强大的网络,关键的专利:识别和评估关键技术影响者

IF 4.6 3区 管理学 Q1 BUSINESS
Tao Wang;Chao Yu;Jun Huang;Hsin-Ning Su
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引用次数: 0

摘要

在技术日新月异、外部挑战层出不穷的今天,预测核心专利在技术体系的实力和力量中的作用至关重要。本研究提出了一种方法,将专利引用网络的稳健性分析与核心专利识别相结合,评估其全球产业技术创新意义。其目的是识别网络稳定性和外部变化适应性的关键专利,了解它们在动态技术环境中的影响。利用网络鲁棒性,该研究考察了专利引用网络的连通性、效率和聚类,并根据删除后的结构特征变化评估了专利节点的重要性。研究采用五个技术领域的专利作为案例,对节点的重要性进行排序,并探讨专利属性如何影响这些排序。这项研究将专利网络的稳健性与价值评估相结合,为知识产权战略和科技管理政策提供支持,并为科技系统的复杂性和动态性提供见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Networks, Pivotal Patents: Identifying and Assessing Key Technological Influencers
In a world of swiftly changing technology and external challenges, predicting the role of core patents in technology systems' strength and power is vital. This research presents a method that combines robustness analysis of patent citation networks with core patent identification, assessing their global industrial technology innovation significance. It aims to identify patents key to network stability and external change adaptation, understanding their impact in dynamic tech environments. Using network robustness, the study examines connectivity, efficiency, and clustering in patent citation networks, assessing patent node importance based on structural feature changes postremoval. The study employs patents from five technological domains as case studies, ranking the importance of nodes and exploring how patent attributes affect these rankings. This research contributes by merging patent network robustness with valuation, supporting IP strategies and tech management policies, and offering insights into tech system complexity and dynamism.
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来源期刊
IEEE Transactions on Engineering Management
IEEE Transactions on Engineering Management 管理科学-工程:工业
CiteScore
10.30
自引率
19.00%
发文量
604
审稿时长
5.3 months
期刊介绍: Management of technical functions such as research, development, and engineering in industry, government, university, and other settings. Emphasis is on studies carried on within an organization to help in decision making or policy formation for RD&E.
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