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中文题名:

 多维邻近下新能源汽车产业专利合作网络演化及其机制研究    

姓名:

 赵媛    

保密级别:

 公开    

论文语种:

 chi    

学科代码:

 025200    

学科专业:

 应用统计    

学生类型:

 硕士    

学位:

 应用统计硕士    

学位类型:

 专业学位    

学位年度:

 2024    

校区:

 珠海校区培养    

学院:

 统计学院    

研究方向:

 数据科学与管理    

第一导师姓名:

 杜勇宏    

第一导师单位:

 统计学院    

提交日期:

 2024-06-13    

答辩日期:

 2024-05-25    

外文题名:

 Research on the evolution and mechanism of patent cooperation network in the new energy vehicle industry under multidimensional neighborhood    

中文关键词:

 新能源汽车产业 ; 专利合作网络 ; 社会网络分析法 ; 多维邻近性    

外文关键词:

 New energy automobile industry ; Patent cooperation network ; Social network analysis method ; Multidimensional proximity    

中文摘要:

在面临全球环境污染和温室效应的挑战下,新能源汽车因其环保和节能特性受到了全球范围内的重视。中国政府通过《新能源汽车产业发展规划(2021-2035年)》等政策文件,明确将新能源汽车产业定位为国家战略发展产业,旨在通过创新、协调、绿色、开放、共享的发展理念,推动产业的可持续发展。专利作为技术合作创新过程中科技成果转化的主要载体,已经使得合作申请专利成为提升新能源汽车产业主体创新能力、促进知识和技术交流的重要途径,有助于加快新能源汽车相关技术的产业化进程,促进新能源汽车产业的健康持续发展。
近年来,网络化发展模式将专利合作带入一个新的发展阶段,形成了以企业、高校与科研院所为主体的新能源汽车产业的专利合作网络,本文基于已有文献对专利合作网络的研究,按照“网络结构→网络演化→演化驱动机制→优化建议”的逻辑主线,基于2001-2021年新能源汽车产业合作申请专利数据,研究我国新能源汽车产业专利合作网络的发展。本研究不仅基于专利视角丰富了专利合作网络的理论研究,揭示了新能源汽车产业专利合作网络的结构与演化机制,还在帮助网络主体突破发展瓶颈,增强自身的研发实力,推动新能源汽车产业快速发展,提升国际竞争力方面具有现实意义。
首先,界定专利合作与多维邻近性的相关概念,并利用得到的4229条我国新能源汽车产业联合申请发明专利数据,从专利合作趋势、不同主体合作类型、不同主体竞争力、前十位新能源车企专利合作情况以及关键技术几个方面,分析我国新能源汽车产业专利合作的基本情况。其次,以创新主体为节点,以合作关系为连边,以合作次数为权重,构建中国新能源汽车产业专利合作网络,运用Gephi软件对合作网络模型进行可视化处理,并从定性与定量两个方面,对新能源汽车产业专利合作网络的构成要素、形成动因、整体与个体网络结构特征等方面进行研究分析。再次,利用Logistic模型拟合中国新能源汽车产业专利合作网络成长曲线,将新能源汽车产业发展划分为初创期(2001-2009年)、形成期(2010-2017年)和成长期(2018-2021年)三个阶段,在此基础上从时间和空间两个维度分析网络结构演化过程。然后,运用QAP法,以合作申请专利数为被解释变量,以地理、技术、制度和社会邻近性为解释变量,探究这四个邻近性在不同阶段对新能源汽车产业专利合作网络演化的影响。最后,从新能源汽车产业网络结构特征、网络演化特征与演化的邻近性机制三方面得出结论,并依据结论提出发掘潜在专利合作关系、发挥关键节点作用、扩大集聚态势以及发挥多维邻近性正向影响等建议。

外文摘要:

Faced with the challenges of global environmental pollution and greenhouse effect, new energy vehicles have received global attention due to their environmental and energy-saving characteristics. The Chinese government has clearly positioned the new energy vehicle industry as a national strategic development industry through policy documents such as the New Energy Vehicle Industry Development Plan (2021-2035), aiming to promote sustainable development of the industry through innovative, coordinated, green, open, and shared development concepts. Patents, as the main carrier for the transformation of scientific and technological achievements in the process of technological cooperation and innovation, have made cooperative patent applications an important way to enhance the innovation ability of the new energy vehicle industry, promote knowledge and technology exchange, accelerate the industrialization process of new energy vehicle related technologies, and promote the healthy and sustainable development of the new energy vehicle industry.
In recent years, the networked development model has brought patent cooperation into a new stage of development, forming a patent cooperation network in the new energy vehicle industry with enterprises, universities, and research institutes as the main body. Based on the research on patent cooperation networks in existing literature, this article follows the logical mainline of "network structure → network evolution → evolutionary driving mechanism → optimization suggestions", and studies the development of China's new energy vehicle industry patent cooperation network based on patent application data from 2001 to 2021. This study not only enriches the theoretical research of patent cooperation networks from a patent perspective, but also reveals the structure and evolutionary mechanism of patent cooperation networks in the new energy vehicle industry. It also helps network entities break through development bottlenecks, enhance their research and development capabilities, promote the rapid development of the new energy vehicle industry, and enhance international competitiveness, which has practical significance.
Firstly, define the relevant concepts of patent cooperation and multi-dimensional proximity, and use the 4229 joint application invention patent data of China's new energy vehicle industry to analyze the basic situation of patent cooperation in China's new energy vehicle industry from several aspects, including patent cooperation trends, different subject patent cooperation situations, different subject competitiveness, the top ten new energy vehicle enterprise patent cooperation situations, and key technologies. Secondly, with innovation entities as nodes, cooperation relationships as edges, and cooperation frequency as weights, a patent cooperation network for China's new energy vehicle industry is constructed. Gephi software is used to visualize the cooperation network model, and the constituent elements, formation motives, overall and individual network structure characteristics of the patent cooperation network for the new energy vehicle industry are studied and analyzed from both qualitative and quantitative perspectives. Once again, using the logistic model to fit the growth curve of China's new energy vehicle industry patent cooperation network, the development of the new energy vehicle industry is divided into three stages: the start-up period (2001-2009), the formation period (2010-2017), and the growth period (2018-2021). Based on this, the evolution process of the network structure is analyzed from two dimensions: time and space. Then, using the QAP method, with the number of cooperative patent applications as the dependent variable and geographical, technological, institutional, and social proximity as the independent variables, explore the impact of these four proximity factors on the evolution of the patent cooperation network in the new energy vehicle industry at different stages. Finally, conclusions are drawn from three aspects: the network structure characteristics of the new energy vehicle industry, the network evolution characteristics, and the proximity mechanism of evolution. Based on these conclusions, suggestions are proposed to explore potential patent cooperation relationships, play a key node role, expand clustering trends, and leverage the positive impact of multi-dimensional proximity.

参考文献总数:

 83    

馆藏地:

 总馆B301    

馆藏号:

 硕025200/24078Z    

开放日期:

 2025-06-13    

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