Linkages among science, technology, and industry on the basis of main path analysis

IF 3.4 2区 管理学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Informetrics Pub Date : 2024-11-26 DOI:10.1016/j.joi.2024.101617
Shuo Xu , Zhen Liu , Xin An , Hong Wang , Hongshen Pang
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引用次数: 0

Abstract

Compared to the science-technology linkages, the linkages among science, technology, and industry are largely under-studied. Therefore, this paper proposes a main path analysis based framework to discover the science-technology-industry linkages, in which scientific publications, patents, and products are viewed as respective proxies of scientific research, technological advance, and industrial development. To validate the feasibility and effectiveness of our framework, after the DrugBank dataset in pharmaceutical industry was downloaded in XML form on 1 November 2019, this dataset is further enriched, drug entity mentions are recognized from scholarly articles and patents, and several citation cycles are eliminated. The scientific publications span from 1871 to 2019, and patents from 1953 to 2019. There are 8,421, 5,590, and 2,136 article, patent, and drug nodes and 41,200 citations in the largest weakly connected component of the constructed heterogeneous citation network. From empirical analysis on the largest weakly connected component, main conclusions can be drawn as follows. (1) The discovered developmental trajectories indeed encode the interactions among science, technology, and industry. Science and technology not only interact with each other, but also jointly promote the development of the industry, and the industry, in turn, influences the advancement of science and technology. (2) The developmental modes in the pharmaceutical industry can be grouped into three categories: pushed by only science, pushed by only technology, and pushed by science and technology simultaneously. (3) The drugs bridge scientific research and technological advance, and thereby help enhance knowledge exchanges between science and technology and shorten the cycle of drug development. This study contributes to discovering the linkages among science, technology, and industry from the perspective of mutual citations among scholarly articles, patents, and products. However, a scientific verification of our framework in other industries apart from pharmaceutical industry still needs to be further investigated.
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基于主要路径分析的科学、技术和产业之间的联系
与科学-技术联系相比,科学、技术和产业之间的联系在很大程度上研究不足。因此,本文提出了一个基于主要路径分析的框架来发现科学、技术和产业之间的联系,其中科学出版物、专利和产品分别被视为科学研究、技术进步和产业发展的代理变量。为了验证我们的框架的可行性和有效性,在2019年11月1日以XML形式下载了医药行业的DrugBank数据集之后,我们进一步丰富了这个数据集,从学术文章和专利中识别了药物实体的提及,并消除了几个引用周期。学术论文的时间跨度为 1871 年至 2019 年,专利的时间跨度为 1953 年至 2019 年。在构建的异构引文网络的最大弱连接分量中,文章、专利和药物节点分别为8421、5590和2136个,引用次数为41200次。通过对最大弱连接分量的实证分析,可以得出以下主要结论。(1)所发现的发展轨迹确实编码了科学、技术和产业之间的互动。科学和技术不仅相互影响,还共同促进了产业的发展,而产业反过来又影响了科学和技术的进步。(2)医药产业的发展模式可分为三类:仅由科学推动、仅由技术推动、科学与技术同时推动。(3) 药物是科学研究与技术进步的桥梁,有助于加强科学与技术之间的知识交流,缩短药物开发周期。这项研究有助于从学术论文、专利和产品之间相互引用的角度发现科学、技术和产业之间的联系。然而,我们的框架在制药业以外的其他行业的科学验证仍有待进一步研究。
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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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