长江中游城市群城市创新效率的时空格局及其驱动因素

创新效率是城市创新竞争力的核心要素。基于DEA和Malmquist指数模型对长江中游城市群2006～2016年城市创新效率的时空演化规律进行实证分析,并借助GMM估计方法揭示其驱动因子作用的空间异质性。结果发现:(1)创新综合技术效率上,创新效率由2006年的0.731增长至2016年的0.807,以2011年为拐点,呈现平稳发展期和波动变化期两段式特征。"东弱西强"梯度分异格局显著,二元格局差异逐渐弱化;(2)城市创新活动的全要素生产率上,Malmquist指数由2006年的6.2%提高至2016年的18.4%,增长态势相对稳健。空间分异总体上不明显,具有"发散-收敛-发散"的三段式演化特征;(3)GMM回归结果显示,驱动因子对长江中游城市群整体和三大次级城市群作用存在空间异质性,信息化进程、经济基础、外商活跃度有助于激励城市创新效率提升,金融规模阻滞作用显著,而第三产业规模、创新平台、政府支持力度则异质性作用明显。

Study on Spatial-Temporal Pattern and Driving Factors of Urban Innovation Efficiency of Urban Agglomeration in the Middle Reaches of Yangtze River

Innovation efficiency is the core element of urban innovation competitiveness. This paper constructs the assessment system of innovation efficiency based on input-output perspective and measures the innovation efficiency by DEA and Malmquist index models. Then the spatial and temporal evolution of innovation efficiency of the urban agglomerations in the middle reaches of the Yangtze River from 2006 to 2016 is analyzed. The GMM estimation is used to discover the spatial heterogeneity of the driving factors. The results show that: (1) In terms of the comprehensive technology efficiency of innovation, on one hand the innovation efficiency temporally increased from 0.731 in 2006 to 0.807 in 2016 with 2011 as the turning point, which shows the two-stage characteristics of stable development and fluctuation period. On the other hand, the gradient differentiation pattern of “ Weak East and Strong West” is significant spatially. However, the dual spatial pattern is gradually weakened since the innovation efficiency has been descending from the west to the east. (2) In terms of productivity of urban innovation activities, the Malmquist index increased from 6.2% in 2006 to 18.4% in 2016 indicates that the growth trend is relatively stable, while the generally unobvious spatial differentiation indicates the three-stage evolutionary characteristics of “divergence-convergence-divergence”. (3) GMM regression results show that the driving factors have different spatial effects on both of the whole urban agglomeration and the three sub-urban groups in the middle reaches of Yangtze River. The informationization process, the economic foundation, and the foreign business activity positively help to inspire urban innovation efficiency; the financial scale has a significantly negative effect; the tertiary industry scale, innovation platform of university and government support have heterogenous effects obviously. This study has the contribution to improve the regional innovation environment for the local governments.