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我国涉农企业科技成果转化效率提升路径研究——基于SSBM-网络DEA与Light GBM方法 被引量:6

Research on the Improvement Path of Transformation Efficiency of Scientific and Technological Achievements of Agricultural Enterprises:Method based on SSBM-network DEA and LightGBM
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摘要 涉农企业科技成果转化效率关乎农业科技与经济“两张皮”问题,为此本文在构建SSBM-网络DEA模型测算涉农企业科技成果转化效率的基础上,基于系统论的视角,构建涉农企业科技成果转化生态系统,将涉农科技成果转化效率影响路径分解为转化能力、转化保障、转化动力与转化环境四大指标,共10项二级指标,并使用LightGBM机器学习方法探究其路径优化问题,主要得到以下研究结论。(1)2009—2017年我国涉农企业科技成果转化效率整体呈上升趋势,但均值仅为0.421,整体效率损失较大。(2)涉农企业科技成果转化效率主要由转化能力贡献(贡献度为68.93%);转化保障、转化动力与转化环境的贡献度较低(贡献度分别为15.64%、14.73%与0.7%),突出表现在协同创新、融资环境与制度环境的促进作用不明显。为此,提出了优化我国涉农企业科技成果转化效率的政策建议。 Agricultural enterprise transformation of scientific and technological achievements about agricultural science and technology and economic efficiency“two skins”problem,this paper in constructing SSBM-network DEA model on the basis of measuring the efficiency of agricultural enterprise transformation of scientific and technological achievements,based on the perspective of system theory,build agricultural enterprise ecological system transformation of scientific and technological achievements,and will affect the path of agriculture science and technology achievements transformation efficiency is decomposed into ability,the guarantee of the conversion,the power transformation and transformation environment four indicators,a total of 10 secondary indexes,and LightGBM machine learning method is used to explore the path optimization problem,basically have the following research conclusions:(1)From 2009 to 2017,the overall efficiency of transformation of scientific and technological achievements of my country’s agricultural enterprises showed an upward trend,but the average value was only 0.421,and the overall efficiency loss was relatively large.(2)The transformation efficiency of agricultural enterprises’scientific and technological achievements is mainly contributed by transformation ability(contribution rate is 68.93%);the contribution rate of transformation guarantee,transformation power and transformation environment is low(contribution rate is 15.64%,14.73%and 0.7%respectively),Which is prominently manifested in that the promotion of collaborative innovation,financing environment and institutional environment is not obvious.To this end,policy recommendations for optimizing the transformation efficiency of scientific and technological achievements of my country’s agricultural-related enterprises are put forward.
作者 林青宁 毛世平 LIN Qingning;MAO Shiping
出处 《农业技术经济》 CSSCI 北大核心 2022年第5期4-17,共14页 Journal of Agrotechnical Economics
基金 国家自然科学基金面上项目“农业企业科技成果转化效率研究:基于企业技术创新能力的视角”(编号:71673275) 国家自然科学基金国际(地区)合作与交流项目“中非农业技术转移机制及效果评估研究”(编号:71761147005) 中国农业科学院创新工程项目“涉农企业开展创新活动研究”(编号:ASTIP-IAED-2019-05)。
关键词 涉农企业 科技成果转化效率 LightGBM算法 网络DEA 机器学习 Agricultural enterprises Innovation ecosystem LightGBM algorithm Network DEA Machine learning
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