Leveraging Entrepreneurship for Environmental Sustainability: A Machine Learning Approach to SDG Achievement
使用机器学习技术分析全球创业观察数据，发现商业服务部门、创业意图和创业教育对实现环境相关的可持续发展目标有重要影响，为政策制定者提供了可操作的见解。
ABSTRACT In the face of escalating environmental challenges, the United Nations' Sustainable Development Goals (SDGs) have become crucial benchmarks for sustainability, with SDG 7 (Affordable and Clean Energy), SDG 12 (Responsible Consumption and Production), and SDG 13 (Climate Action) addressing key issues like energy efficiency, resource management, and climate change. This study explores the impact of the entrepreneurship ecosystem (EE) on these environmental goals, using data from the Global Entrepreneurship Monitor (GEM) and applying advanced machine learning techniques such as bagging, random forest, boosting, Shapley Additive Explanations (SHAP), and Partial Dependence Plots (PDPs). Grounded in sustainability, innovation, Resource‐Based View (RBV), and institutional theories, the study reveals the critical role of the business services sector, entrepreneurial intentions, and entrepreneurial education in driving progress toward environmental sustainability. The findings offer actionable insights for policymakers and contribute to the academic understanding of how entrepreneurship can be leveraged to achieve SDGs, emphasizing the need for a robust and integrated entrepreneurial ecosystem to foster sustainable practices.