地理科学 ›› 2016, Vol. 36 ›› Issue (3): 321-327.doi: 10.13249/j.cnki.sgs.2016.03.001

• •    下一篇

中国地级以上城市工业创新效率空间格局研究

杜志威1,2(), 吕拉昌3,4(), 黄茹3   

  1. 1.中山大学地理科学与规划学院,广东 广州 510275
    2.广州大学地理科学学院,广东 广州 510006
    3.首都师范大学资源环境与旅游学院,北京 100048
    4.北京城市创新与发展研究中心,北京100048
  • 收稿日期:2014-09-09 修回日期:2015-01-04 出版日期:2016-03-20 发布日期:2016-05-18
  • 作者简介:

    杜志威(1987-),男,广东广州人,博士研究生,主要从事城市与区域发展研究。E-mail: 84102294@qq.com

  • 基金资助:
    国家自然基金项目(41471136)、北京市自然科学基金资助项目 (9132002)、国家社科重大招标课题(12&ZD169)、国家社会科学重点项目 (12AZD100)资助

Spatial Pattern of Industrial Innovation Efficiency for Chinese Cities at Prefecture Level and Above

Zhiwei Du1,2(), Lachang Lyu3,4(), Ru Huang3   

  1. 1. School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, Guangdong, China
    2. School of Geographical Sciences, Guangzhou University, Guangzhou 510006, Guangdong, China
    3. College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
    4. Center of Urban Innovation and Development Research, Beijing 100048, China
  • Received:2014-09-09 Revised:2015-01-04 Online:2016-03-20 Published:2016-05-18
  • Supported by:
    Under the auspices of National Nature Science Foundation of China (41471136), Beijing Natural Science Foundation (9132002), Key Public Biding Project of National Social Science of China (12&ZD169), Key Program for National Social Science Foundation of China (12AZD100)

摘要:

以中国288个地级以上城市为研究对象,运用2008年第二次全国经济普查工业创新活动数据,综合考察城市工业创新效率的空间格局及其影响因素。首先,从投入和产出两方面构建了中国城市工业创新效率评价体系,运用DEA包络分析方法,从规模效率和纯技术效率两个维度对城市工业创新技术效率进行分析。然后,以聚类分析划分了3类工业创新效率城市,总结工业创新效率模式的空间特征,并分析了影响空间格局的原因。研究发现:中国城市工业创新效率呈现东强西弱,阶梯状减弱的总体空间格局,工业创新规模效率和纯技术效率的空间特征并不重合;全国尺度上,工业创新效率城市的空间分布与人口密度“黑河-腾冲”线的分布基本一致,区域尺度上,城市间呈现“核心-边缘”空间结构;城市工业创新效率空间格局受到工业发展基础与工业创新能力影响,提高城市工业创新效率关键在于提升工业创新中人力资本要素和优化工业创新投入规模。

关键词: 工业创新效率, 空间格局, 投入产出, DEA, 城市

Abstract:

With the development of knowledge economy, Chinese industrialization is transferring from traditional factor-driving stage to innovation-driving stage. Innovation becomes a significant force for promoting urban industrial efficiency. Exploring the spatial pattern of Chinese urban industrial innovation efficiency can make contribution to improving total innovation efficiency and industrial upgrading for China. 288 cities at prefecture level and above in China are chosen as the objects of study, in order to investigate on the spatial pattern of urban industrial innovation efficiency as well as seek its influential factor. To begin with, we use industrial innovation data from national economic census, and establish an index system of urban industrial innovation efficiency, which is constructed from innovation inputs aspect and innovation outputs aspect. By using Data Envelopment Analysis (DEA), urban industrial innovation technical efficiency (TE) is explained separately from Pure Technical Efficiency (PTE) and Scale Efficiency (SE). Moreover, we divide 3 categories of urban industrial innovation efficiency cities through clustering analysis, exploring spatial pattern characteristic of them. Our findings are 1) Overall spatial pattern of Chinese urban industrial innovation efficiency shows gradient weakened from the east to the west, while the spatial characteristic for PTE and SE is mismatched. 2) Spatial distribution of industrial innovation efficiency cities is approximately coincided with Chinese population distribution, which relates to the “Heihe-Tengchong Line”, and displays obviously “core-periphery” spatial structure in regional scale, such as the Beijing-Tianjin-Hebei region, the Changjiang River Delta region, the Zhujiang River Delta region, the Bohai Rim region and the Chengdu-Chongqing region. 3) Industrial innovation capability and Industrial developing basement are developing combined impact on the spatial pattern of Chinese urban industrial innovation efficiency, while improving human capital elements and optimizing the scale of industrial innovation input is the key of urban industrial innovation efficiency.

Key words: industrial innovation efficiency, spatial pattern, input-output, DEA, cities

中图分类号: 

  • F290