Dual-Policy Coverage and Corporate Green Innovation: Evidence from China’s Commercial Logistics Node City Program and Supply Chain Innovation and Application Pilot Program
Logistics network development and supply chain organizational innovation may create external conditions for corporate green innovation. Using 30,700 firm-year observations for Chinese A-share listed companies from 2012 to 2024, this study examines the relationship between joint coverage by the Commercial Logistics Node City Program and the Supply Chain Innovation and Application Pilot Program and corporate green innovation. Double machine learning is employed to account flexibly for nonlinear relationships between policy coverage, firm characteristics, and green innovation. Dual-policy coverage is positively and significantly associated with green invention patent applications, with a baseline coefficient of 0.1131. The result remains positive under alternative cross-fitting folds, machine learning algorithms, sample restrictions, and measures of green innovation. Channel analyses indicate that dual-policy coverage is associated with greater supply chain digitalization, lower supply chain risk, and higher innovation efficiency. The estimated association is stronger among firms with higher R&D intensity and weaker among firms facing greater environmental uncertainty. These findings provide firm-level evidence that logistics connectivity and supply chain organizational conditions are relevant to corporate green innovation and offer policy implications for sustainable industrial development.
Authors
- Wei Luo (ORCID: https://orcid.org/0000-0003-0043-0687)
- Hengwu Li
- Jinli Du
Institutions
- Guilin University of Aerospace Technology (CN)
- Guilin University of Technology (CN)
- Guilin University of Electronic Technology (CN)
Publication Details
- Journal
- Sustainability
- Published
- 2026-10-14
- DOI
- https://doi.org/10.3390/su182010461
- Primary Topic
- Environmental Sustainability in Business
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China