TY - JOUR
T1 - The regional environmental benefits and heterogeneity of eco-innovation networks
T2 - Evidence from the Yangtze River Economic Belt in China
AU - Yang, Yang
AU - Guo, Yi
AU - Hu, Senlin
AU - Li, Erling
AU - Zhao, Wei
AU - Zeng, Gang
N1 - Publisher Copyright:
© 2025 The Authors.
PY - 2026/1
Y1 - 2026/1
N2 - Constructing Eco-Innovation networks is an effective way to improve innovation capabilities and drive high-quality development. It constructs an indicator system for measuring the environmental benefits of cities at the prefecture level. We quantitatively measure the environmental benefits of cities using the super-efficiency SBM model. Using the PVAR model, we explore the long-term dynamic relationship between eco-Innovation networks and urban environmental benefits. The analysis finds that: ①For core node cities in the eco-Innovation networks, the network has a positive impact on their environmental benefits, but this effect is irregular in the long term. The positive effect of environmental benefits from core node cities on the eco-Innovation networks is weak, smaller than the impact of the networks on the environmental benefits of core node cities. ②For sub-core node cities in the eco-Innovation networks, the network has a strong and sustained positive impact on their environmental benefits, and this impact deepens over time. However, the environmental benefits of sub-core node cities have a short-term negative impact on the eco-Innovation networks. ③For peripheral node cities in the eco-Innovation networks, there is a small mutual promotion between the networks and the environmental benefits of peripheral cities, with both maintaining stability and having minimal mutual influence.
AB - Constructing Eco-Innovation networks is an effective way to improve innovation capabilities and drive high-quality development. It constructs an indicator system for measuring the environmental benefits of cities at the prefecture level. We quantitatively measure the environmental benefits of cities using the super-efficiency SBM model. Using the PVAR model, we explore the long-term dynamic relationship between eco-Innovation networks and urban environmental benefits. The analysis finds that: ①For core node cities in the eco-Innovation networks, the network has a positive impact on their environmental benefits, but this effect is irregular in the long term. The positive effect of environmental benefits from core node cities on the eco-Innovation networks is weak, smaller than the impact of the networks on the environmental benefits of core node cities. ②For sub-core node cities in the eco-Innovation networks, the network has a strong and sustained positive impact on their environmental benefits, and this impact deepens over time. However, the environmental benefits of sub-core node cities have a short-term negative impact on the eco-Innovation networks. ③For peripheral node cities in the eco-Innovation networks, there is a small mutual promotion between the networks and the environmental benefits of peripheral cities, with both maintaining stability and having minimal mutual influence.
KW - Eco-innovation networks
KW - Environmental benefits
KW - Yangtze river economic belt
UR - https://www.scopus.com/pages/publications/105044320366
U2 - 10.1016/j.apgeog.2025.103851
DO - 10.1016/j.apgeog.2025.103851
M3 - 文章
AN - SCOPUS:105044320366
SN - 0143-6228
VL - 186
JO - Applied Geography
JF - Applied Geography
M1 - 103851
ER -