Interlocal learning mechanisms and policy diffusion: The case of new energy vehicles finance in Chinese cities
Abstract Policy diffusion based on learning mechanisms has fascinated political science and public administration scholars for a long time. A robust and growing body of studies have identified the existence and importance of learning mechanisms in policy diffusion. However, there are still some gaps that need to be further improved. First, scholars identify the learning mechanism mainly based on indirect evidence, such as geographical proximity and successful innovation policies adopted by other jurisdictions, which lacking direct and systematic evidence. Second, little is known about how the hierarchical power structure affects the leap from learning behavior to policy adoption. This study provides direct evidence for the promoting effect of intergovernmental learning on policy diffusion by analyzing case of Chinese local financial subsidy policies for new energy vehicles. The empirical results reveal that policy learning in the form of site visits among local governments significantly promotes the policy diffusion, but superior government policy strategy attenuates the influence of interlocal learning on policy diffusion. Also, the initiators and themes of policy learning affect the learning–diffusion linkage, portraying the conditional effects and nuanced dynamics of interlocal policy learning in eliciting policy diffusion.
Authors
- Hongtao Yi (ORCID: https://orcid.org/0000-0002-6753-4627)
- Liang Ma (ORCID: https://orcid.org/0000-0002-8779-5891)
- Xuan Wang (ORCID: https://orcid.org/0000-0002-0830-0898)
- Weixing Liu (ORCID: https://orcid.org/0000-0002-6294-5873)
Institutions
- Florida State University (US)
- University of International Business and Economics (CN)
- Peking University (CN)
- Beijing Municipal Government (CN)
- Renmin University of China (CN)
Publication Details
- Journal
- Policy Studies Journal
- Published
- 2024-11-19
- DOI
- https://doi.org/10.1111/psj.12576
- Citations
- 11
- Primary Topic
- Policy Transfer and Learning
- Type
- article
- Field-Weighted Citation Impact
- 24.54
Funders
- National Natural Science Foundation of China
- Fundamental Research Funds for the Central Universities
- National Social Science Fund of China