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  • 主管单位:
  • 上海市教育委员会
  • 主办单位:
  • 上海理工大学
  • 主  编:
  • 庄松林
  • 地  址:
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  • 邮政编码:
  • 200093
  • 联系电话:
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  • 电子邮件:
  • xbzrb@usst.edu.cn
  • 国际标准刊号:
  • 1007-6735
  • 国内统一刊号:
  • 31-1739/T
  • 邮发代号:
  • 4-401
  • 单  价:
  • 15.00
  • 定  价:
  • 90.00
王鸣涛,叶春明,赵灵玮.基于CRITIC和TOPSIS的区域工业科技创新能力评价研究[J].上海理工大学学报,2020,42(3):258-268.
基于CRITIC和TOPSIS的区域工业科技创新能力评价研究
Evaluation of regional industrial S&T innovation capability based on CRITIC and TOPSIS
投稿时间:2019-05-24  
DOI:10.13255/j.cnki.jusst.20190524001
中文关键词:  区域  工业  科技创新能力  基于指标相关性的权重确定法  逼近理想解排序法
英文关键词:regional  industry  S&T innovation capability  CRITIC  TOPSIS
基金项目:国家自然科学基金资助项目(71840003)
作者单位E-mail
王鸣涛 安阳师范学院 计算机与信息工程学院安阳 455000 yechm6464@163.com 
叶春明 上海理工大学 管理学院上海 200093  
赵灵玮 上海理工大学 管理学院上海 200093  
摘要点击次数: 150
全文下载次数: 239
中文摘要:
      为有效评价区域工业科技创新能力,构建了融合绝对值指标和平均值指标的评价指标体系。以28个地区为研究对象,基于目前最新的2014—2017年数据,使用基于指标相关性的权重确定法(CRITIC)确定指标权重,运用逼近理想解排序法(TOPSIS)从“静态”和“动态”两个视角评价,识别出各地区工业科技创新能力的现状和发展。研究发现,技术引进、自主创新、R&D人员和经费、R&D项目活跃度、科技成果转化始终是影响各地区工业科技创新能力提升的重要因素。“静态”评价结果显示,中国工业科技创新能力总体一般,地区间差异较大,“很强”和“较强”的地区只有广东、江苏、上海、北京、浙江和山东6个省市。“动态”评价结果显示,工业科技创新能力发展存在明显的区域依存,强弱格局比较稳定,短期内难以改变。研究成果表明,该指标体系和模型能够有效评价区域工业科技创新能力。最后,结合重要影响因素,给出提升工业科技创新能力的建议。
英文摘要:
      In order to effectively evaluate the regional industrial S&T innovation capability, an evaluation index system integrating absolute value indexes and average value indexes was constructed. Based on the latest data of 28 regions from 2014 to 2017, the weights of indicators were determined by CRITIC method and the current situation and development of industrial S&T innovation capability in 28 regions were identified by TOPSIS method from two perspectives of "static" and "dynamic" evaluation. It is found that technology introduction, independent innovation, R&D personnel and funds, R&D project activity, and the transformation of S&T achievements are always the important factors affecting the upgrading of regional industrial S&T innovation capability. The results of "static" evaluation show that China's industrial S&T innovation capability is general as a whole, with great regional differences. Only six provinces and cities namely Guangdong, Jiangsu, Shanghai, Beijing, Zhejiang and Shandong are "very strong" and "strong". The results of "dynamic" evaluation show that there is obvious regional dependence in the development of industrial S&T innovation capability, the pattern of strength and weakness is relatively stable, and it is difficult to change in short term. The research results also show that the index system and model presented can effectively evaluate the regional industrial S&T innovation ability. Finally, combined with the important affecting factors, some suggestions were given to improve the innovation ability of industrial S&T.
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