创新价值链视角下的我国区域创新效率提升路径研究

科研管理 ›› 2014, Vol. 35 ›› Issue (5): 27-37.

创新价值链视角下的我国区域创新效率提升路径研究

余泳泽¹, 刘大勇²

1. 南京财经大学江苏产业发展研究院, 江苏南京 210046;
2. 南开大学经济学院, 天津 300071

收稿日期:2012-06-12 修回日期:2013-06-26 出版日期:2014-05-25 发布日期:2014-05-21
作者简介:余泳泽（1982-），男（汉），河北人，南京财经大学产业发展研究院讲师，中国社科院工业经济研所博士后，研究方向：技术进步与产业成长。
刘大勇（1985-），男（汉），天津，南开大学经济学院博士，研究方向：产业成长。
基金资助:
江苏高校优势学科建设工程项目资助；教育部2011年博士研究生学术新人奖暨专款资助。

The study on the path of improvement in China’s regional innovation efficiency from the perspective of innovation value chain

Yu Yongze¹, Liu Dayong²

1. Jiangsu Industry Development Research Institute, Nanjing University of Finance & Economics, Nanjing 210046, Jiangsu, China;
2. School of Economics, Nankai University, Tianjin 300071, China

Received:2012-06-12 Revised:2013-06-26 Online:2014-05-25 Published:2014-05-21

摘要/Abstract

摘要： 本文基于创新价值链视角，将创新过程按阶段分为知识创新、研发创新和产品创新，利用三阶段DEA模型考察了各阶段创新效率。本文研究表明，知识创新整体创新效率为0.582，研发创新整体效率为0.284，产品创新整体效率为0.529，东部地区各阶段创新效率明显高于中西部地区，尤其在研发效率上表现的更加明显。基于以上研究结论，本文利用二维矩阵的方式将各地区各阶段创新效率划分为四种类型，进而不同的地区可以根据自身优势和劣势选择适宜的创新效率提升路径。

关键词: 创新价值链, 区域创新效率, 提升路径, 三阶段DEA

Abstract: This paper divides the innovation process into knowledge innovation, research and development innovation and product innovation, and uses the three stage DEA model to study the innovative efficiency with the perspective of innovation value chain. This research shows that knowledge innovation efficiency is 0.582, the R&D innovation efficiency is 0.284 and the product innovation efficiency is 0.529. Meanwhile the efficiencies of eastern region are significantly higher than the central and western regions, especially in R&D innovation efficiency. Based on the conclusion above, this paper takes advantage of two-dimensional matrix to classify the regional innovation efficiency into four types for every innovative stage and finds that different regions should choose its appropriate innovation efficiency promotion path according to their own advantages and disadvantages.

Key words: innovation value chain, regional innovation efficiency, path of improvement, three stage DEA Model

中图分类号:

F062.4

余泳泽, 刘大勇. 创新价值链视角下的我国区域创新效率提升路径研究[J]. 科研管理, 2014, 35(5): 27-37.

Yu Yongze, Liu Dayong. The study on the path of improvement in China’s regional innovation efficiency from the perspective of innovation value chain[J]. Science Research Management, 2014, 35(5): 27-37.

参考文献

[1] 史修松,赵曙东,吴福象. 中国区域创新效率及其空间差异研究[J]. 数量经济技术经济研究,2009(3):45-52. [2] 刘顺忠,官建成. 区域创新系统创新绩效的评价[J]. 中国管理科学,2002(01):75-81. [3] 余泳泽. 要素集聚、政府支持与科技创新效率[J]. 经济评论,2011(02):93-98. [4] 白俊红,江可申,李婧. 中国区域创新效率的收敛性分析[J]. 财贸经济,2008(09):119-124. [5] 白俊红,蒋伏心. 考虑环境因素的区域创新效率研究---基于三阶段DEA方法[J]. 财贸经济,2011(10):104-110. [6] 陈劲,陈钰芬. 企业技术创新绩效评价指标体系研究[J]. 科学学与科学技术管理,2006(03):86-92. [7] 庞瑞芝,李鹏. 中国工业创新:过程、效率与模式--基于2001-2008年大中型工业企业的数据[J]. 产业经济研究,2011(02):1-8. [8] 余泳泽. 我国高技术产业技术创新效率及其影响因素研究--基于价值链视角下的两阶段分析[J]. 经济科学,2009(4):62-74. [9] 余泳泽. 政府支持、制度环境、FDI与我国区域创新体系建设[J]. 产业经济研究,2011(02):47-52. [10] Hansen, M.T., and Birkinshaw,J. The innovation value chain[J]. Harvard Business Review, 2007, 85(6):121-135. [11] Sherer, S. From supply-chain management to value network advocacy: implications for e-supply chains[J]. Supply chain management. 2005 (10): 77-83. [12] Kramer M R. Creating shared value[J]. Harvard business review. 2011 (89): 62-77. [13] Lee J, Gereffi G, Beauvais J. Global value chains and agrifood standards: Challenges and possibilities for smallholders in developing countries[J]. Proceedings of the National Academy of Sciences, 2012, 109(31): 12326-12331. [14] Batz, J. Predicting technology adoption to improve research priority setting[J]. Agricultural economics. 2003(28): 151-164. [15] Hansen, E. Introduction to the special issue on innovation and entrepreneurship in the forest sector[J]. Forest Policy and Economics. 2006(8): 669-673. [16] Comin, D. A new approach to measuring technology with an application to the shape of the diffusion curves[J]. The Journal of Technology Transfer. 2008 (33): 187-207. [17] Ghebremichael A, Potter-Witter K. Effects of tax incentives on long-run capital formation and total factor productivity growth in the Canadian sawmilling industry[J]. Forest Policy and Economics, 2009, 11(2): 85-94. [18] Fried, H.O.,Lovell,C.A.K,S.Schmidt and,S.Yaisawarng. Accounting for environment effects and statistical noise in data envelopment analysis[J]. Journal of Productivity Analysis,2002,17:157-174. [19] 牛泽东,张倩肖. FDI创新溢出与门槛效应--基于非线性面板平滑转换回归模型的分析[J]. 产业经济研究,2011(06):52-59. [20] 陈钊,陆铭,金煜. 中国人力资本和教育发展的区域差异:对于面板数据的估算[J].世界经济, 2004(12):25-31. [21] Nasierow, S., and F.J.,Arcelus. On the efficiency of national innovation systems[J]. Socioeconomic Planning Sciences, 2003,37 (3):215.