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中国省域高校科技创新能力、效率及其经济贡献率研究
引用本文:李文辉,江涌芝,何秋锐,陈忠暖.中国省域高校科技创新能力、效率及其经济贡献率研究[J].重庆大学学报(社会科学版),2019,42(3):108-121.
作者姓名:李文辉  江涌芝  何秋锐  陈忠暖
作者单位:华南师范大学地理科学学院,广东广州,510631;华南师范大学公共管理学院,广东广州,510631
基金项目:国家自然科学基金重点项目"全球化背景下城市移民的人地互动与地方协商研究——以珠三角为例"(41630635);广东省科技计划项目"广东与一带一路沿线省份技术创新协同模式及其机制研究"(2017A030303073);广州市哲学社会科学"十三五"规划2018年度课题"广州科技创新一带一路合作机制研究"(2018GZGJ20)
摘    要:以中国省域高校2004-2016年数据为基础,借助SPSS统计工具,采用主成分分析法评价分析了省域高校的科技创新能力;采用两阶段数据包络分析模型(DEA)评价分析了省域高校的科技创新效率;借鉴"柯布-道格拉斯(C-D)生产函数"和索洛"增长速度方程",评价分析了省域高校的科技创新经济贡献率。将三个维度指标分别取平均值,高于平均值的数界定为"高",低于平均值的数界定为"低"。研究发现,三项指标和省份产生了如下对应结果:(1)高-高-高:辽宁、陕西、山东;(2)高-高-低:江苏、广东、浙江;(3)高-低-高:北京、上海、湖北、安徽;(4)低-高-高:吉林、广西、云南、内蒙古、贵州、海南;(5)高-低-低:四川、河南;(6)低-高-低:江西、福建、新疆;(7)低-低-高:湖南、天津、重庆;(8)低-低-低:黑龙江、河北、山西、甘肃。从表现为"高-高-高"的辽宁、陕西和山东3个省份情况看,科技创新能力、科技创新效率、经济贡献率和GDP增长率之间有一定的线性相关关系,研究结论与国家"双一流"高校建设情况也具有一定的一致性。

关 键 词:科技创新能力  科技创新效率  经济贡献率  高校  省域
修稿时间:2018/10/16 0:00:00

Research on the scientific and technological innovation ability, efficiency and economic contribution rate of Chinese provincial universities
LI Wenhui,JIANG Yongzhi,HE Qiurui and CHEN Zhongnuan.Research on the scientific and technological innovation ability, efficiency and economic contribution rate of Chinese provincial universities[J].Journal of Chongqing University(Social Sciences Edition),2019,42(3):108-121.
Authors:LI Wenhui  JIANG Yongzhi  HE Qiurui and CHEN Zhongnuan
Institution:School of Geography, South China Normal University, Guangzhou 510631, P. R. China,School of Geography, South China Normal University, Guangzhou 510631, P. R. China,School of Public Administration, South China Normal University, Guangzhou 510631, P. R. China and School of Geography, South China Normal University, Guangzhou 510631, P. R. China
Abstract:Based on the data collected from provincial universities in China from 2004 to 2016, SPSS statistical tools were used to evaluate the scientific and technological innovation capability by principal component analysis. The efficiency of scientific and technological innovation was evaluated by two-stage data envelopment analysis model (DEA). The contribution rate of scientific and technological innovation was evaluated by using the "Cobb-Douglas (C-D) production function" and Solow "growth rate equation". Average number for each of the three indicators was calculated, data higher than the average number was defined as "high", and data below the average number was defined as "low". Provinces were divided by their grades of the three indicators:1) high-high-high:Liaoning, Shaanxi, Shandong; 2) high-high-low:Jiangsu, Guangdong, Zhejiang; 3) high-low-high:Beijing, Shanghai, Hubei, Anhui; 4) low-high-high:Jilin, Guangxi, Yunnan, Inner Mongolia, Guizhou, Hainan; 5) high-low-low:Sichuan, Henan; 6) low-high-low:Jiangxi, Fujian, Xinjiang; 7) low-low-high:Hunan, Tianjin, Chongqing; 8) low-low-low:Heilongjiang, Hebei, Shanxi, Gansu. Found in Liaoning, Shaanxi and Shandong, there is a certain linear correlation between scientific and technological innovation capability, efficiency, economic contribution rate and GDP growth rate. The research conclusion is consistent with the situation of "Double First-Class" construction to a certain extent.
Keywords:scientific and technological innovation ability  scientific and technological innovation efficiency  economic contribution rate  universities  provinces
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