地理研究 ›› 2021, Vol. 40 ›› Issue (2): 387-401.doi: 10.11821/dlyj020190979

• 研究论文 • 上一篇    下一篇

中国高新技术产业开发区的知识基础及其创新效应——基于国家级高新区上市企业的研究

林剑铬1, 夏丽丽1,2(), 蔡润林3, 蔡虹绮1   

  1. 1.华南师范大学地理科学学院,广州510631
    2.华南师范大学粤港澳大湾区村镇可持续发展研究中心,广州510631
    3.中山大学地理科学与规划学院,广州510275
  • 收稿日期:2019-11-11 接受日期:2020-06-02 出版日期:2021-02-10 发布日期:2021-04-10
  • 通讯作者: 夏丽丽
  • 作者简介:林剑铬(1995-),男,广东德庆人,硕士研究生,主要研究方向为城市与区域创新,产业创新的空间组织与演变过程。E-mail: 2018022328@m.scnu.edu.cn
  • 基金资助:
    国家自然科学基金项目(41001079);广东省软科学项目(2016A070705050)

The knowledge bases of China's High-Tech Industrial Development Zones and their effects on innovation: A study on the listed enterprises

LIN Jiange1, XIA Lili1,2(), CAI Runlin3, CAI Hongqi1   

  1. 1. School of Geography, South China Normal University, Guangzhou 510631, China
    2. Research Center for Sustainable Development of Villages and Towns in Guangdong-Hong Kong-Macao Greater Bay Area, South China Normal University, Guangzhou 510631, China
    3. School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
  • Received:2019-11-11 Accepted:2020-06-02 Online:2021-02-10 Published:2021-04-10
  • Contact: XIA Lili

摘要:

以国家级高新区上市企业为主体,量化划分知识基础类型并以之反映高新区知识基础属性。建立多元线性和地理加权回归模型,通过技术收入、产品销售收入和商品销售收入探究高新区知识基础属性的创新效应。结果表明:① 对样本企业的聚类分析在传统知识基础类型的基础上识别并定义了新的“效率型”知识基础;② 对高新区技术收入的增加,知识基础均衡化呈负效应,其强度由南往北逐渐增强,解析型知识基础专业化只在局部高新区呈正效应;③ 对高新区产品销售收入的增加,知识基础均衡化的效应为正且强度由中部向南北两侧渐增,象征型知识基础专业化呈负效应且相对集中于南部;④ 企业数量超过“门槛”值时,象征型知识基础专业化有利于商品销售收入增加。

关键词: 知识基础, 高新技术产业开发区, 企业, 创新效应, 聚类分析, 地理加权回归

Abstract:

In China, High-Tech Industrial Development Zones (HTIDZs) are industrial spatial agglomerations acting as the contributors to technological change and economic development. However, some current major issues, e.g. ‘enterprises’, the practical actors underpinning knowledge absorption and production of HTIDZs, are rarely discussed in previous literature. From the perspective of enterprises, lack of research is therefore leading to the inadequate cognition to the heterogeneity of knowledge bases and their effects on innovation. In this study, the listed enterprises located in state-level HTIDZs are utilized as microcosmic subjects. By implementing a cluster analysis based on data sets of the above-mentioned enterprises, we come up with a typology of knowledge bases, which may enable the classification of enterprise knowledge bases and presentations of HTIDZ knowledge base attributes. In order to further explore the effects of knowledge base attributes on innovation competitiveness, a multiple linear regression model is established for demonstration of the relatedness between knowledge base attributes and Commodity Sales Income of HTIDZs. Correspondingly, two geographically weighted regression models are constructed and applied when Technical Income and Product Sales Income are respectively taken as dependent variables. The results indicate that: (1) “efficient” knowledge base, distinct from “analytical” knowledge base, “synthetic” knowledge base and “symbolic” knowledge base that have been highlighted in previous literature, is identified and defined based on the cluster analysis of enterprises. (2) For HTIDZ, proportional equalization of knowledge bases inhibits the increase of Technology Income, and from the south to the north, the intensity of such inhibiting effect is strengthened. Specialization of analytical knowledge base has motivating effect for the increase of Technology Income while only a few HTIDZs are under discussion. (3) For HTIDZ, proportional equalization of knowledge bases is an effective way to increase Product Sales Income. It is illustrated that such influence tends to be gradually enhanced from the middle to the north and the south. The relative concentration of symbolic knowledge base goes against the improvement of product competitiveness, especially in southern China. (4) For those HTIDZs whose enterprise quantities outnumber a certain threshold, the promotion of specialization of symbolic knowledge base contributes to the growth of Commodity Sales Income. Policy making which aims to foster innovation capabilities of HTIDZs may benefit from this research under the view of “enterprises-knowledge”.

Key words: knowledge bases, High-Tech Industrial Development Zones, enterprises, effects on innovation, cluster analysis, geographical weighted regression