Policy Coherence Between Central and Local Governments in Supporting SMEs and Its Impact on Regional Growth

Jione Park & Taewon Kang

International Regional Science Review2025https://doi.org/10.1177/01600176251377407article
ABDC B
Weight
0.50

Abstract

Innovation policies have recently shifted toward fostering ecosystems that leverage each region’s unique strengths and resources. While supporting regional industries—particularly small and medium-sized enterprises (SMEs)—is essential, it remains complex due to their limited scale and the characteristics of local innovation systems. Addressing these challenges requires coordinated efforts between central and local governments within a multi-level governance framework. This study examines the coherence of central and local government policies (policy coherence) on SMEs' technological innovation and its impact on regional economic development. To assess the degree of coherence, we use cosine similarity to compare keywords from central government policy documents and local SME support programs in Korea. We then perform a regression analysis to evaluate its effect on regional growth. Our finding indicates that greater policy coherence between central and local governments positively contributes to regional growth, emphasizing their complementary roles in supporting SMEs. This suggests that the importance of strengthening policy coherence to create a more supportive environment for SMEs and promote sustainable regional economic development.

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https://doi.org/https://doi.org/10.1177/01600176251377407

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@article{jione2025,
  title        = {{Policy Coherence Between Central and Local Governments in Supporting SMEs and Its Impact on Regional Growth}},
  author       = {Jione Park & Taewon Kang},
  journal      = {International Regional Science Review},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/01600176251377407},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.