Interpretable machine learning for analyzing the spatial-temporal evolution and influencing factors of green economic development

• Published in: Expert systems with applications Vol. 283; p. 127863
• Main Authors: Ding, Rui, Ran, Xiaofeng, Jiang, Shuyue, Zhang, Bowen
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.07.2025
• Subjects: Green economy development; Influencing Factors; Interpretable Machine Learning; SHAP; Spatio-temporal Transition; Green economy development; SHAP; Spatio-temporal Transition; Influencing Factors; Interpretable Machine Learning

Understanding the dynamics and influencing factors of green economy development (GED) is essential for fostering sustainable growth and environmental sustainability. This paper investigates the spatial–temporal evolution, transition and influencing factors of GED in 287 cities of China. A multidimen...