How to Improve the Efficiency of the New Energy Vehicle Industry: Multiple Paths From Configuration Perspective

Abstract

This study examines regional new energy vehicle (NEV) industry efficiency across 26 Chinese provinces, addressing the need for deeper insights into the spatiotemporal efficiency patterns and configurational pathways influencing NEV development. By employing data envelopment analysis (DEA) to measure efficiency, exploratory spatial data analysis (ESDA) to explore spatial clustering, and fuzzy-set qualitative comparative analysis (fsQCA) to investigate configuration-based pathways, this research provides a nuanced understanding of how regional factors shape NEV efficiency. The analysis identifies four distinct configurational pathways: policy bolstering for technological innovation, organizational synergy, market dynamics and regulatory synergy, and structural deficiency type. These findings suggest that developed regions benefit from prioritizing organizational collaboration and technological support, while less-developed areas may improve efficiency through foundational policy enhancement and regulatory alignment. Furthermore, investing in human capital, technical innovation, and infrastructure can contribute to building a resilient NEV ecosystem. By integrating multiple analytical methods, this study sheds light on the complex interactions shaping NEV efficiency across regions and offers insights for policymakers to enhance the global competitiveness and sustainability of China's NEV industry.