Spatial–Temporal Evolution and Sustainable Type Division of Fishery Science and Technology Innovation Efficiency in China

Abstract

Science and technology innovation is an important driving force to promote the development of fishery industry, and is very important to improve the quality of fishery development. In this study, the Super-SBM model was used to evaluate the fishery science and technology innovation efficiency of 30 provinces and cities in China (excluding Hong Kong, Macao, Taiwan and Tibet) from 2011 to 2020. Combined with the kernel density estimation, the spatial and temporal differentiation characteristics were analyzed. Then, from the two dimensions of investment scale and innovation efficiency, the sustainable development types of fishery science and technology innovation were classified. The results show the following: (1) From the perspective of efficiency change, the overall efficiency of fishery science and technology innovation in China increased first and then decreased during 2011–2020, but the overall efficiency level was low, and the efficiency difference between regions gradually widened, and the eastern coastal regions became the development core of fishery science and technology innovation. (2) From the perspective of spatial differentiation characteristics, there was a large gap between the coastal and inland areas in China. The high-efficiency areas were mainly concentrated in the coastal provinces and cities, such as Guangdong, Jiangsu, Shandong, Shanghai and Tianjin, showing a decreasing trend from east to west. (3) From the perspective of investment scale and innovation efficiency, the study regions can be divided into four types: leading area, breakthrough area, catch-up area and backward area. This paper mainly calculates the efficiency of fishery science and technology innovation in various regions, and divides the type areas of fishery science and technology innovation and development. According to the advantages and problems of different types of areas, different development strategies and correction measures are proposed, which can effectively improve the efficiency of resource utilization, avoid resource waste and realize the sustainable development of fishery.

The Impact of the Digital Economy on the Health Industry from the Perspective of Threshold and Intermediary Effects: Evidence from China

“…Through the measurement of technological innovation efficiency, the impact of technological innovation on the economy and society is studied from different perspectives. For example, Zhu [43] constructed a scientific and technological innovation input-output index system to measure the efficiency of national scientific and technological innovation and made international comparisons. Wu [44] pointed out that the level of technological innovation has a significant threshold effect on the optimization of industrial structure.…”

“…In the context of innovation-driven strategy, technological innovation is the key to achieve the development of the health industry. This paper draws on the choice of technological innovation indicators by Li et al [52], Wu [44], and Zhu [43] to measure the level of technological innovation in terms of both inputs and outputs. Technological innovation inputs reflect the scale of factors that firms invest in in terms of innovation activities and are measured through R&D expenditures and R&D full-time personnel equivalents.…”

Venture Capital and Chinese Firms’ Technological Innovation Capability: Effective Evaluation and Mechanism Verification

“…Third, under the Chinese Patent Act, patents fall under three categories: invention, utility model, and industrial design, all of which belong to IP rights. Therefore, the total number of the three types of patents used as a dependent variable will be more representative [32]. Moreover, some firms have no applications; therefore, we take the logarithm of 1 plus the total number of applications to be used as the explained variable.…”

“…This explains why VC secures competitive edges of management and resource utilisation for the investee to improve investment in R&D, which is a factor that directly impacts TIC. In this study, the total number of persons involved in R&D activities in a year is used as R&D spending (RDspend), while the number of persons involved per invention patent is used as the human capital input (RDperson) [32]. In Table 4, Columns 1 (RDPerson) and 3 (RDspend) are used as explained variables to conduct the empirical study, and it is found that VC has a significantly positive effect on investment in R&D at the 1% level.…”

Research on Industrial Innovation Efficiency and the Influencing Factors of the Old Industrial Base Based on the Lock-In Effect, a Case Study of Jilin Province, China

“…In the research on innovation efficiency and its influencing factors, the research scales and indicators selected are diverse. In the research on the measurement of innovation efficiency, the scales include international [1,2], country [3][4][5], region [6,7], a specific industry [8][9][10][11] and enterprise [12][13][14], and there are few studies on the intercity scale. The use of indicators above the provincial scale is too macro to reflect the special influencing factors of the intercity scale, and some micro studies cannot reflect the overall appearance of industrial evolution and development.…”