基于新能源汽车的专利合作网络演化研究

A research on the evolution of patent cooperation networks based on new energy vehicles

以新能源汽车为研究对象,通过挖掘相关专利合作数据,绘制新能源汽车的专利合作网络,运用社会网络分析方法,基于时间和空间两个维度,剖析在1989-2015年间,新能源汽车专利合作网络的网络结构以及空间分布的演化规律。研究结果表明,新能源汽车的专利合作网络演化呈现明显的阶段特征,自2010年开始,网络规模呈现爆发式增长,网络朝着更为连通的方向演化发展;在不同的演化阶段,网络结构演化存在较大差异,核心组织地位日益突显,网络呈现多元化合作发展,不同类型组织间的专利合作日趋显著;区域内和区域间的专利合作方式呈现不同的空间演化规律,区域边界对于广西、黑龙江、甘肃以及海南等地的跨区域合作存在较大影响,北京、江苏以及浙江等地在跨区域合作中处于明显优势地位。

The stable and sound development of the new energy vehicle industry has become the focus of the development of the Chinese automobile industry and national economic.The patent cooperation network provides a new perspective for the analysis of cooperation and development in the field of new energy vehicles.However,there are few studies on the evolution and development of new energy vehicle patent cooperation network based on enterprises,universities,scientific research institutes and individuals,and considering both time and space dimensions.In view of this,this paper takes the new energy vehicle patent cooperative network established by the new energy vehicle patent cooperative data as the research object,uses the social network analysis method,based on the time and space dimension,to analyze the network structure and the evolution law of spatial distribution of the new energy vehicle patent cooperative network.At first,the patent database of China National Intellectual Property Office(SIPO)is used as the data source to locate all relevant patents of new energy vehicles applied in China.According to the classification of new energy vehicles in Strategic Emerging Industries Classification and the relevant literature of new energy vehicles in academic journals,the high-frequency keywords of new energy vehicles are preliminarily determined.According to IPC classification,the obtained patents are screened,and Python is used to mine the name abstract and the text information of sovereignty items in the patents,so as to accurately identify the high-frequency keywords of new energy vehicles.Repeat the operation steps until the high-frequency keywords,IPC classification and the corresponding changes in the total number of patents are relatively small,so as to obtain a more accurate expression of the new energy vehicle patent retrieval.Then,using patent search expression,1020 new energy vehicles field patents are retrieved with patent data and cooperative application relationship,these data are selected as the research data of this paper.Considering that the patent cooperation behavior of new energy vehicles has obvious stage characteristics,patents can be divided into three stages,1989-2003,2003-2009 and 2010-2015,to study the evolution of the patent cooperation behavior.Then,the evolution law of new energy vehicle patent cooperation network is analyzed from the time dimension.Gephi software was used to map the new energy vehicles patent cooperation network in 1989-2003,2004-2009 and 2010-2015,and social network analysis was used to measure the structural indicators of the patent cooperation network of new energy vehicles in three stages,so as to analyze the evolution law of the overall structure of new energy vehicles patent cooperation network.Then,the evolution law of the individual network structure of new energy vehicles is analyzed by constructing a'breadth-depth'two-dimensional matrix of degree value and unit weight.Subsequently,the spatial evolution law of the patent cooperation network of new energy vehicles is analyzed from the spatial dimension.Through the change in the number and proportion of new energy vehicle patents in different regions,the evolution law of new energy vehicle patents in different regions is analyzed.Through the cross-regional cooperation of new energy vehicle patents,the evolution law of new energy vehicle patents’external cooperation is analyzed,and the distribution pattern of patent cooperation in different regions is analyzed by'breadth-depth'two-dimensional matrix.The conclusions are as follows:Firstly,from 1989 to 2015,the evolution of new energy vehicles patent cooperation network shows obvious stage characteristics.Since 2010,the number of nodes and links in the network has increased rapidly,and the scale of the network has shown an explosive growth trend.At the same time,the network has a smaller average path length and a larger clustering coefficient,and evolves towards a more connected direction.Secondly,there are great differences in the evolution of the patent cooperation network structure of new energy vehicles between stages,and there is a diversified cooperation and development.During 1989-2003,individuals represented by Gang Wan became important nodes in this stage network;during 2004-2009,the network was mainly composed by patent cooperatives among enterprises,universities and research institutes of the same type;during 2010-2015,the network was represented by State Grid Corporation,Chongqing Chang’an Vehicle Co.,Ltd.and Zhejiang Jili Holding Group Co.,Ltd.Enterprises,universities such as Chongqing University and Tsinghua University,as well as scientific research institutes such as China Electric Power Research Institute,have a high degree of cooperation breadth and cooperation depth.These organizations have become the core nodes of the network at this stage.In addition,patent cooperation among different types of organizations is becoming increasingly prominent.Thirdly,patents cooperation patterns within and between regions show different spatial distribution and evolution laws.From the perspective of regional cooperation,the total amount of patent cooperation and the proportion of internal cooperation in Shanghai,Zhejiang and Chongqing are relatively high,and the impact of regional boundaries on these regions is gradually increasing;In Heilongjiang,Gansu,Guangxi and Hainan,the total amount of patent cooperation and the proportion of internal cooperation are relatively low,and the impact of regional boundaries on these regions is gradually weakening.From the regional external cooperation point of view,Beijing is the core of cross-regional cooperation,and its position is constantly consolidated;at the same time,the capacity of cross-regional cooperation in Shandong,Jiangsu and Zhejiang is also increasing;as the recipient of knowledge,Beijing,Jiangsu and Zhejiang are in a prominent position,while Guangxi,Guizhou and Gansu are still in need of strengthening their ability to acquire knowledge.