Spatially differentiated drivers of regional innovation
Evidence from Turkish provinces
Bibliographic Data
| ID | 21679883 |
|---|---|
| Authors | Sıla Ceren Varış Husar (0000-0001-9302-0956, Slovak University of Technology in Bratislava), Ö Burcu Özdemir Sarı (0000-0002-3745-1740, ORTA DOĞU TEKNİK ÜNİVERSİTESİ, MİMARLIK FAKÜLTESİ) |
| Year | 2026 |
| Issue | 51 |
| Publication date | 2026-04-18 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | İDEALKENT (JOURNAL) |
| Journal identifiers | ISSN: 1307-9905 • E-ISSN: 2602-2133 |
| Publisher | IDEALKENT (PUBLISHER) |
| DOI | 10.31198/idealkent.1852450 |
| OpenAlex | W7154844682 |
| Language | EN |
| References cited | 33 |
This research examined the spatial structure of regional innovation in Türkiye. The dominant use of uniform policy instruments in innovation policies has raised concerns about the insufficient consideration of regional differences. In this context, the research aimed to analyze whether the determinants of innovation generated spatially differentiated effects across Turkish provinces. At the provincial level (NUTS 3), patent and utility model registrations from 2019 were employed as indicators of innovation output. Factors influencing innovation were analyzed through variables representing R&D and new enterprises in innovative sectors, institutional presence and local economic structure. The empirical analysis first applied global regression models and subsequently employed geographically weighted regression to capture spatial heterogeneity in the relationships between innovation drivers and outputs. The findings revealed that the effects of innovation determinants varied significantly across provinces. In particular, innovative employment, R&D capacities and institutional structures produced stronger outcomes in more developed regions, while their effects remained limited in peripheral areas. These results demonstrated that innovation dynamics in Türkiye were shaped by spatially differentiated processes rather than uniform mechanisms. The research therefore highlighted the necessity of rethinking innovation policies in Türkiye through place-based and spatially sensitive approaches
Driving factors · Geographically Weighted Regression · Location · Regional development · Regional innovation system · Regional Policy · Regression analysis · Turkish · Firm Innovation and Growth · Innovation Policy and RD · Regional Development and Policy
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Regional Innovation Systems, Clusters, and the Knowledge Economy
Stylized Facts in the Geography of Innovation
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Yaratıcı Sınıfın Girişimcilik Potansiyeli
Covid 19 and regional entrepreneurship
The territorial dynamics of innovation
The Resurgence of Regional Economies, Ten Years Later
Clusters and knowledge
Territorial Innovation Models
Determinants of the Efficiency of Regional Innovation Systems
Unseen costs
The Learning Region
Local Indicators of Spatial Association—Lisa
Development agencies in Turkey
The Geography of Innovation
Geographically Weighted Regression
| Citation velocity | historical |
|---|---|
| Highly cited | No |