• 研究论文 •

### 多维邻近性对产学研合作创新的影响——广州市高新技术企业的案例分析

1. 1. 中山大学地理科学与规划学院,广州 510275
2. 中山大学城市化研究院,广州 510275
• 收稿日期:2016-11-11 修回日期:2017-02-10 出版日期:2017-04-20 发布日期:2017-05-04
• 作者简介:

作者简介：胡杨（1984- ）,男,湖北荆州人,博士研究生,研究方向为区域创新与产业集群。E-mail:huyangtree520@163.com;李郇（1964- ）,男,江西南昌人,博士,教授,博士生导师,研究方向为城市经济学、区域经济。E-mail:lixun23@126.com

• 基金资助:
国家自然科学基金项目（41271138）

### The impact of multi-dimensional proximities on university-industry cooperative innovation: Case studies of high-tech enterprises in Guangzhou

Yang HU1(), Xun LI1,2()

1. 1. School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China
2. Urbanisation Institute, Sun Yat-sen University, Guangzhou 510275, China
• Received:2016-11-11 Revised:2017-02-10 Online:2017-04-20 Published:2017-05-04

Abstract:

With the growing importance of University-Industry cooperative innovation (U-I cooperative innovation) in regional innovation, there is an increasing concern over the factors influencing U-I cooperative innovation. While U-I cooperative innovation features a process of knowledge transfer, multi-dimensional proximity is an appropriate analytical perspective to study the influencing factors of U-I cooperative innovation. This paper argues that geographical proximity, cognitive proximity and social proximity are essential elements of a conceptual framework for the analysis of U-I cooperative innovation, which contains heterogeneous organization. As such multi-dimensional proximities represent an important factor in the promotion of U-I cooperative innovation, interactive learning has been proved to be the way to realize knowledge transfer under the influence of multi-dimensional proximities for cooperative subjects—since frequent and continuous interaction between U-I cooperative subjects can enhance the level of U-I cooperation. By constructing a theoretical framework of "Multi-dimensional proximities, geographical proximity and related proximities→Interactive learning→Level of cooperation", and based on a multi-case study methodology, this research takes high-tech enterprises in the Guangzhou Development District as an example and explores the influence of multi-dimensional proximities on "point to point" U-I cooperative innovation. The research findings show that: (1) while geographical proximity, cognitive proximity and social proximity all contribute to the level of U-I cooperation, these positive effects vary at different stages of technological innovation; (2) whilst interactive learning has significant moderating effects on multi-dimensional proximities and the level of U-I cooperation, there are noticeable periodic characteristics in its effects in terms of content, way and intensity; (3) geographical proximity, cognitive proximity and social proximity, respectively, have complementary and substitutive effects on the level of U-I cooperative innovation, although the effects may vary in different stages. In the interaction between different types of proximities, the positive influence of complementary effects is usually greater than that of substitutive effects. The conclusion is useful for us to understand the interaction process between the innovation subjects under different circumstances of proximities; in addition, it can also provide evidence for policy-making as regards rational distribution of scientific and technological resources, selection of U-I cooperative partners, as well as appropriate responses to different circumstances of proximities in the process of technological innovation cooperation.