{"title":"Disruptive content, cross agglomeration interaction, and agglomeration replacement: Does cohesion foster strength?","authors":"Kun Tang , Baiyang Li , Qiyu Zhu , Lecun Ma","doi":"10.1016/j.joi.2024.101570","DOIUrl":null,"url":null,"abstract":"<div><p>A trend in the academic field is agglomerations among scholars to generate knowledge with a disruptive influence on science and technology; however, the benefits have not been fully substantiated. This paper analyzes over 660,000 papers on artificial intelligence published from 1961 to 2023. We propose a method to calculate the innovative capacity of disruptive knowledge based on the similarity of historical, current, and future keywords, finding that scholars who commence their scientific endeavors earlier possess a heightened capability for disruptive knowledge innovation as <em>Dkc</em> index. The analysis reveals that multiagglomeration scholars have the highest average number of publications and citations, followed by agglomeration-flow scholars. Moreover, a larger agglomeration results in a lower ability to disrupt and consolidate knowledge innovation. Multiagglomeration and agglomeration-flow scholars harm disruptive/consolidative innovations. However, as the agglomeration effect intensifies, these two types of scholars from the disruptive perspective and multiagglomeration scholars from the consolidation perspective have a diminishing marginal effect on innovation capacity. The agglomeration size acts as a partial intermediary in the <em>Multi</em>→<em>Size</em>→<em>Dkc</em> index from the dual perspective and as a full mediator in the <em>Flow</em>→<em>Size</em>→<em>Dkc</em> index from the disruptive perspective, but only with a direct effect from the consolidative perspective.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 4","pages":"Article 101570"},"PeriodicalIF":3.4000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Informetrics","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1751157724000828","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
A trend in the academic field is agglomerations among scholars to generate knowledge with a disruptive influence on science and technology; however, the benefits have not been fully substantiated. This paper analyzes over 660,000 papers on artificial intelligence published from 1961 to 2023. We propose a method to calculate the innovative capacity of disruptive knowledge based on the similarity of historical, current, and future keywords, finding that scholars who commence their scientific endeavors earlier possess a heightened capability for disruptive knowledge innovation as Dkc index. The analysis reveals that multiagglomeration scholars have the highest average number of publications and citations, followed by agglomeration-flow scholars. Moreover, a larger agglomeration results in a lower ability to disrupt and consolidate knowledge innovation. Multiagglomeration and agglomeration-flow scholars harm disruptive/consolidative innovations. However, as the agglomeration effect intensifies, these two types of scholars from the disruptive perspective and multiagglomeration scholars from the consolidation perspective have a diminishing marginal effect on innovation capacity. The agglomeration size acts as a partial intermediary in the Multi→Size→Dkc index from the dual perspective and as a full mediator in the Flow→Size→Dkc index from the disruptive perspective, but only with a direct effect from the consolidative perspective.
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.