集群是创新系统与企业之间的中观层面。集群机制促进了技术、人才和知识资源的聚集、企业之间的技术溢出和研发合作，进而起到了提高创新效率的作用，然而，不同区域聚集的集群显示出创新效率的差异，以及基于差异的集群创新能力提升的不同路径。从集群的视角出发，以我国各省创新型集群数据为基础，首先使用DEA-Malmquist法计算各省份集群的创新效率，并根据创新效率的情况将集群分为全面型、技术进步型、技术薄弱型、规模经济型4类集群，再使用模糊集定性比较分析法识别出不同情形下影响创新效率的7条路径，根据路径的特点将其总结为全面性、环境型、聚集型，得到不同类型的集群的创新提升路径，得到的研究结果对于丰富集群创新战略和管理理论与实践具有一定意义。

Industrial clusters clustered in different regions show differences in innovation efficiency and innovation capabilities, and different clusters should correspond to different innovation efficiency improvement paths. Based on the data of my country's innovative industrial clusters, first use the data envelopment analysis (DEA)-Malmquist index method to calculate the innovation efficiency of clusters, which can be divided into comprehensive, technologically advanced, technologically weak, and economies of scale. And then use fuzzy set qualitative comparative analysis (fsqca) to identify 7 paths that affect the innovation efficiency of clusters in different situations, and divide them into comprehensive, environmental, and aggregation types, and obtain the innovation improvement paths of different types of clusters. The results show that: (1) The innovative industrial clusters in Beijing are the only ones that are comprehensive, the innovative industrial clusters in Fujian, Guizhou, Chongqing, and Hubei are technologically advanced, and the innovative industrial clusters in Inner Mongolia, Jilin, and Yunnan are technologically weak. The innovative industrial clusters in Jiangsu, Zhejiang, Sichuan, and Tianjin belong to economies of scale; (2) The comprehensive path is suitable for comprehensive and technologically advanced clusters, the technologically weak clusters are suitable for environmental paths, and the aggregation path is suitable for technological progress and economies of scale cluster, but the same type of industrial cluster can correspond to different paths in different regions to achieve the effect of improving innovation efficiency; (3) The number of clusters, the number of industrial alliances and the number of invention patents granted in the year are the main indicators that affect the innovation efficiency of innovative industrial clusters .

F127；F273.1

浙江省软科学研究计划重点项目“企业技术创新数字化转型-基于互联网开放式创新平台的实证研究”,项目号(2021C25029)