科研管理 ›› 2012, Vol. 33 ›› Issue (9): 22-31.

• 论文 • 上一篇    下一篇

高技术产业技术创新投入对创新绩效影响的实证研究 —基于全产业及其下属五大行业面板数据的比较分析

曹勇1,2, 苏凤娇1   

  1. 1. 华中科技大学管理学院,湖北 武汉 430074;
    2. 河海大学商学院,江苏 南京 211160
  • 收稿日期:2011-03-31 修回日期:2011-09-07 出版日期:2012-09-27 发布日期:2012-09-20
  • 基金资助:
    国家自然科学基金项目"开放式创新环境下专利效用对企业技术创新绩效的影响机理研究"(71172092);教育部人文社科基金项目(07JA630003);华中科技大学自主创新基金研究项目(2010AW021)。

The impact of technological innovation input on innovation performance basedon the panel data of Chinese high-tech industries

Cao Yong1,2, Su Fengjiao1   

  1. School of Management, Huazhong University of Science and Technology, Wuhan 430074, China
  • Received:2011-03-31 Revised:2011-09-07 Online:2012-09-27 Published:2012-09-20

摘要: 技术创新投入对创新绩效具有直接影响。本文运用Pearson相关分析、改进的Griliches-Jaffe知识生产函数模型和逐步回归分析等方法,实证分析1995-2008年我国高技术产业技术创新投入对创新绩效的影响机理,并首次对高技术产业整体及其下属5个典型行业进行比较分析。结果表明:高技术产业整体与其下属行业之间、以及下属各行业彼此之间,其技术创新投入对创新绩效影响的效果存在明显差异;即使相同的投入要素在不同行业对初始创新绩效和最终创新绩效的影响效果也有显著差别;R&D投入和非R&D投入对创新绩效都有重要影响;对于不同行业创新资源的高投入并不一定都能带来高产出。在进一步分析这些差异及其原因的基础上,就今后我国高技术产业的协调发展战略提出了相关政策建议。

关键词: 技术创新投入, 创新绩效, 高技术产业, 知识生产函数, 逐步回归分析

Abstract: The relationships between Technological Innovation Input (TII) and innovation performance are explored with the panel data collected from Chinese high-tech industries during the period of 1995-2008, the Pearson’s correlation analysis, modified function model of Griliches-Jaffe knowledge production, and multiple stepwise regression analysis method are used as the analysis methodology. The relationships among the entire high-tech industry and its subordinate five typical industries are compared and analyzed. The results indicate that firstly, there are different relationships between the entire high-tech industry and subordinate industries as well as among subordinate industries; secondly, even with the same factor of TII, there are different effects on initial and final innovation performance in different subordinate industry; thirdly, both R&D input and non R&D input have a positive impact on innovation performance, and the high input is not always brings high performance in different industries. Finally, some policy suggestions and managerial implications are provided on how to improve the innovation performance of Chinese high-tech industry.

Key words: TII, innovation performance, high-tech industry, Griliches-Jaffe knowledge production function, stepwise regression analysis

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