Innovation ecosystem and corruption: evidence from the global innovation index
Yazarlar (3)
Mehmet Ali Koseoglu
Metropolitan State University, Amerika Birleşik Devletleri
Metropolitan State University, Amerika Birleşik Devletleri
Doç. Dr. Hasan Evrim ARICI Kastamonu Üniversitesi, Türkiye
Doç. Dr. Mehmet Altin Rosen College of Hospitality Management, Amerika Birleşik Devletleri
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Management Decision (Q1) | ||
| Dergi ISSN | 0025-1747 Dergi Bilgileri (2026) | ||
| Dergi Tarandığı Indeksler | SSCI | ||
| Makale Dili | Türkçe | Basım Tarihi | 01-2026 |
| Kabul Tarihi | – | Yayınlanma Tarihi | 26-02-2026 |
| Cilt / Sayı / Sayfa | – / 1 / 1–22 | DOI | 10.1108/MD-10-2024-2279 |
| Makale Linki | https://www.emerald.com/md/article/doi/10.1108/MD-10-2024-2279/1343722/Innovation-ecosystem-and-corruption-evidence-from | ||
| UAK Araştırma Alanları |
Otel İşletmeciliği
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| Özet |
| Purpose This study investigates the complex relationship between a country's national innovation system and levels of corruption, focusing on both corruption control (CC) and corruption perception. Design/methodology/approach Using Global Innovation Index data (2013–2022) and machine learning algorithms (random forest, partial dependence plots), the study evaluates the role of innovation-related factors. Findings Political stability and regulatory quality are the strongest predictors of CC and perception. R&D investments are particularly important in upper-middle-income countries, while infrastructure plays a key role in low-income countries. Practical implications Policymakers should foster balanced innovation systems, strengthen governance, and adapt anti-corruption strategies to national income levels. Originality … |
| Anahtar Kelimeler |
| "National innovation system" | "Corruption control" | "Corruption perception" | "Global innovation index" | "Machine learning algorithms" |
BM Sürdürülebilir Kalkınma Amaçları
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| Google Scholar | 1 |