A Study on the Analysis and Prediction of the Evolution Path of China’s Electric Vehicle Industry Policy Based on Text Mining - Zizheng Liu; Tao Xie (World Electric Vehicle Journal)
In the 21st century, China’s electric vehicle (EV) industry has demonstrated remarkable growth, rapidly catching up with and surpassing other nations in scale and development. Understanding the policy mechanisms behind this rapid ascent is crucial for analyzing the evolution of China’s EV sector and making informed decisions for its future development. This study provides a comprehensive analysis of the evolution of China’s EV policies from 2009 to 2023, with projections through 2027, using a mixed-method approach that incorporates text mining, co-word network analysis, and BERT-based trajectory models to explore the operational logic of various policy frameworks and predict future policy directions. The study findings reveal distinct phases in the evolution of China’s EV policies. Initially, the focus was on building industrial capacity through supply-side measures, laying the foundation for growth. As the industry matured, policies expanded to include demand-side incentives and environmental regulations, reflecting a shift towards a balanced and sustainable approach. Our research shows that early policy decisions significantly influenced later adjustments, highlighting the role of path dependence. By mapping the trajectory of China’s EV policies, this study offers a framework for predicting future trends, providing guidance for Chinese policymakers and offering strategies that would allow other countries to effectively compete with China. Ultimately, this research underscores the importance of adaptive and coordinated policy strategies for fostering sustainable growth in strategic industries, providing valuable lessons for China and beyond.