This study examines the impact of education quality and innovative activities on economic growth in Shanghai through international trade and fixed asset formation. The study examines how higher education quality and innovation activities drive regional economic growth, with a focus on the mediating effects of international trade and fixed asset formation in Shanghai. The study adopts a quantitative approach utilizing panel data from 31 provinces in China covering the period from 1999 to 2022. The study incorporates variables such as education quality, innovation capacity, and GDP per capita, as well as control variables like labor, capital, and infrastructure. The methodology involves multiple regression models and robustness tests to verify the relationships between and effects of education quality and innovation with regard to economic growth. This study analyzes the direct and indirect effects of university R&D expenditure and innovation on economic growth using a regression model, based on data from 2014 to 2022 in relation to Shanghai. The model introduces variables such as international trade, capital formation, and urbanization to analyze the relationship between higher education quality and economic growth.
Focusing on Shanghai Port, this in-depth study explores how government support can make port organizations more competitive. This study shall implement qualitative analysis based on in-depth interviews with key industry and government leaders to break down the complicated actions taken by the government and how they have changed the operational and strategic skills of the port industry. Seven factors were found in our study to be the most crucial support factors: Financial, regulatory, infrastructure growth, talent, market, policy, and organizational support. In their ways, each of these groups undermines the ability of port businesses to compete. For instance, finance can make ports more competitive in aspects such as tax cuts, lower interest rates, innovation and R&D funds, financing programs, venture capital funds, and putting up R&D sites. Supporting regulations makes sure that there is fair competition and smooth operations. This is done by protecting intellectual property, keeping the market going smoothly, improving the business environment, and monitoring market regulations. Building new infrastructure, such as innovation and updated buildings, enables the smooth running of the port businesses and minimizes wastage of time; thus, more time is spent on production. Supporting talent, the market, and policy all work together to make the human capital, international cooperation, and strategic regulatory framework that a company needs to stay ahead in the long run. It is clear from organizational support how important collaborative networks are for making ports more competitive. These networks, for instance, can be of assistance in helping schools and businesses work together, create new technologies, and find ways for companies and colleges to study together. This study examines these support systems to determine where the government should step in and how the systems can be made better to make ports more competitive. In terms of practical contribution, this in-depth study helps policymakers and port workers plan for the future. This study shows a fair way for the government to support the port business, which changes with its needs and stays competitive in the world of trade.
This research focuses on addressing critical driving safety issues on university campuses, particularly vehicular congestion, inadequate parking, and hazards arising from the interaction between vehicles and pedestrians. These challenges are common across campuses and demand effective solutions to ensure safe and efficient mobility. To address these issues, the study developed detailed microsimulation models tailored to the Victor Levi Sasso campus of the Technological University of Panama. The primary function of these models is to evaluate the effectiveness of various safety interventions, such as speed reducers and parking reorganization, by simulating their impact on traffic flow and accident risk. The models provide calculations of traffic parameters, including speed and travel time, under different safety scenarios, allowing for a comprehensive assessment of potential improvements. The results demonstrate that the proposed measures significantly enhance safety and traffic efficiency, proving the model’s effectiveness in optimizing campus mobility. Although the model is designed to tackle specific safety concerns, it also offers broader applicability for addressing general driving safety issues on university campuses. This versatility makes it a valuable tool for campus planners and administrators seeking to create safer and more efficient traffic environments. Future research could expand the model’s application to include a wider range of safety concerns, further enhancing its utility in promoting safer campus mobility.
The objectives of this qualitative research are to study problems and factors promoting success in the career path of government officials in the Ministry of Higher Education, Science, Research, and Innovation (MHESI) in Thailand. The study also finds out career path model to opinions between executives and government officials. This qualitative employed in-depth interview and focus group discussion with executives, academics, and civil servants. It found that the problem was the planning and management of career path due to lacking of standard pattern. Also, it found that the model of career path provides practitioners with career advancement opportunities and job titles from the very beginning to the very top where they can advance and can plan their career progression. The model also provides an opportunity to explore officers’ competencies, aptitudes, and interests that are appropriate for any type of work in the organization and able to prepare them to perform the job, which will affect the success of civil servants’ work and human resource management to create career path and develop oneself to be able to compete for academic and professional excellence, as well as prepare the government officers for appropriate positions in the future.
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.
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