中国
业务
产业组织
营销
工程管理
工程类
政治学
法学
作者
Xiaoping Wang,Liping Qiu,Feng Hu,Hao Hu
标识
DOI:10.1016/j.esr.2024.101505
摘要
Industry-university-research collaboration is the primary channel of industrial innovation, and China is a common context for research on innovation in the new energy vehicle industry. This study analyzes the industry-university-research collaborative innovation network in China's new energy vehicle industry using various software programs, including Gephi and ArcGIS, based on collaborative invention patent data related to the new energy vehicle industry provided by the global patent database incoPat. According to the findings of this study, the highest number of patents obtained through industry-university-research collaboration was observed in new energy vehicle device and accessory manufacturing, whereas the number of new entrants was significantly higher than the number of incumbents albeit in a downward trend, suggesting that the creation of new collaborative relationships among new entrants has always been the main phenomenon in the process of building an industry-university-research innovation system in the new energy vehicle industry. As private firms have long been playing an integral role in industry-university-research collaboration in the new energy vehicle industry, the number of private firms in the network exhibited an upward trend annually, while the dual heterogeneous connection mode was the primary connection mode in industry-university-research collaboration. There were some differences between the spatial characteristics of intraprovincial and interprovincial collaboration in the industry-university-research collaborative network in China's new energy vehicle industry. The analysis results obtained using GeoDetector revealed that the influence of economic base, level of openness to the outside world, government dominance, market dominance, regional science and technology finance, and entrepreneurial spirit varied from one stage to another. • The industry-university-research innovation network of new energy automobile industry in China is taken as the study subject. • Examined both network structure characteristics and influential factors. • Used a social network analysis and GeoDetector based on patent data from 2004 to 2019.
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