作为技术密集型新兴产业,新能源汽车核心技术研发需要企业、高校和研究院所通力合作,进而形成结构复杂的协同创新网络。现有研究对新能源汽车产业各创新主体形成协同创新网络的关注较少,且缺乏对长期动态协同创新行为的系统化讨论。利...作为技术密集型新兴产业,新能源汽车核心技术研发需要企业、高校和研究院所通力合作,进而形成结构复杂的协同创新网络。现有研究对新能源汽车产业各创新主体形成协同创新网络的关注较少,且缺乏对长期动态协同创新行为的系统化讨论。利用指数随机图模型(Exponential Random Graph Model,ERGM)分析2017—2021年中国新能源汽车合作专利协同创新网络,探索影响新能源汽车产业协同创新网络动态演化的主要因素,以及不同创新主体类型(企业、高校和研究院所)对协同创新关系演化的影响。研究发现:(1)在新能源汽车产业协同创新网络中,不同类型创新主体更易形成合作关系;(2)创新能力较强的创新主体更有可能与其他主体形成新合作关系,且企业更愿意与自身创新能力差距不大的其他主体合作;(3)协同创新网络星型结构明显,且表现出明显扩张态势;(4)针对不同类型创新主体的异质性分析结果表明,相比于企业,高校和研究院所更有可能与其他创新主体形成新合作关系。研究结论对于持续推进我国新能源汽车产业技术创新、构建新一代汽车技术体系、助力能源系统转型以及实现碳达峰和碳中和目标具有重要意义。展开更多
Based on the HS 4-digit code trade data in UNCOMTRADE from 1995 to 2020, this paper analyzes the characteristics of the evolution of the global PG trade network using the complex network approach and analyzes the chan...Based on the HS 4-digit code trade data in UNCOMTRADE from 1995 to 2020, this paper analyzes the characteristics of the evolution of the global PG trade network using the complex network approach and analyzes the changes in its resilience at the overall and country levels, respectively. The results illustrated that:(1) The scale of the global PG trade network tends to expand, and the connection is gradually tightened, experiencing a change from a “supply-oriented” to a “supply-and-demand” pattern, in which the U.S., Russia, Qatar, and Australia have gradually replaced Canada, Japan, and Russia to become the core trade status, while OPEC countries such as Qatar, Algeria, and Kuwait mainly rely on PG exports to occupy the core of the global supply, and the trade status of other countries has been dynamically alternating and evolving.(2) The resilience of the global PG trade network is lower than that of the random network and decreases non-linearly with more disrupted countries. Moreover, the impact of the U.S. is more significant than the rest of countries. Simulations using the exponential random graph model(ERGM) model revealed that national GDP, institutional quality, common border and RTA network are the determinants of PG trade network formation, and the positive impact of the four factors not only varies significantly across regions and stages, but also increases with national network status.展开更多
文摘作为技术密集型新兴产业,新能源汽车核心技术研发需要企业、高校和研究院所通力合作,进而形成结构复杂的协同创新网络。现有研究对新能源汽车产业各创新主体形成协同创新网络的关注较少,且缺乏对长期动态协同创新行为的系统化讨论。利用指数随机图模型(Exponential Random Graph Model,ERGM)分析2017—2021年中国新能源汽车合作专利协同创新网络,探索影响新能源汽车产业协同创新网络动态演化的主要因素,以及不同创新主体类型(企业、高校和研究院所)对协同创新关系演化的影响。研究发现:(1)在新能源汽车产业协同创新网络中,不同类型创新主体更易形成合作关系;(2)创新能力较强的创新主体更有可能与其他主体形成新合作关系,且企业更愿意与自身创新能力差距不大的其他主体合作;(3)协同创新网络星型结构明显,且表现出明显扩张态势;(4)针对不同类型创新主体的异质性分析结果表明,相比于企业,高校和研究院所更有可能与其他创新主体形成新合作关系。研究结论对于持续推进我国新能源汽车产业技术创新、构建新一代汽车技术体系、助力能源系统转型以及实现碳达峰和碳中和目标具有重要意义。
基金funded by the National Natural Science Foundation of China Projects (Grant number 71703128)Anhui Provincial Higher Education Research Key Project (grant number: 2024AH052139)。
文摘Based on the HS 4-digit code trade data in UNCOMTRADE from 1995 to 2020, this paper analyzes the characteristics of the evolution of the global PG trade network using the complex network approach and analyzes the changes in its resilience at the overall and country levels, respectively. The results illustrated that:(1) The scale of the global PG trade network tends to expand, and the connection is gradually tightened, experiencing a change from a “supply-oriented” to a “supply-and-demand” pattern, in which the U.S., Russia, Qatar, and Australia have gradually replaced Canada, Japan, and Russia to become the core trade status, while OPEC countries such as Qatar, Algeria, and Kuwait mainly rely on PG exports to occupy the core of the global supply, and the trade status of other countries has been dynamically alternating and evolving.(2) The resilience of the global PG trade network is lower than that of the random network and decreases non-linearly with more disrupted countries. Moreover, the impact of the U.S. is more significant than the rest of countries. Simulations using the exponential random graph model(ERGM) model revealed that national GDP, institutional quality, common border and RTA network are the determinants of PG trade network formation, and the positive impact of the four factors not only varies significantly across regions and stages, but also increases with national network status.
