基于三阶段DEA模型的创新效率评价研究——以节能环保上市公司为例
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摘要
通过构建节能环保上市公司创新效率评价指标体系,采用三阶段DEA模型对2015年56家节能环保上市公司的创新效率进行测度。研究结果表明,剔除环境因素和统计噪声的影响后,大部分节能环保上市公司的技术效率和规模效率均得到提高,纯技术效率略有下降,规模收益呈递增状态的上市公司居多,环境因素制约了节能环保上市公司的创新效率。东部地区节能环保上市公司的创新效率高于中部,中部高于西部。最后提出了创新效率改进的建议,促进节能环保产业健康发展。
In this paper, the innovation performance evaluation index system of energy-saving and environmentally friendly listed companies is established, and the innovation efficiency of 56 Energy conservation and environment protection listed companies in 2016 is evaluated with the three-stage DEA model. The results show that both the technical efficiency and scale efficiency of most energy-saving and environmentally friendly listed companies is improved after stripping the environment variables and the statistical noise, while pure technical efficiency decreases lightly, returns to scale in most listed companies are increasing, and environment variables restrict innovation efficiency of the listed companies. This paper gives suggestions for innovation efficiency to promote the healthy development of energy-saving and environmentally friendly industry.
In this paper, the innovation performance evaluation index system of energy-saving and environmentally friendly listed companies is established, and the innovation efficiency of 56 Energy conservation and environment protection listed companies in 2016 is evaluated with the three-stage DEA model. The results show that both the technical efficiency and scale efficiency of most energy-saving and environmentally friendly listed companies is improved after stripping the environment variables and the statistical noise, while pure technical efficiency decreases lightly, returns to scale in most listed companies are increasing, and environment variables restrict innovation efficiency of the listed companies. This paper gives suggestions for innovation efficiency to promote the healthy development of energy-saving and environmentally friendly industry.
引文
[1]张危宁,朱秀梅,柳青等.高技术产业集群创新绩效评价指标体系设计[J].工业技术经济,2006,25(11):57-59.
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[3] Shen K,Marxism S O. Evaluation Dimension of Innovation Performance of Enterprise′s R&D Personnel and Its Effect Mechanism[J]. Technology Economics,2017.
[4]樊琦,韩民春.政府R&D补贴对国家及区域自主创新产出影响绩效研究———基于中国28个省域面板数据的实证分析[J].管理工程学报,2011,25(3):183-188.
[5]马文聪,侯羽,朱桂龙.研发投入和人员激励对创新绩效的影响机制———基于新兴产业和传统产业的比较研究[J].科学学与科学技术管理,2013,34(3):58-68.
[6]张晓黎,覃正.知识基础能力、研发投入与技术创新绩效关系研究———基于全球R&D领先通信及技术设备制造类企业的实证分析[J].科技进步与对策,2013,30(11):140-144.
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[13]杨青峰.剥离环境因素的中国区域高技术产业技术效率再估计———基于三阶段DEA模型的研究[J].产业经济研究,2014(4):94-102.
[14]丁亚峰,杨陈.股权集中度、研发投入对创新绩效的影响———基于不同市场结构的比较研究[J].财会通讯,2015(21):46-49.
[15]刘华,张玉蓉.高技术产业R&D投入现状及影响研究——以湖北省为例[J].财会通讯,2015(10):42-44.
[16]黄海霞,张治河.中国战略性新兴产业的技术创新效率———基于DEAMalmquist指数模型[J].技术经济,2015,34(1):21-27.
[17]刘满凤,李圣宏.基于三阶段DEA模型的我国高新技术开发区创新效率研究[J].管理评论,2016,28(1):42-52.
[18]刘明广.基于DEA-Malmquist指数法的广东区域创新体系创新效率动态评价[J].统计与管理,2017(1):67-71.
[19] Khoshnevis P,Teirlinck P. Performance evaluation of R&D active firms[J]. Socio-Economic Planning Sciences,2017.
[20] Gkypali A,Filiou D,Tsekouras K. R&D collaborations:Is diversity enhancing innovation performance?[J]. Technological Forecasting&Social Change,2017.
[21] Fried H O,Lovell C A K,Schmidt S S,et al. Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis[J].Journal of Productivity Analysis,2002,17(1-2):157-174.
[22] Banker R D,Charnes A,Cooper W W. Some models for the estimation of technical and scale inefficiencies in data envelopment analysis[J].Management Science,1984:1078-1092.
[23]熊正德,阳芳娟,万军.基于两阶段DEA模型的上市公司债权融资效率研究———以战略性新兴产业新能源汽车为例[J].财经理论与实践,2014(5):51-56.
[2]易朝辉,陈朝晖.创新绩效评价指标体系演变的国际比较及其启示[J].科技管理研究,2014,34(6):61-65.
[3] Shen K,Marxism S O. Evaluation Dimension of Innovation Performance of Enterprise′s R&D Personnel and Its Effect Mechanism[J]. Technology Economics,2017.
[4]樊琦,韩民春.政府R&D补贴对国家及区域自主创新产出影响绩效研究———基于中国28个省域面板数据的实证分析[J].管理工程学报,2011,25(3):183-188.
[5]马文聪,侯羽,朱桂龙.研发投入和人员激励对创新绩效的影响机制———基于新兴产业和传统产业的比较研究[J].科学学与科学技术管理,2013,34(3):58-68.
[6]张晓黎,覃正.知识基础能力、研发投入与技术创新绩效关系研究———基于全球R&D领先通信及技术设备制造类企业的实证分析[J].科技进步与对策,2013,30(11):140-144.
[7]陈收,邹增明,刘端.技术创新能力生命周期与研发投入对企业绩效的影响[J].科技进步与对策,2015(12):72-78.
[8]周江华,李纪珍,刘子谞等.政府创新政策对企业创新绩效的影响机制[J].技术经济,2017,36(1):57-65.
[9]赵树宽,余海晴,巩顺龙.基于DEA方法的吉林省高技术企业创新效率研究[J].科研管理,2013,34(2):36-43.
[10]苏屹,李柏洲.基于随机前沿的区域创新系统创新绩效分析[J].系统工程学报,2013,28(1):125-133.
[11]汪晓梦.区域性技术创新政策绩效评价的实证研究——基于相关性和灰色关联分析的视角[J].科研管理,2014,35(5):38-43.
[12]尹惠斌,游达明.基于BP神经网络的企业突破性创新绩效评价研究[J].软科学,2014,28(5):125-129.
[13]杨青峰.剥离环境因素的中国区域高技术产业技术效率再估计———基于三阶段DEA模型的研究[J].产业经济研究,2014(4):94-102.
[14]丁亚峰,杨陈.股权集中度、研发投入对创新绩效的影响———基于不同市场结构的比较研究[J].财会通讯,2015(21):46-49.
[15]刘华,张玉蓉.高技术产业R&D投入现状及影响研究——以湖北省为例[J].财会通讯,2015(10):42-44.
[16]黄海霞,张治河.中国战略性新兴产业的技术创新效率———基于DEAMalmquist指数模型[J].技术经济,2015,34(1):21-27.
[17]刘满凤,李圣宏.基于三阶段DEA模型的我国高新技术开发区创新效率研究[J].管理评论,2016,28(1):42-52.
[18]刘明广.基于DEA-Malmquist指数法的广东区域创新体系创新效率动态评价[J].统计与管理,2017(1):67-71.
[19] Khoshnevis P,Teirlinck P. Performance evaluation of R&D active firms[J]. Socio-Economic Planning Sciences,2017.
[20] Gkypali A,Filiou D,Tsekouras K. R&D collaborations:Is diversity enhancing innovation performance?[J]. Technological Forecasting&Social Change,2017.
[21] Fried H O,Lovell C A K,Schmidt S S,et al. Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis[J].Journal of Productivity Analysis,2002,17(1-2):157-174.
[22] Banker R D,Charnes A,Cooper W W. Some models for the estimation of technical and scale inefficiencies in data envelopment analysis[J].Management Science,1984:1078-1092.
[23]熊正德,阳芳娟,万军.基于两阶段DEA模型的上市公司债权融资效率研究———以战略性新兴产业新能源汽车为例[J].财经理论与实践,2014(5):51-56.