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Updated: Jul 15, 2025

Operation of the Collaborative Composite Manufacturing CCM System
Published on: October 1, 2019
Can industrial collaborative agglomeration improve carbon emission efficiency? Empirical evidence from China
Hui Tian1, Jiaqi Qin2, Chaoyin Cheng1
1School of Business, Central South University, Changsha, 410083, China.
Industrial collaborative agglomeration (ICA) initially hinders then helps carbon emission efficiency (CEE). This relationship varies by region and involves industrial upgrading and green innovation, with spatial spillover effects observed.
Area of Science:
- Environmental Economics
- Industrial Economics
- Regional Science
Background:
- Low-carbon development necessitates modernized industrial systems and new development models.
- Industrial collaborative agglomeration (ICA) between manufacturing and producer services is a potential strategy for carbon reduction.
Purpose of the Study:
- To investigate the influence of ICA on carbon emission efficiency (CEE).
- To analyze the heterogeneous effects, impact mechanisms, and spillover effects of ICA on CEE.
Main Methods:
- Utilized balanced panel data from China's 30 provinces and municipalities (2008-2019).
- Employed econometric analysis to examine the relationship between ICA and CEE, including regional heterogeneity and spatial spillover effects.
Main Results:
- A U-shaped relationship exists between ICA and CEE, indicating initial inhibition followed by promotion.
- Regional heterogeneity observed: significant U-shaped in the east, inverted U-shaped in the west, and insignificant in the center.
- Industrial structure upgrading and green technological innovation are key mechanisms driving the ICA-CEE relationship.
- ICA exhibits spatial spillover effects on CEE in neighboring areas, also presenting a U-shaped relationship.
Conclusions:
- ICA's impact on CEE is complex and non-linear, with regional variations.
- Industrial upgrading and green innovation are crucial for leveraging ICA to improve CEE.
- Policymakers should consider regional characteristics and spatial dependencies when formulating industrial and environmental policies.
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