Public Funding of Cluster Initiatives in Russian Regions
The Role of Reputation
Bibliographic Data
| ID | 21218748 |
|---|---|
| Authors | Evgeniy Kutsenko (0000-0002-0335-1944, National Research University Higher School of Economics, corresponding author), E Ivanova (0000-0003-2972-3379, National Research University Higher School of Economics, corresponding author), Valeriya Vlasova (0000-0002-9079-0979, National Research University Higher School of Economics, corresponding author) |
| Year | 2025 |
| Volume | 15 |
| Issue | 3 |
| Pages | 344-359 |
| Publication date | 2025-09-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Regional Research of Russia (JOURNAL) |
| Journal identifiers | ISSN: 2079-9713 • E-ISSN: 2079-9705 |
| Publisher | Pleiades Publishing Ltd (PUBLISHER) |
| DOI | 10.1134/s207997052560060x |
| OpenAlex | W4416739288 |
| Language | EN |
| References cited | 40 |
The paper seeks to understand, which factors: innovative development of cluster home regions, economic performance of cluster members, management and governance excellence of cluster teams, or their ability to gain trustworthy reputation from national-level policymakers—influence clusters’ selection for public funding, and the volumes of subsidy allocated. The research is based on the case of 20 Russian pilot innovative clusters—PICs. The Heckman correction was used for the hypotheses testing. The results imply that reputation was the most influential factor for clusters’ selection and the subsidy volumes they got. The paper’s academic novelty is in separating the objective characteristics of clusters from the subjective reputational issues, both regarded from the public funding perspective. Policy implications suggest formalizing the clusters’ collective reputation and increasing the integrity of the selection procedures for public subsidizing
Corporate governance · Excellence · Reputation · Subsidy · Cultural Industries and Urban Development · Regional Economic Development and Innovation · University-Industry-Government Innovation Models
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| Highly cited | No |
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