Research on the Influencing Factors of Technology Demand-Oriented Technology Transfer ——Taking 101 High-Tech Enterprises as Examples
Tang Luyuan1,2, Xie Shiyao3, Hu Siyang2
1. School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100010, China;
2. National Industrial Information Security Development Research Center, Beijing 100040, China;
3. Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
Abstract:Based on the field investigation of 101 high-tech enterprises and the diagnostic opinions of experts and scholars on the technical needs of sample enterprises, this paper puts forward four factors that affect the transformation efficiency of scientific and technological achievements, namely the clarity of technical needs, the technical Demand intensity, technology demand depth and technology demand fit.CART algorithm is used to handle the complex nonlinear relationship between variables, and conduct a comprehensive analysis of the factors affecting the transformation of technological achievements.The model training results show that the depth of technical requirements and the clarity of technical requirements are two important variables that affect the transformation of scientific and technological achievements.Based on the analysis of the empirical results, this paper finally puts forward a technical demand-oriented transformation plan of scientific and technological achievements.
唐露源, 谢士尧, 胡思洋. 技术需求导向的科技成果转化影响因素研究——以101家高新技术企业为例[J]. 中国科技论坛, 2023(4): 16-24.
Tang Luyuan, Xie Shiyao, Hu Siyang. Research on the Influencing Factors of Technology Demand-Oriented Technology Transfer ——Taking 101 High-Tech Enterprises as Examples. , 2023(4): 16-24.
[1]ROSEN D W.Thoughts on design for intelligent manufacturing[J].Engineering,2019,5 (4):609-614.
[2]CHEN Y D,HAN Z Y,CAO K Y,et al.Manufacturing upgrading in industry 4.0 era[J].Systems research and behavioral science,2020,37(4):766-771.
[3]UTTERBACK J M.Innovation in industry and the diffusion of technology[J].Science,1974,183 (4125):620-626.
[4]戚湧,朱婷婷,郭逸.科技成果市场转化模式与效率评价研究[J].中国软科学,2015 (6):184-192.
[5]邢晓昭,李善青,赵辉.科技成果转化成熟度评价研究进展[J].科技管理研究,2018,38 (13):71-76.
[6]王健,周宇华,杨永征.科研院所成果转化的制约因素[J].化工管理,2005 (9):13-16.
[7]张慧颖,史紫薇.科技成果转化影响因素的模糊认知研究——基于创新扩散视角[J].科学学与科学技术管理,2013,34 (5):28-35.
[8]DAS G G.Information age to genetic revolution:embodied technology transfer and assimilation:a tale of two technologies[J].Technological forecasting and social change,2007,74 (6):819-842.
[9]刘家树,菅利荣.科技成果转化效率测度与影响因素分析[J].科技进步与对策,2010,27 (20):113-116.
[10]王华统,曹光源,郭韧.影响科技成果转化的主成分分析[J].运筹与管理,2003,12 (6):123-126.
[11]罗雪英,傅云.基于 ISM 的高校科技成果转化影响因素分析[J].闽江学院学报,2012,33 (5):130-134.
[12]汪小梅,汪令涛,李鹏.科研院所科技成果转化能力的多目标评价研究[J].科技管理研究,2016,36 (20):83-87.
[13]王萌.科技人员股权激励对科技成果转化绩效的影响研究[D].西安:西安理工大学,2017.
[14]姚思宇,何海燕.高校科技成果转化影响因素研究:基于Ordered Logit模型实证分析[J].教育发展研究,2017 (9):51-58.
[15]洪永淼,汪寿阳.数学、模型与经济思想[J].管理世界,2020,36 (10):15-27.
[16]李春生,焦海涛,刘澎,等.基于C4.5决策树分类算法的改进与应用[J].计算机技术与发展,2020,30 (5):185-189.
[17]徐旭冉,涂娟娟.基于决策树算法的空气质量预测系统[J].电子设计工程,2019,27 (9):39-42.
[18]陈茜,马向平,贾承丰,等.基于决策树ID3算法的人才留汉吸引政策研究[J].武汉理工大学学报 (信息与管理工程版),2019,41 (2):148-153.
[19]罗计根,杜建强,聂斌,等.融合GINI指数的ID3改进算法[J].南昌大学学报 (工科版),2019,41 (1):80-84.
[20]WU X,KUMAR V,ROSS Q J,et al.Top 10 algorithms in data mining[J].Knowledge and information systems,2008,14 (1):1-37.
[21]周涛,吉卫喜,宋承轩.基于决策树C4.5算法的制造过程质量管理[J].组合机床与自动化加工技术,2018 (12):134-136,141.
[22]吴薇,张源,李强子,等.基于迭代CART算法分层分类的土地覆盖遥感分类[J].遥感技术与应用,2019,34 (1):68-78.
[23]王茵,郭红钰.基于CART的社区矫正人员危险性评估[J].计算机与现代化,2018 (8):73-78.
[24]HAN J,MAO K,XU T,et al.A soil moisture estimation framework based on the CART algorithm and its application in China[J].Journal of hydrology,2018,563:65-75.
[25]江志农,魏东海,王磊,等.基于CART决策树的柴油机故障诊断方法研究[J].北京化工大学学报 (自然科学版),2018,45 (4):71-75.
[26]霍国庆,李捷,张古鹏.我国战略性新兴产业技术创新理论模型与经典模式[J].科学学研究,2017,35 (11):1623-1630.
[27]岳宇君,马艺璇,张磊雷.政府补贴、技术创新与高新技术企业高质量发展[J].南京财经大学学报,2022 (2):46-54.
[28]贺红.科技成果向现实生产力转化的初步研究[J].科技管理研究,2006 (6):71-73.
[29]李牧南,吴泽宇,张璇.高技术企业研发效率与信息技术投入效率的关系[J].科技管理研究,2022,42 (6):89-96.
[30]霍国庆.科技成果转化的创新模式与思考[J].智库理论与实践,2019,4 (4):71-74.
[31]朱家秀.产学研合作、研发投入对企业创新绩效的影响研究[J].经济研究导刊,2021 (34):18-20.
[32]熊利芝,袁志忠,吴玉先,等.校企联合共建实验室模式探讨[J].科技视界,2017 (1):134.
[33]霍国庆.我国科技成果转移转化的根本症结及其解决策略[J].智库理论与实践,2016 (2):119-125.
[34]董洁,黄付杰.中国科技成果转化效率及其影响因素研究:基于随机前沿函数的实证分析[J].软科学,2012,26 (10):15-20.
[35]郭颖,段炜钰,孟婧,等.中国科学院产学研合作网络特征对其科技成果转化绩效的影响[J].中国科技论坛,2022 (5):81-89.
[36]刘家树,菅利荣.科技成果转化效率测度与影响因素分析[J].科技进步与对策,2010,27 (20):113-116.
[37]罗茜,高蓉蓉,曹丽娜.高校科技成果转化效率测度分析与影响因素扎根研究:以江苏省为例[J].科技进步与对策,2018,35 (5):43-51.
[38]张明喜,郭戎.从科技成果转化率到转化效率:指标体系设计与实证分析[J].软科学,2013,27 (12):85-89,139.