熵、异质性及其对技术进步的影响

IF 3.4 2区 管理学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Wonchang Hur
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引用次数: 0

摘要

本研究旨在确定专利受让人的熵和技术领域内专利技术的异质性是否会对该领域对其他领域的影响产生积极作用。提出这一问题的动机来自于不同学科间探讨的多样性-绩效辩论。本文考虑了三种熵指数:香农指数、赫芬达尔指数和洛伦兹指数。此外,通过使用预先训练的深度神经网络进行词嵌入,还开发了语义异质性指数。本研究调查了从 1976 年到 2021 年构成专利全貌的八个合作专利分类(CPC)部分中的约 200 万件专利。主要发现有两个方面。首先,一个技术领域内创造的知识的语义异质性对其对其他领域的影响有积极影响。其次,随着发明实体熵的增加,一个领域的影响力会受到负面影响。这表明,当发明集中在少数多产实体中,而不是分布在小实体中时,技术领域的影响力往往更大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Entropy, heterogeneity, and their impact on technology progress

This study seeks to determine whether the entropy of patent assignees and the heterogeneity of patented technology within a technology domain positively contribute to the domain's influence on others. This question is motivated by the diversity-performance debates that have been explored across diverse disciplines. Three entropy indices are considered: Shannon, Herfindahl, and Lorenz indices. In addition, the semantic heterogeneity index is developed by employing a pre-trained deep neural network for word embedding. This study investigates about 2 million patents from 1976 to 2021 in the eight Cooperative Patent Classification (CPC) sections that constitute the entire patent landscape. The major findings are two folds. First, the semantic heterogeneity of knowledge created within a technology domain has a positive impact on its influence on others. Second, a negative impact can be exerted on a domain's influence, as the entropy of inventing entities increases. This suggests that a technology domain tends to be more influential when inventions are concentrated among a few prolific entities rather than being distributed across small entities.

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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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