产业集聚视域下多要素驱动区域创新发展的组态效应分析——以成渝地区双城经济圈为例
The Grouping Effect of Multifactor-Driven Regional Innovation Development Under the Perspective of Industrial Agglomeration:Taking Chengdu-Chongqing Economic Circle as an Example
魏奇锋 1郭安妮 2盛毅3
作者信息
- 1. 四川省社会科学院产业经济研究所,成都 610071;西南财经大学中国西部经济研究院,成都 611130;成都理工大学商学院,成都 610059
- 2. 成都理工大学商学院,成都 610059
- 3. 四川省社会科学院产业经济研究所,成都 610071
- 折叠
摘要
基于知识密集型服务业及专利等相关数据,利用fsQCA方法,分析多要素驱动区域创新发展多重并发路径.结果显示:(1)在全域视角下,成渝地区双城经济圈知识密集型服务业发展不均衡,各城市知识密集型服务业集聚度具有显著梯度特征;(2)在行业视角中,行业集聚效应地区异质性显著,产业集聚"两极分化"特征显著,具有"强者越强,弱者越弱"集聚趋势;(3)组态分析发现,区域创新发展条件间存在多重并发关系,进一步总结出两条创新发展模式:以对外开放为核心的创新发展模式和以要素集聚为核心的创新发展模式.最后,从产业集聚、创新投入、开放合作等3个角度提出促进区域创新发展的对策建议.
Abstract
Based on the data related to knowledge-intensive service industries(KIBS)and patent grants,the fsQCA meth-od is used to analyze the multiple concurrent paths of regional innovation development driven by multi-factors.The results show that:(1)From the overall situation,there is an imbalanced situation of KIBS agglomeration in Chengdu-Chongqing Economic Circle,the KIBS agglomeration of the 16 cities shows obvious gradient characteristics;(2)From industry hetero-geneity,the industry agglomeration effect shows obvious regional heterogeneity,with the industry agglomeration shows"the stronger the stronger,the weaker the weaker"agglomeration trend;(3)From empirical analysis result,regional innovation conditions have multiple concurrent relationships,combined with the results of the group,summed up two innovation mod-els:to innovation development mode centered on opening to the outside world and clustering factors.Finally,suggestions for regional innovation development are put forward from industrial agglomeration,innovation investment,and openness and co-operation perspectives.
关键词
知识密集型服务业/产业集聚/区域创新/模糊集定性比较分析Key words
KIBS/industrial agglomeration/regional innovation/fsQCA引用本文复制引用
基金项目
教育部人文社会科学规划项目(21YJC790122)
中国博士后科学基金资助面上项目(2022MD713778)
成都市社会科学规划"研究阐释习近平总书记来川视察重要指示精神"专项重点项目(2023A16)
四川省川酒发展研究中心重点项目(CJZ22-03)
成都理工大学"双一流"建设哲学社会科学重点建设项目(ZDJS202305)
出版年
2024
NETL
NSTL
万方数据