Analyzing the Correlation Between the Growth of University Science and Technology Innovation Parks (USTIPs) and Regional Economic Development in Yangtze River Delta, China
The rapid growth of University Science and Technology Innovation Parks (USTIPs) have recently been vital to China’s innovation-driven development. However, contributions to regional economic growth remains understudied. The Yangtze River Delta (YRD), given its economic foundation, concentration of higher institutions, and innovation policy emphasis, provides an ideal context for such study. This paper examines the relationship between USTIPs and regional economic development in the YRD. A multivariate regression analysis across 41 cities revealed that a 1% increase in USTIP quantity corresponds to a 0.122% rise in GDP, a 0.096% increase in high-tech industrial output, and a 0.087% improvement in land use efficiency. These effects are weaker than those of other Science and Technology Innovation Parks (STIPs), which contribute a 0.595% GDP increase, 0.106% growth in high-tech output, and 0.289% improvement in land use efficiency. A comparative analysis further showed that 12 USTIPs employ 21,325 staff with a registered capital of USD 2.12 billion, substantially lower than 123 STIPs that employed 226,055 staff with USD 24.09 billion capital. Despite these limitations, USTIPs are established as long-term drivers of innovation ecosystems and regional competitiveness. These findings serve as empirical evidence linking USTIPs to economic growth, providing valuable insights for optimizing regional innovation policies.
Authors
- Yue Wu (ORCID: https://orcid.org/0000-0001-7296-8182)
- Auwalu Faisal Koko (ORCID: https://orcid.org/0000-0003-2425-9941)
- Zexu Han
- Siyuan Zhang (ORCID: https://orcid.org/0000-0002-1307-2869)
Institutions
- Zhejiang International Studies University (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- Systems
- Published
- 2025-12-08
- DOI
- https://doi.org/10.3390/systems13121105
- Citations
- 1
- Primary Topic
- University-Industry-Government Innovation Models
- Type
- article
- Field-Weighted Citation Impact
- 2.76