Does Industry–University–Research System Coordination Really Mediate Fiscal S&T Investment? A Differentiated Examination of Regional Innovation Systems

This study examines how fiscal science and technology (S&T) investment is associated with regional innovation performance through industry-university-research (IUR) system coordination, a critical issue for optimizing S&T resource allocation and advancing high-quality regional economic development. Based on 2010–2020 panel data covering 28 Chinese provincial regions, we adopt the entropy weight method to construct a composite index of regional innovation performance covering knowledge and economic outputs. Taking IUR system coordination as the mediating variable and controlling for a full set of regional characteristics, we unpack the dynamic correlation and transmission mechanism linking fiscal S&T investment and regional innovation outcomes. The results show that fiscal S&T investment is positively associated with regional innovation performance, with both basic and applied research investment exhibiting positive associations. However, mediation analyses reveal that the indirect effects through IUR system coordination lack sufficient statistical support in both pathways. These findings suggest that the positive association between fiscal S&T investment and regional innovation performance is not transmitted through the indirect channel of IUR system coordination. The results also reveal cross-regional innovation gaps and provide targeted policy references for optimizing fiscal S&T investment structure and improving investment efficiency.

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Publication Details

Journal
Systems
Published
2026-10-09
DOI
https://doi.org/10.3390/systems14101272
Primary Topic
University-Industry-Government Innovation Models
Type
article
Field-Weighted Citation Impact
0.00
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Does Industry–University–Research System Coordination Really Mediate Fiscal S&T Investment? A Differentiated Examination of Regional Innovation Systems

Chenhui Liu, TianYi Zhang, Dianni Wang, Fan Li et al.
Systems
University-Industry-Government Innovation Models
article

Does Industry–University–Research System Coordination Really Mediate Fiscal S&T Investment? A Differentiated Examination of Regional Innovation Systems

Chenhui Liu, TianYi Zhang, Dianni Wang, Fan Li, Ching‐Hung Lee
article en

Abstract

This study examines how fiscal science and technology (S&T) investment is associated with regional innovation performance through industry-university-research (IUR) system coordination, a critical issue for optimizing S&T resource allocation and advancing high-quality regional economic development. Based on 2010–2020 panel data covering 28 Chinese provincial regions, we adopt the entropy weight method to construct a composite index of regional innovation performance covering knowledge and economic outputs. Taking IUR system coordination as the mediating variable and controlling for a full set of regional characteristics, we unpack the dynamic correlation and transmission mechanism linking fiscal S&T investment and regional innovation outcomes. The results show that fiscal S&T investment is positively associated with regional innovation performance, with both basic and applied research investment exhibiting positive associations. However, mediation analyses reveal that the indirect effects through IUR system coordination lack sufficient statistical support in both pathways. These findings suggest that the positive association between fiscal S&T investment and regional innovation performance is not transmitted through the indirect channel of IUR system coordination. The results also reveal cross-regional innovation gaps and provide targeted policy references for optimizing fiscal S&T investment structure and improving investment efficiency.

SystemsVol. 14(10)
Hong Kong Polytechnic University (HK), Xi'an Jiaotong University (CN)
Openalex Percentile: Top 8%
University-Industry-Government Innovation Models
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Does Industry–University–Research System Coordination Really Mediate Fiscal S&T Investment? A Differentiated Examination of Regional Innovation Systems — Chenhui Liu, TianYi Zhang, et al. · Systems (2026) | TGRS Research Map | TGRS