中国高校技术转移网络的时空特征及影响因素——基于高校-城市二模网络视角

高校技术转移效率偏低是当前中国亟待解决的现实问题，在创新驱动战略深入实施背景下，从空间供需视角探究其转移规律，对实现世界科技强国目标具有重要参考价值。基于2001—2018年中国高校专利转让数据构建高校-城市二模网络，利用社会网络分析、GIS空间分析和网络动力学模型，定量分析高校技术转移网络的空间演化规律及影响因子。研究发现：(1)中国高校技术转移网络规模迅速扩张，高校和城市节点的发育均呈现显著差异性，高校技术主要由综合类和理工类“985/211”高校转至直辖市、省会和区域中心城市；(2)高校技术转移以本地为主，边界效应明显，本地技术转移高值区呈现以直辖市和省会城市为核心的散布格局，跨区域技术转移网络呈现以京津、成渝、长三角、珠三角、哈长沈为核心节点的“梯形”架构；(3)高校等级、高校类型、地理距离、空间共位、技术兼容性和城市技术吸收能力综合影响高校技术转移网络的形成与演化。据此，建议因地制宜促进城市尺度的高校技术转移体系建设，并强化核心城市的多尺度高校技术转移网络建设。

Spatiotemporal dynamic and influencing mechanism of university technology transfer network in China: A university-city bipartite network perspective

The low efficiency of university technology transfer has become a real problem that need to be solved urgently in China. In the context of the in-depth implementation of innovation-driven strategy, it has important reference value to realize the goal of building world S&T power that explores the transfer law from the perspective of university supply and regional demand. Using university-assigned patent data from 2001 to 2018, this study investigates the spatiotemporal characteristic and influencing mechanism of university technology transfer network in China from university-city perspective based on social network analysis, GIS spatial analysis, and network dynamic model. Some findings were obtained as follows: (1) With the growing number of universities and cities involved in university technology transfer network, the scale of the network is expanding rapidly, and the differences among university and city nodes in terms of the scope and quantity of technology transfer are both enlarging. The technology of university is mainly transferred from comprehensive and science and engineering universities belonging to 985 Project and 211 Project to municipalities, provincial capitals, and regional central cities. (2) University technology transfer is highly geographically localized with a significant border effect. On the one hand, high-level local university technology transfer is mainly distributed in municipalities and provincial capitals, because these cities are characterized by higher absorptive capacity with numerous prestigious universities. On the other hand, once it crosses the border of the city where the university is located, university technology transfer decreases significantly since geographical distance does not substantially impact university technology transfer. Due to the existence of substantial university technology transfer among core cities such as Beijing, Shanghai, Shenzhen, and Chengdu, nonlocal university technology transfer network is trapezoidal-shaped and anchored by five metropolitan areas, namely Beijing-Tianjin, Chengdu-Chongqing, Yangtze River Delta, Pearl River Delta, and Harbin-Changchun-Shenyang. (3) The formation and evolution of university technology transfer network are co-driven by university level, university type, geographical distance, co-location, technological compatibility, and urban technology absorptive capacity. Accordingly, it is suggested to promote the construction of university technology transfer system at city scale according to local conditions and strengthen the construction of multi-scale university technology transfer network in core cities.