Innovation has always been a key driver of economic development, particularly in the context of small and medium-sized enterprises (SMEs). Despite their significant contributions, many of these enterprises currently lack strong research and development capabilities, face challenges in innovation investment, and struggle to produce high-quality innovative results. To address these issues and overcome funding obstacles, many SMEs are turning to supply chain finance (SCF) as a supplementary financing method. This study utilizes stata16 and fixed effects models to analyze the impact and mechanism of SCF on enterprise innovation performance (EIP), focusing on companies listed on the SME Board and GEM in Shenzhen, China from 2011 to 2020. The findings reveal that SCF can effectively enhance enterprise innovation output, facilitating the conversion of resources into high-quality innovation results. Additionally, the study demonstrates that supply chain concentration acts as a mediator between SCF and EIP. Moreover, SCF is found to significantly boost EIP with low supplier concentrations and high customer concentrations. This suggests that SMEs encounter obstacles to innovation from suppliers and customers, and SCF may not fully address the challenges posed by these relationships. Overall, this research offers new empirical insights into the economic implications of companies adopting SCF, providing valuable guidance for enterprises in optimizing innovation decisions and for the government in enhancing supplier and customer information disclosure systems.
Personal branding is a conscious activity that utilizes classic product marketing methods to make a person more marketable. In our study, we employed a quantitative research methodology. Through a survey, we examined the importance respondents assign to visible and non-visible traits and characteristics. During the data analysis, we established a ranking of the most important traits identified by the survey participants, which they believe contribute to a more favorable perception. Among the top five ranked traits—reliability, appearance, charisma, grooming, and authenticity—three are recognizable during the first encounter. Our findings suggest that women place greater emphasis on social perception than men, making them more likely to remain unnoticed. At the same time, younger generations tend to overvalue their presence on social media platforms.
Background: Simulation-based medical education is a complex learning methodology in different fields. Exposing children to this teaching method is uncommon as it is designed for adult learning. This study aimed to develop and implement simulation-based education in first aid training of children and investigate the emotions of children in post-simulation scenarios that replicate emergency situations. Methods: This was a phenomenological qualitative research study. The participants attended the modified “Little Doctor” course that aims to train children in first aid and, subsequently, completed simulation scenarios. The children attended focus groups and were asked about their experiences of the course and how they felt during the simulation scenarios. Results: 12 children (Age 8–11 years old) attended the course, and 10 completed the simulation scenarios and focus groups. The major theme derived from was the simulation experience’s effect, which was divided into two subthemes: the emotion caused by—and the behavioral response to—the simulation. The analysis revealed shock and surprise toward the environment of the simulation event and the victim. The behaviors expressed during the simulation scenarios ranged from skill application and empathy to recall and teamwork. Conclusions: Simulation scenarios were successfully implemented during the first-aid training course. Although participants reported mixed feelings regarding the experience, they expressed confidence in their ability to perform real-life skills.
The purpose of this study is to analyze issues related to the use of green technology and to provide a theoretical basis for how the application of green technology in agriculture can reduce inequality. Additionally, the study aims to explore policy alternatives based on the analysis of inequality reduction issues through farmer surveys. For this purpose, this study used survey data to analyze farmers’ perceptions, acceptance status, willingness to accept green technology, and perceptions of inequality. The quantitative analysis was performed to analyze the relationship between the acceptance of green technology and perceptions of inequality. The results confirmed that access to information, perception of climate change, and awareness of the need to reduce greenhouse gas emissions are major factors. In particular, the higher the satisfaction with policies regarding the introduction of green technology, the lower the perception of inequality. Specifically, the acceptance of green technology showed a significant positive correlation with access to information, perception of climate change, and awareness of the need to reduce greenhouse gas emissions, while perceptions of inequality showed a significant negative correlation with policy satisfaction. In conclusion, green technology in agriculture is vital for reducing climate change damage and inequality. However, targeted policy support for small-scale farmers is essential for successful adoption. This study provides policy implications related to the application of green technology in the agricultural sector, which can promote sustainable agricultural development.
An extensive assessment index system was developed to evaluate the integration of industry and education in higher vocational education. The system was designed using panel data collected from 31 provinces in China between 2016 and 2022. The study utilized the entropy approach and coupled coordination degree model to examine the temporal and spatial changes in the level of growth of the integration of industry and education in higher vocational education, as well as the factors that impact it. In order to examine how the integration of industry and education in higher vocational education develops over time and space, as well as the factors that affect it, we utilized spatial phasic analysis, Tobit regression model, and Dagum’s Gini coefficient. The study’s findings suggest that between 2016 and 2022, the integration of industry and education in higher vocational education showed a consistent improvement in overall development. Nevertheless, there are still significant regional differences, with certain areas showing limited levels of integration, while the bulk of regions are either in a state of low integration with high clustering or low integration with low clustering. Most locations showed either a “low-high” or “low-low” level of agglomeration, indicating a significant degree of spatial concentration, with a clear trend of higher concentration in the east and lower concentration in the west. The progress of industrial structure and the degree of regional economic development have a substantial impact on the amount of integration of industry and education in higher vocational education. There is a notable increase in the amount of integration between industry and education in higher vocational education, which has a favorable effect. Conversely, the local employment rate has a substantial negative effect on this integration. Moreover, the direct influence of industrial structure optimization is restricted. The Gini coefficient of the development level of integration of industry and education in higher vocational education exhibits a slight rising trend. Simultaneously, there is a varying increase in the Gini coefficient inside the group and a decrease in the Gini coefficient between the groups. The disparities in the level of integration between Industry and Education in the provincial area primarily stem from inter-group variations across the locations. To promote the integration of industry and education in higher vocational education, it is recommended to strengthen policy support and resource allocation, address regional disparities, improve professional configuration, and increase investment in scientific and technological innovation and talent development.
Purpose: Today’s challenges underscore the importance of energy across all segments of life. This scientific paper investigates the multifaceted relationship between energy efficiency, energy import reliance, population heating access, renewable energy integration, electricity production capacities, internet utilization, structural EU funds, and education/training within the framework of economic development. Methodology: Using data from selected European countries and employing self-organizing neural networks (SOM) and linear regression, this research explores how these interconnected factors influence the journey toward a sustainable and prosperous economic future. Results: The analysis revealed a strong connection between energy efficiency and numerous socioeconomic factors of modern times, with most of these connections being non-linear in nature. Conclusion: As countries work toward sustainable development goals, prioritizing energy efficiency can contribute to improved quality of life, economic growth, and environmental sustainability.
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