摘要
以2005到2020年的中国规模以上工业企业经营数据为基础,采用三阶段DEA模型就其研发投入与产出情况进行了实证分析,结果表明创新效率情况良好,但离最优值还有一定的距离.在剔除了外部因素的影响后,平均纯技术效率基本保持不变,而平均综合技术效率和平均规模效率轻微下降,但对各年度的综合技术效率、纯技术效率和规模效率有比较大的影响,并且存在投入不足和冗余的问题,说明环境因素和随机误差对评价工业企业的技术创新绩效有影响,三阶段DEA模型更能准确地评价工业企业的技术创新绩效,为避免造成资源浪费,工业企业需要寻找适度的发展规模,努力通过提高规模效率而最终提高综合技术效率,并根据研究成果提出了相应的对策建议.
Based on the operating data of China's industrial enterprises above designated size from 2005 to 2020,the threestage DEA model is used to conduct an empirical analysis on their R&D input and output.The results show that the innovation efficiency is good,but there is still a certain distance from the optimal value.After excluding the influence of external factors,through comparative analysis,the average pure technical efficiency remains basically unchanged,while the average comprehensive technical efficiency and average scale efficiency decrease slightly,which has a relatively large impact on the comprehensive technical efficiency,pure technical efficiency and scale efficiency of each year,and there are problems of insufficient investment and redundant investment,indicating that environmental factors and random errors have an impact on evaluating the technological innovation performance of industrial enterprises.The three-stage DEA model can more accurately evaluate the technological innovation performance of industrial enterprises.In order to avoid waste of resources,industrial enterprises need to find a suitable development scale,and ultimately improve the overall technical efficiency by improving the scale efficiency,and put forward corresponding countermeasures and suggestions according to theresearchresults.
出处
《科学决策》
CSSCI
2022年第9期111-121,共11页
Scientific Decision Making
关键词
创新
三阶段DEA模型
效率
innovation
three-stageDEAmodel
efficiency
