管理评论 ›› 2021, Vol. 33 ›› Issue (2): 97-107.

• 技术与创新管理 • 上一篇    下一篇

基于J-SBM三阶段DEA模型的区域低碳创新网络效率研究

徐建中, 赵亚楠   

  1. 哈尔滨工程大学经济管理学院, 哈尔滨 150001
  • 收稿日期:2017-11-21 出版日期:2021-02-28 发布日期:2021-03-08
  • 通讯作者: 赵亚楠(通讯作者),哈尔滨工程大学经济管理学院博士研究生
  • 作者简介:徐建中,哈尔滨工程大学经济管理学院教授,博士生导师,博士。
  • 基金资助:
    国家自然科学基金项目(71273072);黑龙江省哲学社会科学研究规划项目(17JYH49);黑龙江省经济社会发展重点研究课题(KY10900170004)。

Research on the Efficiency of Regional Low Carbon Innovation Network Based on J-SBM Three-stage DEA Model

Xu Jianzhong, Zhao Yanan   

  1. School of Economics and Management, Harbin Engineering University, Harbin 150001
  • Received:2017-11-21 Online:2021-02-28 Published:2021-03-08

摘要: 针对创新驱动发展战略下我国区域低碳创新网络发展面临的可持续转型增长的问题与挑战以及外部环境对效率影响作用,构建包含非期望产出的区域低碳创新网络效率评价体系,基于我国2006—2015年区域面板数据,利用改进的J-SBM三阶段DEA模型测算区域低碳创新网络效率,探讨环境因素和随机干扰对区域低碳创新网络效率的影响机理以及低碳创新网络的生产模式,在方法和内容上揭示我国低碳创新网络发展面临的挑战形势中的“黑箱”。研究表明:环境因素和随机干扰对投入松弛变量的影响存在异质性,且在未考虑环境因素和随机干扰时绝大多数地区的低碳创新网络效率被低估;我国区域低碳创新网络效率呈稳步上升态势,北京、上海两个地区位于效率的前沿面上,大多数地区仍有较大的提升空间;我国区域低碳创新网络的生产模式位于“低投入低效率”象限的比例最大。

关键词: 创新网络效率, 低碳创新, J-SBM模型, 三阶段DEA, 非期望产出

Abstract: Under the strategy of innovation-driven development, aiming at meeting the challenges of the sustainable transformation and growth and dealing the impact of external environment on efficiency in the development of low-carbon innovation network in China, this paper builds the evaluation system of regional low-carbon innovation network including undesirable output. Based on the regional panel data from 2006 to 2015, this paper employs modified J-SBM three-stage DEA model to evaluate the regional low carbon innovation network efficiency, also analyzes influence mechanism of the environment factors and the random disturbance, and discusses the production mode of low carbon innovation network. On top of that, in terms of method and content of low carbon innovation network development, the “black box” is revealed in the challenging situation of China. The research shows that: the influence of environmental factors and random disturbance on the input slack variable is heterogeneity, and the low carbon innovation network efficiency is underestimated in most areas without considering environmental factors and random disturbances. Regional low carbon innovation network efficiency has steadily risen, Beijing and Shanghai are at the forefront of efficiency, and in most parts of China, there is still a large space to improve efficiency. The production mode of regional low carbon innovation network occupies the most of quadrant of low input and low efficiency region.

Key words: innovation network efficiency, low carbon Innovation, J-SBM model, three-stage DEA model, undesirable output