Suppr超能文献

技术网络:创新的自催化起源

Technology networks: the autocatalytic origins of innovation.

作者信息

Napolitano Lorenzo, Evangelou Evangelos, Pugliese Emanuele, Zeppini Paolo, Room Graham

机构信息

Department of Economics, University of Bath, Bath BA2 7AY, UK.

Istituto dei Sistemi Complessi (ISC)-CNR, 00185 Rome, Italy.

出版信息

R Soc Open Sci. 2018 Jun 27;5(6):172445. doi: 10.1098/rsos.172445. eCollection 2018 Jun.

Abstract

We analyse the autocatalytic structure of technological networks and evaluate its significance for the dynamics of innovation patenting. To this aim, we define a directed network of technological fields based on the International Patents Classification, in which a source node is connected to a receiver node via a link if patenting activity in the source field anticipates patents in the receiver field in the same region more frequently than we would expect at random. We show that the evolution of the technology network is compatible with the presence of a growing autocatalytic structure, i.e. a portion of the network in which technological fields mutually benefit from being connected to one another. We further show that technological fields in the core of the autocatalytic set display greater fitness, i.e. they tend to appear in a greater number of patents, thus suggesting the presence of positive spillovers as well as positive reinforcement. Finally, we observe that take place whereby different groups of technology fields alternate within the autocatalytic structure; this points to the importance of recombinant innovation taking place between close as well as distant fields of the hierarchical classification of technological fields.

摘要

我们分析了技术网络的自催化结构,并评估了其对创新专利动态的重要性。为此,我们基于国际专利分类定义了一个技术领域的有向网络,其中,如果源领域的专利活动比随机预期更频繁地预示着同一地区接收领域的专利,那么源节点就通过一条链路连接到接收节点。我们表明,技术网络的演化与不断增长的自催化结构的存在相一致,即网络的一部分,其中技术领域通过相互连接而相互受益。我们进一步表明,自催化集核心中的技术领域表现出更大的适应性,即它们往往出现在更多的专利中,从而表明存在正溢出效应以及正强化作用。最后,我们观察到自催化结构中不同技术领域组之间会交替出现这种情况;这表明在技术领域分层分类的相近和遥远领域之间进行重组创新的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b627/6030307/bd3d866b301f/rsos172445-g1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验