区域创新能力是深入实施国家创新驱动发展战略的基础要素，识别区域创新能力影响因子、挖掘区域创新能力联动机制是加速提升区域创新能力的关键。运用动态QCA分析方法，构建“数字创新主体—数字创新平台—数字创新生态环境”分析框架，从时空双维视角综合分析2017—2021年我国内地31个省份面板数据，探索驱动区域创新能力提升的组态路径。研究发现：政府、企业、中介机构和数字治理环境在提升区域创新能力中发挥重要核心作用。其中，高水平区域创新能力组态有4条路径，可归纳为“创新主体+创新平台”驱动型、“创新主体+创新平台+创新环境”驱动型、“创新环境”驱动型3种模式；低水平区域创新能力组态路径有8条，可归纳为“创新主体+创新环境”限制型、“创新环境”限制型、“创新主体+创新平台”限制型3种模式；在时间维度上，4条高水平组态路径均在2020年呈现一致性下降趋势；在空间维度上，区域创新能力呈现出明显的东西部发展不平衡现象。

Regional innovation capability is a fundamental element for the in-depth implementation of the national innovation-driven development strategy. Identifying the influencing elements of regional innovation capability and discovering the linkage mechanism of regional innovation capability is the key to accelerating the enhancement of regional innovation capability. With the extensive and in-depth promotion of digital technology, digital technology and regional innovation present a high degree of coupling. However, the current research on digital innovation ecosystems is still in the development stage, especially on the relationship between the coupling of digital innovation ecosystem elements and regional innovation capacity there are still some research gaps. Therefore, it is necessary to further explore the connection between the two. Are there any necessary conditions between cause and effect? Are there any combinations of "different cause and effect" ? What is the impact of these combinations on the enhancement of regional innovation capability? Are there any laws of time and space? This will further open the "black box" of the operating mechanism of digital innovation ecosystem elements and regional innovation capabilities.#br#Most of the existing studies have only focused on the "net benefit" of a single element of the innovation ecosystem on regional innovation capabilities, ignoring the impact of the linkage combination of elements. Although the traditional QCA analysis method has improved the problem of multi-factor linkage combination, it is limited by the static and unsaturated theoretical construction. Most of the multi-factor linkage analysis uses static cross-sectional data. The problem of "time blind zone" cannot effectively examine the influence of time and space on the linkage combination of multiple factors. Thus, this study takes the regional innovation of 31 provinces as the research objects, uses the dynamic QCA analysis method to build the analysis framework of "digital innovation subject-digital innovation platform-digital innovation ecological environment"; it further analyzes the provincial panel data of 31 provinces and cities from 2017 to 2021 from the two-dimensional perspective of time and space, and explores the configuration path to drive regional innovation capabilities.#br#The research finds that the government, enterprises, intermediaries and digital governance environment play vital roles in enhancing regional innovation capabilities. The necessity of the variables including "digital governance environment" and "digital financial inclusion environment" exhibits a clear time effect. There are four paths for the configuration of high-level regional innovation capabilities, which can be summarized into three modes: "innovation subject + innovation platform" driven mode, "innovation subject + innovation platform + innovation environment" driven mode, and "innovation environment" driven mode. There are eight paths in the configuration of low-level regional innovation capabilities, which can be summarized into three modes: "innovation subject + innovation environment" restriction mode, "innovation environment" restriction mode, and "innovation subject + innovation platform" restriction mode. In the time dimension, the four configurations at high levels all showed a consistent downward trend in 2020. In the spatial dimension, the level of regional innovation capabilities presents an obvious unbalanced development between the east and the west. It is suggested that localities should choose appropriate digital innovation ecosystems according to their local conditions to cultivate new regional innovation power and promote the new development of digital China.#br#This study applies the dynamic QCA research method to examine the factors influencing regional innovation capability, analyzes the relationship between digital innovation ecosystem elements and regional innovation capability, makes up for the time blind zone in previous QCA research, and explores typical cases of multiple combinations of paths from the spatial and temporal dimensions, providing theoretical references and inspirations for the development of regional innovation capacity. It also discusses typical cases of multiple combinations of paths from both spatial and temporal dimensions, which provides theoretical reference and enlightenment for the development of regional innovation capability. Future research on regional innovation capability can be explored from key cities and high-tech industries, and makes empirical analysis of the technological innovation process of national key facilities.#br#