基于专利引用网络的新兴技术颠覆性发展路径测度

IF 3.4 2区 管理学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Informetrics Pub Date : 2024-01-12 DOI:10.1016/j.joi.2024.101493
Xiaoli Wang , Wenting Liang , Xuanting Ye , Lingdi Chen , Yun Liu
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引用次数: 0

摘要

研究新兴技术的颠覆性创新发展路径有助于追踪和把握关键核心技术的发展,促进新兴技术和产业的创新与发展。本文对新兴技术的创新发展路径进行了测度,包括:(1)通过设计技术干扰度模型,完善三重引文网络并量化干扰度测度;(2)从数据集视角提出引文网络的收缩方法;(3)提出以技术干扰度作为引文网络重要性标准的主要路径提取方法;(4)以3D打印技术中的烧结技术为实证对象,以1997-2019年的12662个专利族为实证对象。实证结果表明,中断度值由反式引用关系决定,不存在共引关系,有效去除了闭环结构,从而减小了数据集的规模。所提出的干扰度量化方法可为技术创新水平的有效评估以及研发方向和资源分配的决策提供支持。
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Disruptive development path measurement for emerging technologies based on the patent citation network

Studying disruptive innovation development paths for emerging technologies helps trace and grasp key core technologies development, promoting innovation and development in emerging technologies and industries. This paper measures the innovation development path for emerging technology, including: (1) improving the triple citation network and quantifying disruptive measurement by designing a technological disruption model; (2) proposing a contraction method for the citation network from the dataset perspective; (3) proposing a method to extract the main path using technology disruption degree as a criterion for citation networks importance; (4) taking the sintering technology in 3-D printing technology as the empirical object with 12,662 patent families from 1997 to 2019. The empirical results indicate that the disruption degree value is determined by the transitive citation relationship without the co-citation relationship, and the closed-loop structures are effectively removed, thereby reducing the size of the dataset. The proposed disruption quantification method can support effective evaluation of technological innovation levels and decision-making for the research and development (R&D) direction and resource allocation.

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来源期刊
Journal of Informetrics
Journal of Informetrics Social Sciences-Library and Information Sciences
CiteScore
6.40
自引率
16.20%
发文量
95
期刊介绍: Journal of Informetrics (JOI) publishes rigorous high-quality research on quantitative aspects of information science. The main focus of the journal is on topics in bibliometrics, scientometrics, webometrics, patentometrics, altmetrics and research evaluation. Contributions studying informetric problems using methods from other quantitative fields, such as mathematics, statistics, computer science, economics and econometrics, and network science, are especially encouraged. JOI publishes both theoretical and empirical work. In general, case studies, for instance a bibliometric analysis focusing on a specific research field or a specific country, are not considered suitable for publication in JOI, unless they contain innovative methodological elements.
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