Internal logic of digital innovation ecosystem development

China is undergoing a pivotal transition from “basically accomplished industrialization” to “advanced new-type industrialization,” where digital technologies accelerate the integration with the manufacturing system, spanning the total factors, the entire industrial chain (from low-end to high-end), and diversified context (from enterprises to industries to cross-sector integration). Establishing a self-organizing, self-adapting and evolvable digital innovation ecosystem will provide sustainable power for this new industrialization paradigm. To address this research question concerning the intrinsic dynamics of digital innovation ecosystem evolution, we adopt a “Technology-Data-Context (TDC)” framework to systematically examine the developmental trajectory of manufacturing digital innovation ecosystems and find their evolutionary paths. The principal findings of this paper are as follows: First, it examines the dynamic interplay of technology, data, and context across different evolutionary stages of digital innovation ecosystems from an endogenous perspective. Second, it analyzes the multidimensional value space constituting these innovation ecosystems. Third, it establishes a TDC-I (Technology-Data-Context-Innovation) framework as the foundational logic for understanding the micro-level dynamics, where reciprocal interactions among technological innovation, data-driven innovation, and contextual innovation propel the ecosystem’s formation and spiral evolution. This study makes marginal contributions to both digital innovation ecosystem theory and industrial digitalization research, while providing practical insights to enhance industrial digital transformation and informing policymaking for optimizing value co-creation in digital innovation ecosystem.

Publication Details

Journal
Zhongguo ruankexue
Published
2025-09-01
DOI
https://doi.org/10.3724/1005-0566.20250917
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Internal logic of digital innovation ecosystem development

Zhongguo ruankexue
Digital Transformation in Industry
article

Internal logic of digital innovation ecosystem development

article en

Abstract

China is undergoing a pivotal transition from “basically accomplished industrialization” to “advanced new-type industrialization,” where digital technologies accelerate the integration with the manufacturing system, spanning the total factors, the entire industrial chain (from low-end to high-end), and diversified context (from enterprises to industries to cross-sector integration). Establishing a self-organizing, self-adapting and evolvable digital innovation ecosystem will provide sustainable power for this new industrialization paradigm. To address this research question concerning the intrinsic dynamics of digital innovation ecosystem evolution, we adopt a “Technology-Data-Context (TDC)” framework to systematically examine the developmental trajectory of manufacturing digital innovation ecosystems and find their evolutionary paths. The principal findings of this paper are as follows: First, it examines the dynamic interplay of technology, data, and context across different evolutionary stages of digital innovation ecosystems from an endogenous perspective. Second, it analyzes the multidimensional value space constituting these innovation ecosystems. Third, it establishes a TDC-I (Technology-Data-Context-Innovation) framework as the foundational logic for understanding the micro-level dynamics, where reciprocal interactions among technological innovation, data-driven innovation, and contextual innovation propel the ecosystem’s formation and spiral evolution. This study makes marginal contributions to both digital innovation ecosystem theory and industrial digitalization research, while providing practical insights to enhance industrial digital transformation and informing policymaking for optimizing value co-creation in digital innovation ecosystem.

Zhongguo ruankexueVol. 40(9)
Industry, innovation and infrastructure
Openalex Percentile: Top 35%
Digital Transformation in Industry
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.