Search

In recent years, the number and scale of small, medium-sized, and micro enterprises have continued to increase, which is the main force to promote the development of China's national economy, the guarantee of China's rapid and stable economic development, and has a direct impact on social stability and people's livelihood. In China's economic growth, small, medium-sized, and micro businesses play a critical role. However, several limitations limit their current growth stage, preventing them from expanding their size, such as resource and environmental limits, an inappropriate industrial structure, and institutional issues, such as severe market rivalry. To address this issue, this paper develops a micro innovation service platform for small and medium-sized businesses, offers a variety of services to small and medium-sized businesses, fully realizes data sharing and transmission in all aspects using social perception and neural network algorithms, and effectively utilizes social attributes on mobile nodes to assist each node. Also, it investigates the impact of the innovation service platform for small and medium-sized micro firms in practice. After the construction of the innovation service platform for small and medium-sized micro enterprises in 2018, it analyzes the number of transaction projects of platform technology transfer, technology development, technical consultation, and technical services from 2018 to 2020 and analyzes the transaction volume of projects in four aspects. The results show that they have significantly improved, which plays an important role in realizing the transformation of achievements and improving the innovation ability of small and medium-sized micro enterprises in China. At the same time, according to the investigation and analysis of 8 innovative service platforms in the western region, 25% of them have developed well. [ABSTRACT FROM AUTHOR]

This paper makes a new attempt to identify the effectiveness of innovation factor allocation with a random forest method. This method avoids the evaluation bias of the relative effectiveness caused by the noneffective selection of production frontier in the nonparametric DEA method. It does not refer to other optimal subjects but shifts the focus to the judgment of its own effectiveness. In addition, it also gets rid of the constraints of the model and variables in the parameter SFA method, ensuring the reliability of the measurement results by resampling thousands of times. The data is collected from 30 provinces in China from 2009 to 2018. The findings show the innovation factor allocation in more than half of the provinces is not fully effective. It indicates that how to make use of innovation factor inputs to achieve the actual innovation output higher than own optimal levels is currently still in a period of exploration in China. To further improve innovation factor allocation efficiency, it deeply analyzes the impacts of innovation factor inputs and finds out the important innovation factor inputs. Furthermore, this study presents the nonlinear characteristics and optimal combination of important innovation factor inputs. According to this, it offers the detailed suggestions about how to adjust current important innovation factor inputs for each province in order to greatly enhance the effectiveness of innovation factor allocation in the future. [ABSTRACT FROM AUTHOR]

Traditional marine pastures have made great contributions to human beings, but traditional marine pastures have also caused major harm to the marine natural environment. Modern technology represented by artificial intelligence has broad application prospects and significant potential and has the ability to innovate and enhance the conventional marine ranching business that is currently in recession. The particularity of China's marine ranching industry determines the combination of technologies such as underwater robots and the Internet of Things with the development of marine ranching to create a sustainable intelligent marine ranching industry in China. The growth of China's national economy is largely influenced by the development of the country's financial services industry. In order to better support the development of the real economy, it is necessary to establish a financial service system with controllable risks and complementary activities. This paper proposes to use the method of Internet of Things data collection combined with sensors to conduct economic analysis. By taking a number of data in recent years for research and analysis, the results show that financial service industry innovation has become an important part of improving the competitiveness of the industry and an important driving force for economic growth. The Internet of Things (IoT) business in China is a fast-growing industry with huge potential. From the perspective of international comparison, our country is currently in the early stage of the development of the Internet of Things, and a certain technology, industry, and application foundation has been established in the early stage of development. In the financial services business, the visual tracking provided by IoT technology has innovative potential. Introducing IoT technology into financial service business and identifying the driving force and process of financial innovation have practical significance for accelerating financial innovation. [ABSTRACT FROM AUTHOR]