Xian Li , Haixing Du , Yi Bu , Mingshu Ai , Junjie Huang , Tao Jia
{"title":"Innovation lineage structure: A graph structure in publications of scholars and its association with disruptiveness","authors":"Xian Li , Haixing Du , Yi Bu , Mingshu Ai , Junjie Huang , Tao Jia","doi":"10.1016/j.joi.2025.101730","DOIUrl":null,"url":null,"abstract":"<div><div>Numerous factors have been associated with disruptive research that dramatically drives scientific development. However, few studies have explored the issue from the perspective of the publication structures of scholars. To fill the gap, we identified a graph publication structure, termed innovation lineage structure, from 110,488,521 publications in the <em>OpenAlex</em> database authored by 1523,664 scholars who began their careers in 1980 or later. Using logistic regression models, we found that publications within these structures were more disruptive than those outside. This finding remained robust across different disruptiveness measures, scholars of various genders, and within the natural and engineering sciences. Informed by career stages and knowledge diversity, we observed that scholars adopted exploration research strategies for research within their innovation lineage structures, leading to more disruptive impacts. The proposed innovation lineage structures are associated with disruptiveness and offer insights for scholars seeking greater impact, highlighting that publications grounded in novel work and characterized by persistent innovation are more likely to be disruptive.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 4","pages":"Article 101730"},"PeriodicalIF":3.5000,"publicationDate":"2025-09-10","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/S1751157725000926","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
Numerous factors have been associated with disruptive research that dramatically drives scientific development. However, few studies have explored the issue from the perspective of the publication structures of scholars. To fill the gap, we identified a graph publication structure, termed innovation lineage structure, from 110,488,521 publications in the OpenAlex database authored by 1523,664 scholars who began their careers in 1980 or later. Using logistic regression models, we found that publications within these structures were more disruptive than those outside. This finding remained robust across different disruptiveness measures, scholars of various genders, and within the natural and engineering sciences. Informed by career stages and knowledge diversity, we observed that scholars adopted exploration research strategies for research within their innovation lineage structures, leading to more disruptive impacts. The proposed innovation lineage structures are associated with disruptiveness and offer insights for scholars seeking greater impact, highlighting that publications grounded in novel work and characterized by persistent innovation are more likely to be disruptive.
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.