Green Finance Path to Improve Entrepreneurship, Employment, and Circular Economy: New Insights Using XGBoost–SHAP Analysis

This study examines how green finance drives sustainable economic development in Saudi Arabia, focusing on the Hail region, with comparisons across seven major cities (Riyadh, Jeddah, Mecca, Medina, Dammam, Tabuk, and Taif). Through an XGBoost machine learning approach enhanced by SHAP interpretation, we analyze how Green Finance Investment (IGF), Alternative and Nuclear Energy (ANE), Electricity Access (ATE), and Logarithmic Carbon Emissions (LCDE) influence New Business Registrations (NBR), Employment rates (EM), and Circular Economy outcomes measured via Combustible Renewables and Waste (CRW). Results reveal that ANE is the dominant predictor of employment across all cities, with SHAP values ranging from 76.9% in Hail to 96.6% in Jeddah. Entrepreneurial drivers vary regionally: ANE leads in Riyadh (63.1%) and Jeddah (73.3%), LCDE dominates in Hail (45.0%) and Taif (48.6%), and IGF is primarily evident in Tabuk (39.5%). Model accuracy varies, with RMSE being the highest in Hail (58.97) and lowest in Jeddah (433.86), highlighting structural differences across urban economies. Circular economy pathways diverge between LCDE-driven industrial modernization (e.g., Dammam, 62.9%) and IGF-driven greenfield development (e.g., Tabuk, 81.1%). These findings support a threefold city classification and provide actionable insights into Saudi Arabia’s Vision 2030 implementation. They inform targeted policy interventions, including green infrastructure investments in energy hubs, industrial modernization programs in manufacturing centers, and entrepreneurial financing mechanisms in emerging regions.