摘要
基于资源基础理论构建研究框架,以2019—2021年我国30个重点城市的面板数据为研究样本,运用动态QCA方法对影响数字政府建设绩效的资源要素及其组态路径、动态变化过程进行探究。研究发现,单一资源要素在不同时期均非提高数字政府建设绩效的必要条件,能够提高数字政府建设绩效的资源组态路径有三类,即“综合资源联动型”“响应能力驱动型”和“创新能力主导型”,数字政府建设绩效的驱动机制正逐步由“综合资源联动型”和“响应能力驱动型”向“创新能力主导型”转变,这表明创新性资源要素协同配置下的创新能力优势在数字政府建设中日益凸显。鉴于此,应动态把握资源要素间的耦合联系,因地制宜,因时而变,动态选择资源组合路径,驱动数字政府建设长效推进。
Based on the resource-based theory,a re-search framework is constructed,utilizing panel data from 30 key cities in China spanning from 2019 to 2021 as the research samples.The dynamic Qualitative Comparative Analysis(QCA)method is employed to delve into the configuration path and dy-namic evolution of the impact of local resource elements on digit-al government construction performance.The findings reveal that a single resource element is not a necessary condition for achie-ving high digital government construction performance across dif-ferent time periods.The resource configurations that yield high digital government construction performance can be categorized into three types:"comprehensive resource linkage,""response capability-driven,"and"innovation capability-led."Fur-thermore,the driving mechanism behind the performance of local digital government construction is transitioning from"compre-hensive resource linkage"and"response capability-driven"to"innovation capability-led,"highlighting the growing signifi-cance of innovation capabilities fostered by the coordinated allo-cation of innovative resource elements in digital government con-struction.In view of this,it is imperative to dynamically grasp the coupling relationships among resource elements,adapt to lo-cal conditions and temporal changes,and strategically select re-source combination paths to facilitate the sustainable advance-ment of digital government construction.
作者
陈弘
孙一辰
熊春林
CHEN Hong;SUN Yi-chen;XIONG Chun-lin
出处
《城市问题》
CSSCI
北大核心
2024年第8期15-26,51,共13页
Urban Problems
基金
国家社会科学基金后期资助项目(21FGLB089)——“农村公共产品供给质量研究”
湖南省社会科学基金“学术湖南”精品培育项目(23ZDAJ010)——“大数据时代提升乡村基层治理效能的机制创新研究”。
关键词
资源组合
数字政府建设绩效
重点城市
动态QCA
面板数据
resource combination
performance of dig-ital government construction
key cities
Dynamic QCA
panel data
