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"New Quality Productive Forces and High-level Science & Technology Self-reliance and self-strengthening" Column

Which Digital Innovation Ecosystem Drives the Development of  New Quality Productive Forces?

—A Dynamic QCA Analysis  Based on Provincial Panel Data 

Hu Zhen 

(School of Humanities and Law, Northeastern University, Shenyang 110169, China)

Abstract: As an advanced productivity form led by innovation, new quality productive  forces serve as the core engine for promoting high-quality development. In the digital economy  era, the digital innovation ecosystem provides critical support for the cultivation and release of  these forces by integrating innovation subjects, resources, and environments. Based on digital in⁃ novation ecosystem theory, this study employs the dynamic QCA method and uses panel data  from 31 provinces in China from 2017 to 2022 as a sample to systematically explore the multiconfiguration paths and spatiotemporal evolution characteristics of digital innovation ecosystem  elements driving the development of new quality productive forces. The research aims to identify  configurations that effectively drive this development and examine whether these paths exhibit  significant temporal and regional effects. The findings indicate that: ①From a temporal dimen⁃ sion, no single digital innovation ecosystem element constitutes a necessary condition for the de⁃ velopment of new quality productive forces, though the necessity of data elements and digital  governance shows an upward trend annually, reflecting a significant temporal effect. From a spa⁃ tial dimension, the eastern region exhibits a high dependence on innovation subjects, resources, and environments; the central region focuses on subjects and resources; and the western region  shows lower dependence, indicating distinct regional effects. ②Five configuration paths gener⁃ ate high-level new quality productive forces, categorized into three modes: "ElementGovernance" empowerment-driven, Subject-led endogenous-driven, and System synergy  symbiotic-driven. Conversely, seven configuration paths lead to low-level development, summa⁃ rized as Environmental ecological absence, Lack of endogenous power, and Structural imbalance  limitation. ③While the configuration paths did not show significant temporal or regional effects  during the sample period, the overall driving mechanism is shifting toward a system synergy  symbiotic-driven mode, indicating that the linkage effect of multiple elements is becoming in⁃ creasingly vital. Theoretically, this study advances the dynamic and empirical expansion of digi⁃ tal innovation ecosystem theory, addresses the call for causality and temporality in configuration  research, and deepens the understanding of context-dependency. Practically, it provides a refer⁃ ence for regions to develop new quality productive forces according to local conditions: first, by  strengthening the core role of data and digital governance; second, by fostering synergy across  multiple elements; and third, by respecting regional differences to develop productivity accord⁃ ing to local contexts. 

Key words: digital innovation ecosystem; new quality productive forces; digital innovation  subjects; digital innovation resources; digital innovation environment; configuration perspective; dynamic QCA; panel data