This research presents a comprehensive model for enhancing the road network in Thailand to achieve high efficiency in transportation. The objective is to develop a systematic approach for categorizing roads that aligns with usage demands and responsible agencies. This alignment facilitates the creation of interconnected routes, which ensure clear responsibility demarcation and foster efficient budget allocation for road maintenance. The findings suggest that a well-structured road network, combined with advanced information and communication technology, can significantly enhance the economic competitiveness of Thailand. This model not only proposes a framework for effective road classification but also outlines strategic initiatives for leveraging technology to achieve transportation efficiency and safety.

Comparative analysis of the development history of sports social organizations in China, Japan and South Korea from multiple perspectives, in order to provide reference suggestions for solving the existing problems of the development of sports social organizations in China as well as for the sustainable development in the future. This paper explores the optimization path of sports social organizations in China by using the literature method and comparative analysis method. The study finds that the current development of sports social organizations in Japan and South Korea is characterized by independence and autonomy, a relatively rich number and variety of organizations, mutual separation of powers and responsibilities between government agencies and social organizations, and autonomous operation and efficient governance of sports social organizations. The development of sports social organizations in China has reached a new level since the founding of New China, and the Party’s attention to and support for their development has been increasing, but China still has deficiencies in the number of organizations, organizational capacity, and policy system. The study concludes that Japan and South Korea have three development conditions for sports social organizations: a socially oriented governance system, a more complete policy and regulation system, and a standardized and efficient financial support system. The study concludes that the prosperity of sports social organizations is crucial in building a strong sports nation at the present time. Combining the successful experiences of Japan and South Korea and integrating into China’s national conditions, we strive to build a governance system that combines government and society, construct a diversified financial support system, and improve the policy support system for sports organizations to promote the progress of sports social organizations in China, and open the way for the autonomy and independence of sports social organizations in China, and put the improvement of the governance system of sports social organizations on the agenda.

The global increase in organic food consumption underscores the need for in-depth research to understand the determinants of consumer purchase intentions towards organic products. Hence, this study aims to investigate the factors influencing the consumer purchase intentions towards organic food through an analysis involving 274 participants. Additionally, it also explores the mediating and moderating effects of attitudes and environmental concerns on the purchasing intentions towards organic food, providing insights in how these psychological and environmental factors influence consumer behavior. Using a quantitative method, data was gathered from the South Korean cities of Jinju and Changwon. However, analysis was performed through Partial Least Squares Structural Equation Modeling. The research findings illustrate that subjective norm, perceived behavioral control, and ethical consciousness significantly influence attitudes towards purchase intentions of organic foods. Moreover, the results indicate that attitude positively influenced consumer purchase intention towards organic food. Results reveal that attitude serves as a mediator in the relationship between subjective norms and consumer purchase intentions for organic food. Similarly, Likewise, attitude mediates the connection between perceived behavioral control and consumer purchase intention towards organic food. Additionally, the results indicate that attitude mediates the relationship between ethical consciousness and consumer purchase intention towards organic food. Furthermore, environmental concerns are found to significantly moderate the association between attitude and consumer purchase intention towards organic foods. The insights garnered from this study shed light on consumer intentions to purchase organic foods, equipping stakeholders such as marketers, retailers, and producers with valuable insights for creating effective marketing strategies aiming at promotion of these products. This research serves as a pivotal resource for developing targeted approaches to enhance the market share and consumption of organic foods.

This study investigates the impact of supply chain agility on customer value and customer trust while investigating the role of price sensitivity as a mediating variable in the healthcare industry. A quantitative methodological approach was used. This was cross-sectional descriptive research based on a survey method, and data were collected using a structured questionnaire. The sample consisted of 384 respondents who had already used healthcare facilities. The sampling technique was convenience sampling and collected data were analyzed using structural equation modeling. The study indicated that supply chain agility positively impacts customer value and customer trust, while there is no moderation role of price sensitivity in the healthcare industry. Previous scholars revealed that there is a strongly available association between supply chain agility and customer value. But no attempt was undertaken to investigate the impact of supply chain agility on customer trust while moderating the role of price sensitivity.

This paper studies the patent race problem of communication enterprises investing in communication technologies, and constructs a portfolio optimization model which considers the expected returns, investment risks, and replacement costs, in order to achieve the dual goals of maximizing the net investment income of backward enterprises and minimizing the expected investment risk. Through numerical experimental analysis, the optimal investment portfolio strategy under different risk levels and the impact of different risk levels on the net income of lagging company are obtained. The research results show that due to the backward research in the first stage of the backward enterprises, when their own investment decision-making power is relatively high, they can focus on the development of self-interested key technology areas in order to achieve the victory of the patent race.

The telecommunications services market faces essential challenges in an increasingly flexible and customer-adaptable environment. Research has highlighted that the monopolization of the spectrum by one operator reduces competition and negatively impacts users and the general dynamics of the sector. This article aims to present a proposal to predict the number of users, the level of traffic, and the operators’ income in the telecommunications market using artificial intelligence. Deep Learning (DL) is implemented through a Long-Short Term Memory (LSTM) as a prediction technique. The database used corresponds to the users, revenues, and traffic of 15 network operators obtained from the Communications Regulation Commission of the Republic of Colombia. The ability of LSTMs to handle temporal sequences, long-term dependencies, adaptability to changes, and complex data management makes them an excellent strategy for predicting and forecasting the telecom market. Various works involve LSTM and telecommunications. However, many questions remain in prediction. Various strategies can be proposed, and continued research should focus on providing cognitive engines to address further challenges. MATLAB is used for the design and subsequent implementation. The low Root Mean Squared Error (RMSE) values and the acceptable levels of Mean Absolute Percentage Error (MAPE), especially in an environment characterized by high variability in the number of users, support the conclusion that the implemented model exhibits excellent performance in terms of precision in the prediction process in both open-loop and closed-loop.