Innovation has become the main impetus for regional development. Effective utilization of innovation resources is crucial in promoting sustainable innovation. From the theoretical aspect, there still exists uncertainty of how to effectively evaluate innovation performance. From the empirical aspect, we still doubt whether regions of higher economic level or high innovation quantity really show positive regional innovation performance, especially in heterogeneous regions. This paper uses DEA-Malmquist index to measure regional innovation performance of the Yangtze River Economic Belt in China. Regions of similar performance levels are grouped by ward clustering, analysis regional innovation performance characteristics, and problem-solving paths of regions in different development stages. The empirical research proves that overall performance of Yangtze River Economic Belt is not high. The economic core area has realized increase of innovation volume through large amount of material input and resource consumption, instead of realizing full utilization of innovative resources; how to improve the utilization rate of existing technical resources has been neglected. Different regions with similar innovation performance show different characteristics and innovation problems, including resource mismatch, input redundancy, or insufficient output. There are also some differences in the way the region’s specific innovation performance is improved.
China’s high-tech innovation and marketization efficiency still need to be optimized, which restricts the promotion of regional innovation and economic development. On such practical problem, this paper mainly focuses on improvement of high-tech efficiency of China, with the hope that the research can help to find ways to improve efficiency in both regions and industry development. Moreover, the impact on the high-tech innovation stage and the marketization stage are analyzed, in order to make clear the main problems in the complex process of high-tech innovation. This paper proposed the super-SBM model and the panel regression model. The conclusions are as follows. (1) The efficiency of high-tech innovation in China is improving, but there are great differences within regions. Therefore, the heterogeneous regional innovation context should be taken into consideration in the institutional management policies. (2) There is a significant positive correlation between government subsidies and R&D intensity in improving the high-tech innovation efficiency. Government needs to carry out appropriate policy guidance, increase financial support, and encourage high-tech enterprises to increase R&D investment. (3) Openness and better innovation environment play a positive role in the technology marketization stage; thus, the establishment of inter-regional cooperation or transnational relations is an effect way. Forming a better innovation environment can also help to enhance international high-technology cooperation and improve marketization efficiency.
Universities are important sources of knowledge and key members of the regional innovation system. The key problem in Chinese universities is the low efficiency of the scientific and technological (S&T) transformation, which limits the promotion of regional innovation and economic development. This article proposes the three-stage efficiency analytical framework, which regards it as a complex and interactive process. Avoiding the problem of considering the input and output of university S&T transformation as a “black box” and neglecting the links among different transformation stages. The super efficiency network SBM model is applied to the heterogeneous region of the Yangtze River Economic Belt. Empirical research proves that university S&T transformation has not been effectively improved and the scientific resources invested in universities have not been efficiently utilized in recent years. Generally, Despite the correlation between regional economy and transformation efficiency, the exclusive increase in resources is not enough. Regional openness and the quality of research talents are key factors for the application of technological innovation and technology marketization. Universities should not only pursue the number of research outputs but pay more attention to high-quality knowledge production to overcome difficulties in research achievements transformation.
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