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Science and technology innovation policies have been considered as effective policy tools in promoting regional innovation. This paper used content analysis method to analyze 321 pieces of science and technology policies published from 2006 to 2018. Structures of the policy social networks had been analyzed and discussed, and the main points and emphasis of the science and technology policy system of China’s Yangtze River Delta region had been revealed. Results indicated that Shanghai, Jiangsu, Zhejiang and Anhui’s science and technology policy system structures were relatively consistent, while the development paths were different, and the content of industrial policy of four provinces had a serious homogenization problem.

Knowledge and technology transferring between universities and industries had been an important research focus of innovation management. Bibliometric research on the university-industry knowledge transferring had always used patent collaboration and citation data as indicators. However, patent licensing data were more representative and could target the knowledge transferring directions. This paper had gone through the data of Chinese academic-industry patent licensing and focused on the variances in regional level and geographic distance. Using patent licensing document analyzing method, the academic-industry knowledge flowing patterns had been discovered. Results showed that localization effects had been existed in those Chinese regions and the engagement of knowledge transferring was severely unbalanced.

This paper had studied “3 + 1” National Innovation Demonstration Zones (NIDZ) in China, which located in Beijing, Wuhan, Shanghai and Anhui province. There were national level instructions for innovation demonstration zones. These 4 regions would benefit from the specific policy approved by the Chinese government and the whole nation depended on them to improve creative S & T level in the future from “Made in China” to “Created in China”. This paper had compared different aspects among these 4 innovation zones. The “1” Anhui Hefei-Wuhu-Bengbu area (HWB) would benefit from experience made by the “3” earlier innovation zones.

The characteristics of science and technology activities (STA) have important effect on the characteristics of the research of science and technology policy (STP). On this argument, we review the research on the characteristics of STA and the characteristics of the study of STP, discuss the characteristic of STP itself and the effect on the research of STP, therefore summarize the characteristics the research of STP should have. The characteristics of the current STA are as below: its effect is irreversible and of wide range as well as high speed ; it faces with the risk of technology and market; it has ethical anomie; it is interdisciplinary and cross level and domain; it has national mission, etc. These characteristics make the research of STP need the following characteristics: Timeliness and scientific; Tolerance and face up to failure; Normative values; Extend research subject; national demand oriented, etc.

Different regions had various kinds of academic resources and industries competitors. The knowledge and innovation output generated by researchers in academy had been transferred into industries through patent licensing. Using the patent licensing document analyzing method and the mapping technique, the academic-industry knowledge flowing patterns of different regions in China had been discovered and visualized in maps. The regional performance of academic-industry knowledge transfer was rather mixed and unbalanced. Based on the licensing performance data, this paper had also generated a 4 × 4 block matrix as evaluation tool and ranked 28 Chinese regions into 8 levels according to their academic licensing performance. Further suggestions and advice had been given for regions in different levels.

This paper had collected the patent licensing documents of all Chinese universities and made a comprehensive study on licensing performance. With a whole set of data from SIPO, the exact licensing frequency number and licensing propensity number of Chinese universities had been obtained for the first time. On average, 16.03 patents (6%) per university had been licensed out to the industry, which is much lower than expectations. The frequency of licensing, propensity of licensing, number of partners (licensees), number of patent stocks, local-transfer ratio and the distribution of licensing frequency in terms of university-firm distance had been obtained in details. Five hypotheses had been made to discover the variances in university licensing performance. With the ANOVA technique, five hypotheses had been confirmed within the dataset, which had revealed a significant effect of patent stocks, local economic performance, central government support, existence of TTO and local government administration on university licensing performance.