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作 者:曹玉红[1] 尤建新[2] 赵连霞[1] CAO Yuhong;YOU Jianxin;ZHAO Lianxia(School of Management,Shanghai University,Shanghai 200444,China;School of Economics&Management,Tongji University,Shanghai 200092,China)
机构地区:[1]上海大学管理学院,上海200444 [2]同济大学经济与管理学院,上海200092
出 处:《同济大学学报(自然科学版)》2022年第7期1062-1072,共11页Journal of Tongji University:Natural Science
基 金:国家自然科学基金面上项目(71871134);上海市软科学研究计划重点项目(22692111500)。
摘 要:构建基于TOPSIS(technique for order preference by similarity to ideal solution)的最优组合权重赋权模型,对上海18个研发与转化功能性平台198项专利产出进行实证分析,研究创新点表现在两个方面:通过正负理想点构建优化的组合赋权模型,避免了现有研究中没有考虑专利是否能够成功转化的弊端;通过中位数检验验证了平台效率评估模型的合理性,避免了现有研究忽略对平台专利转化效率测度模型合理性进行验证的缺陷。实证发现,该研究构建的组合赋权模型专利转化风险鉴别能力(Z=5.546)较高,可以较为科学地判定研发与转化功能性平台的实际效率。Based on the idea of TOPSIS(Technique for Order Preference by Similarity to Ideal Solution),this research builds a multi-objective programming model to solve the optimal combination weights.It conducts an empirical analysis on the output of 198 patents on 18 R&D and transformation functional platforms in Shanghai,and finds that,the combination empowering model constructed in this study has a high identification capability of patent transformation risk(Z=5.546),which can determine the actual R&D efficiency of the platform more scientifically.Research innovations are manifested in two aspects:The multi-objective nonlinear programming model is constructed by positive and negative ideal points to carry out combination weighting,which avoids the disadvantages of the existing research,such as a large number of overlapping evaluation scores of patent failure conversion and successful transformation,and low distinguishing ability of the two types of transformation;Through the test of whether the efficiency score of failed transformation is significantly less than the median of the efficiency score of successful conversion,the rationality of efficiency evaluation model is verified,and the defect that existing research neglects to verify the rationality of platform patent conversion efficiency measurement model is avoided.
关 键 词:研发与转化功能性平台 效率评估 组合赋权 专利转化风险识别
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