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

Author

Listed:
  • Ilyes Abidi

    (Management Information Systems Department, Applied College, University of Ha’il, Hail City P.O. Box 2440, Saudi Arabia
    Humanities Research Centre, University of Ha’il, Hail 55476, Saudi Arabia)

  • Hesham Yousef Alaraby

    (Management Information Systems Department, Applied College, University of Ha’il, Hail City P.O. Box 2440, Saudi Arabia
    Humanities Research Centre, University of Ha’il, Hail 55476, Saudi Arabia)

  • Ghassan Rabaiah

    (Management Information Systems Department, Applied College, University of Ha’il, Hail City P.O. Box 2440, Saudi Arabia
    Humanities Research Centre, University of Ha’il, Hail 55476, Saudi Arabia)

Abstract

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.

Suggested Citation

  • Ilyes Abidi & Hesham Yousef Alaraby & Ghassan Rabaiah, 2025. "Green Finance Path to Improve Entrepreneurship, Employment, and Circular Economy: New Insights Using XGBoost–SHAP Analysis," Sustainability, MDPI, vol. 17(21), pages 1-21, October.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:21:p:9400-:d:1777479
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    References listed on IDEAS

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    1. Ghada Alturif & Wafaa Saleh & Mohamed Ramadan A. Rezk & Mohammed Mahgoub Hassan & Leonardo Piccinetti & Alaa A. El-Bary & Alaa A. El-Bary, 2024. "Innovative pathways to a circular economy in Saudi Arabia and its spillover effects on the Arab Region," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 12(2), pages 314-332, December.
    2. Xie, Yi & Jiang, Jinwen & Wang, Dong, 2024. "Green finance policy and labor demand: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 86(C).
    3. Fu, Bowen & Zhang, Yixiang & Maani, Sholeh & Wen, Le, 2025. "Green finance and job creation: Analyzing employment effects in China's manufacturing industry within green finance innovation and reform pilot zones," Energy Economics, Elsevier, vol. 141(C).
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