基于三阶段数据包络分析的国内众创空间创新效率研究

Research on Innovation Efficiency of Makerspace Based on Three-stage Data Envelopment Analysis

摘要:

运用三阶段数据包络分析（DEA）的BCC模型对中国2017年30个省份众创空间的创新效率进行测算，结果表明中国众创空间的整体创新效率较低、区域创新能力差异大、综合创新效率低；在环境和随机扰动因素的影响下规模效率对众创空间整体创孵能力的评估值虚高；此外，通过投影分析探究出，造成我国部分地区众创空间非DEA有效的主要原因是存在较大程度的投入冗余问题。基于此，为了进一步提升中国众创空间资源利用效率及创新效率，本文认为对于众创空间的管理要做到以下四点：①“精耕”现有众创空间平台，优化资源配置效率；②构建省域群创孵网络，加强城市群之间的创孵合作及资源流动；③打造全球创孵集聚地，利用规模效应带动创新发展；④提高区域开放程度，依靠国际化来带动区域创新效率提升。

Abstract:

This paper uses the BCC model of the three-stage Data Envelopment Analysis method (DEA-BCC) to calculate the innovation efficiency of makerspace in 30 provinces, autonomous regions and municipalities directly under the Central Government of China in 2017. The results show that the overall innovation efficiency of makerspace in China are low, the regional innovation ability is different, and the comprehensive innovation efficiency is low, and under the influence of environment and random disturbance factors, the evaluation value of scale efficiency on the overall incubation capacity of makerspace is falsely high. Moreover, it is found that the main reason for the DEA non-effective makerspace in some regions is the existence of a large degree of investment redundancy by projection analysis, and some suggestions are put forward to further improve the resource utilization efficiency and innovation efficiency of makerspace in China. First, we should intensive cultivation the existing makerspace and optimize the efficiency of resource allocation. Second, we need to build a provincial-level incubation network to strengthen innovation, incubation cooperation and resource flow between urban agglomerations. Then, we need to create a global innovation incubation center and use the scale effect to drive innovation and development. Finally, we need to increase the degree of regional openness and then we can to promote regional innovation efficiency through internationalization.