中国省域科技创新效率演化及其影响因素研究

科研管理 ›› 2012, Vol. 33 ›› Issue (1): 10-18,26.

中国省域科技创新效率演化及其影响因素研究

樊华^1,2, 周德群¹

1. 南京航空航天大学经济与管理学院, 江苏南京 210016;
2. 淮海工学院, 江苏连云港 222005

收稿日期:2010-03-30 修回日期:2011-01-14 出版日期:2012-01-27 发布日期:2012-02-03
作者简介:樊华(1962- ),男(汉),江苏张家港市人,博士,南京航空航天大学管理科学与工程博士后,淮海工学院教授;研究方向:教育科技与经济系统,能源经济与管理,可持续发展理论与实践。周德群(1963- ),男(汉),江苏建湖人。南京航空航天大学经济与管理学院常务副院长,博士,特聘教授,博士生导师,研究方向为管理科学与工程,能源-经济-环境系统。
基金资助:
国家自然科学基金项目(考虑影响因素交互作用和能源回弹效应的能效政策分析模型,编号:70873058);中国博士后科学基金资助项目(高等教育-科技-经济复合系统协调发展研究,编号:20090451209)和江苏省博士后科研资助计划项目(区域高等教育-科技-经济复合系统协调发展研究,编号:0901123C)。

Regional science and technology innovation efficiency evolution and its affect factors in Chinese provinces

Fan Hua^1,2, Zhou Dequn¹

1. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
2. Huaihai Institute of Technology, Lianyungang 222005, China

Received:2010-03-30 Revised:2011-01-14 Online:2012-01-27 Published:2012-02-03

摘要/Abstract

摘要： 本文运用规模报酬可变的DEA模型测度2000-2007年中国省域科技创新效率并分析其收敛性和影响因素。研究发现:科技创新效率具周期性波动演化特点;东部省域科技创新效率高于中西部省域,西部省域科技创新效率提高快,赶上并超过了中部省域;西部省域科技创新效率具有绝对和条件收敛特征;全国和东中部省域科技创新效率条件收敛显著,绝对收敛特征不明显;考察期内工业结构、对外开放度、高等教育发展水平对科技创新效率具有正影响效应,而政府影响力具有负向作用。研究结果为国家及地区科技创新效率政策提供参考信息。

关键词: 科技创新效率, DEA, 收敛性, Tobit模型, 面板数据

Abstract: Based on the panel data of China’s provinces during the period of 2000-2007, an empirical analysis on the scientific and technology innovation efficiency and its convergence and influence factors is conducted by using the Data Envolopment Analysis(DEA) model of variable scale returns. The results are as follows:the scientific and technology innovation efficiency has the character of periodic undulation evolution; the east provinces have higher innovation efficiency than that for the middle and west provinces, the efficiency for west provinces enhances quickly, has caught up with and surpassed the efficiency for middle provinces; the west provinces have the absolute and conditional convergence; the conditional convergence of the whole country and the east-middle area is remarkable, however, the absolute convergence is not obvious; the industry structure, the openness, and the higher education level of development have the positive influence on the efficiency, meanwhile the government effect has the negative impact on scientific and technology innovation efficiency. The conclusions will provide enlightenments for the policy of national scientific and technology innovation efficiency.

Key words: science and technology innovation efficiency, DEA, convergence, Tobit model, panel data

中图分类号:

F207

樊华, 周德群. 中国省域科技创新效率演化及其影响因素研究[J]. 科研管理, 2012, 33(1): 10-18,26.

Fan Hua, Zhou Dequn. Regional science and technology innovation efficiency evolution and its affect factors in Chinese provinces[J]. Science Research Management, 2012, 33(1): 10-18,26.

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