Spatial patterns of agricultural innovation system: regional insights from Türkiye

This study examines the spatial patterns of the Agricultural Innovation System (AIS) and its impact on regional economic development across 26 NUTS-2 regions in Türkiye. Global and Local Moran’s I were employed to assess spatial dependence, clustering, and outlier patterns. Subsequently, an Ordinary Least Squares (OLS) regression model was used to investigate the indicators affecting agricultural GDP using GIS-based tools. Moran’s I analyses show spatial clustering in some key AIS indicators in Türkiye, suggesting an east–west divergence, with high-high (H-H) clusters concentrated in western regions and low-low (L-L) clusters in eastern regions. These spatial patterns emphasize the need for regionally tailored strategies to strengthen innovation capacity and reduce spatial inequalities. OLS results indicate that agricultural enterprises, organic crop production, and agricultural research actors have a significant positive association with agricultural economic performance. Residual Moran’s I results indicate no significant spatial autocorrelation in the model, supporting the validity of the OLS specification. This study contributes to AIS literature by (1) integrating spatial and statistical methods to explore regional geographic patterns and innovation performance, (2) shifting focus from national to regional AIS perspectives, and (3) proposing a methodological framework for regional AIS analysis, offering insights for agricultural policy and regional development.