O'Neale Dion R J, Hendy Shaun C, Vasques Filho Demival
Department of Physics, University of Auckland, Auckland, New Zealand.
Te Pūnaha Matatini-The Centre for Complex Systems and Networks, Auckland, New Zealand.
Front Big Data. 2021 Jul 14;4:689310. doi: 10.3389/fdata.2021.689310. eCollection 2021.
Agglomeration and spillovers are key phenomena of technological innovation, driving regional economic growth. Here, we investigate these phenomena through technological outputs of over 4,000 regions spanning 42 countries, by analyzing more than 30 years of patent data (approximately 2.7 million patents) from the European Patent Office. We construct a bipartite network-based on revealed comparative advantage-linking geographic regions with areas of technology and compare its properties to those of artificial networks using a series of randomization strategies, to uncover the patterns of regional diversity and technological ubiquity. Our results show that the technological outputs of regions create nested patterns similar to those of ecological networks. These patterns suggest that regions need to dominate various technologies first (those allegedly less sophisticated), creating a diverse knowledge base, before subsequently developing less ubiquitous (and perhaps more sophisticated) technologies as a consequence of complementary knowledge that facilitates innovation. Finally, we create a map-the Patent Space Network-showing the interactions between technologies according to their regional presence. This network reveals how technology across industries co-appear to form several explicit clusters, which may aid future works on predicting technological innovation due to agglomeration and spillovers.
集聚和溢出效应是技术创新的关键现象,推动着区域经济增长。在此,我们通过分析来自欧洲专利局的42个国家4000多个地区30多年的专利数据(约270万项专利),依据技术产出对这些现象展开研究。我们构建了一个基于显示性比较优势的二分网络,将地理区域与技术领域相联系,并运用一系列随机化策略,将其属性与人工网络的属性进行比较,以揭示区域多样性和技术普遍性的模式。我们的研究结果表明,各地区的技术产出形成了与生态网络类似的嵌套模式。这些模式表明,各地区首先需要在各种技术(那些所谓不太复杂的技术)方面占据主导地位,建立起多样化的知识基础,然后才能因促进创新的互补知识而发展那些普遍性较低(或许更复杂)的技术。最后,我们绘制了一幅地图——专利空间网络,展示了根据技术在各地区的分布情况而形成的技术之间的相互作用。该网络揭示了不同行业的技术如何共同出现并形成几个明确的集群,这可能有助于未来有关预测因集聚和溢出效应而产生的技术创新的研究。