Optimization Study of Regional Digital Innovation Capability Driven by the Synergy of Information Ecology and Digital Transformation: Dynamic QCA Analysis Based on Provincial Panel Data

Digital transformation is gradually emerging as a core driver of high-quality economic development and the achievement of sustainable development goals. As the core engine of the digitalization process, digital innovation is becoming a key supporting force for activating the value of digital elements and fostering a new development pattern. Based on panel data from 31 provincial-level administrative regions in China spanning from 2019 to 2023, we undertook an in-depth exploration of how information ecosystems and digital transformation drivers synergistically enhance regional digital innovation capabilities and their substitutive relationships. The results show the following: Firstly, technological, subject, information, and environmental conditions cannot individually constitute the necessary conditions for a high level of regional digital innovation capacity. Secondly, three types of conditional configurations, namely technology–environment-driven, subject–environment-driven, and balance-driven, are its main driving paths, with significant substitution effects among these conditions. This study provides theoretical and empirical evidence for formulating region-specific strategies to optimize digital innovation capacity and helps formulate differentiated digital development strategies based on regional resource endowments and institutional characteristics, ultimately promoting the construction of a more balanced and resilient digital innovation ecosystem.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2025-08-20
DOI
https://doi.org/10.3390/su17167534
Primary Topic
Environmental Quality and Pollution
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimization Study of Regional Digital Innovation Capability Driven by the Synergy of Information Ecology and Digital Transformation: Dynamic QCA Analysis Based on Provincial Panel Data

Shuhong Guo, Lei Lei, Bo Qi
Sustainability
Environmental Quality and Pollution
article

Optimization Study of Regional Digital Innovation Capability Driven by the Synergy of Information Ecology and Digital Transformation: Dynamic QCA Analysis Based on Provincial Panel Data

Shuhong Guo, Lei Lei, Bo Qi
article en

Abstract

Digital transformation is gradually emerging as a core driver of high-quality economic development and the achievement of sustainable development goals. As the core engine of the digitalization process, digital innovation is becoming a key supporting force for activating the value of digital elements and fostering a new development pattern. Based on panel data from 31 provincial-level administrative regions in China spanning from 2019 to 2023, we undertook an in-depth exploration of how information ecosystems and digital transformation drivers synergistically enhance regional digital innovation capabilities and their substitutive relationships. The results show the following: Firstly, technological, subject, information, and environmental conditions cannot individually constitute the necessary conditions for a high level of regional digital innovation capacity. Secondly, three types of conditional configurations, namely technology–environment-driven, subject–environment-driven, and balance-driven, are its main driving paths, with significant substitution effects among these conditions. This study provides theoretical and empirical evidence for formulating region-specific strategies to optimize digital innovation capacity and helps formulate differentiated digital development strategies based on regional resource endowments and institutional characteristics, ultimately promoting the construction of a more balanced and resilient digital innovation ecosystem.

SustainabilityVol. 17(16)
Harbin Normal University (CN), Harbin Institute of Technology (CN)
Jilin Office of Philosophy and Social Science, Harbin Normal University
Openalex Percentile: Top 79%
Environmental Quality and Pollution
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.