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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References
[1] Schumpeter J. A. the Theory of Economic Development [M]. Cambridge, MA: Harvard University Press, 1912
[2] Hemmert M. The influence of institutional factors on the technology acquisition performance of high-tech firms: survey results from Germany and Japan [J]. Research Policy, 2004, 33(6-7):1019-1039
[3] Jonker M, Romijn H and Szirmai A. Technological effort, technological capabilities and economic performance: a case study of the paper manufacturing sector in West Java [J]. Technovation, 2006, 26(1): 121 134.
[4] Llu s Santamar a, Mar a Jes s Nieto, Andr s Barge-Gil. Beyond formal R&D: Taking advantage of other sources of innovation in low- and medium-technology industries [J]. Research Policy, 2009, 38(3):507-517
[5] Wang Chun-hsien, Lub Iuan-yuan and Chen Chie-bein. Evaluating firm technological innovation capability under uncertainty[J]. Technovation, 2008, 28(6):349-363
[6] 周青, 曾德明. 高新技术企业R&D绩效测度与实证分析[J]. 科学学与科学技术管理, 2003(11):13-15
[7] 朱有为,徐康宁. 中国高技术产业研发效率的实证研究[J] . 中国工业经济, 2006(11):38-45
[8] 郭国峰, 温军伟, 孙保营. 技术创新能力的影响因素—基于中部六省面板数据的实证分析[J]. 数量经济技术经济研究, 2007, 24(9):134-143
[9] 王立成, 牛勇平. 科技投入与经济增长:基于我国沿海三大经济区域的实证分析[J]. 中国软科学, 2010(8):169-177
[10] 官建成, 陈凯华. 我国高技术产业技术创新效率的测度[J]. 数量经济技术经济研究, 2009, 26(1):119-122
[11] 何文章, 郭鹏. 关于灰色关联度中的几个问题的探讨[J]. 数理统计与管理, 1999(10):19-33
[12] Chesbrough H. Open innovation, the new imperative for creating and profiting from technology [M]. Harvard business school press, 2003.
[13] 陈劲, 陈钰芬. 开放创新体系与企业技术创新资源配置[J]. 科研管理, 2006, 27(3):1-8
[14] 傅家骥. 技术创新学[M]. 北京:清华大学出版社,2006.
[15] Liu X H, Buck T. Innovation Performance and Channels f or International Technology Spillovers: Evidence from Chinese High-tech Industries [J]. Research Policy, 2007, 36 (3):355-366
[16] Guan J C, Gao X. Exploring the H-index at Patent Level [J]. Journal o f the American Society for Information Science and Technology, 2009, 60 (1):35-40
[17] 张宗和, 彭昌奇. 区域技术创新能力影响因素的实证分析—基于全国30个省市区的面板数据[J]. 中国工业经济, 2009(11):35-43
[18] Griliches Z. Issues in Assessing the Contribution of Research and Development to Productivity Growth [J]. Bell Journal of Economics, 1979, 10(1):92-116
[19] Jaffe, A. B. Real Effects of Academic Research [J]. American Economic Review, 1989, 79 (5):957-970.
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