residuals produced by the model adhere closely to the fundamental assumptions of least squares principles, underscoring the precision of the estimation process. The fitted SARMA model demonstrates stability, exhibiting minimal deviations from expected trends. This stability enhances its utility in estimating the average prices of goods and services, thus providing valuable insights for policymakers and stakeholders. Utilizing the SARMA (0,1,0) (12,0,12) model enables the projection of future values of the Consumer Price Index (CPI) in Saudi Arabia for the period from June 2020 to June 2021. The model forecasts a consistent upward trajectory in monthly CPI values, reflecting ongoing economic inflationary pressures. In summary, the findings underscore the efficacy of the SARMA model in predicting CPI trends in Saudi Arabia. This model is a valuable tool for policymakers, enabling informed decision-making in response to evolving economic dynamics and facilitating effective policies to address inflationary challenges.