Ming-Ze Zhang , Tang-Rong Wang , Peng-Hui Lyu , Qi-Mei Chen , Ze-Xia Li , Eric W.T. Ngai
{"title":"Impact of gender composition of academic teams on disruptive output","authors":"Ming-Ze Zhang , Tang-Rong Wang , Peng-Hui Lyu , Qi-Mei Chen , Ze-Xia Li , Eric W.T. Ngai","doi":"10.1016/j.joi.2024.101520","DOIUrl":null,"url":null,"abstract":"<div><p>Intergender collaboration is becoming increasingly common in academia. However, the impact of team gender structures on innovation remains unknown. Using data from the American Physical Society, this study applies the disruption index to measure the relationship between gender composition and innovation performance. The results show that compared with single-gender teams, moderate inter-gender collaboration has a greater potential to produce disruptive knowledge and must be adopted by scientific teams. Specifically, the types of innovation in mixed-gender teams are affected by the gender composition. If the proportion of female scholars and their participation increase in a mixed-gender team, it can positively contribute to disruptive performance. If female scientists are placed on a male-dominated team, they may function as consolidation representatives. The robustness results indicate that the conclusions also apply to male scientists. The results suggest that males and females have no significant physiological differences in innovation and that the key is to find a gender balance in collaboration. Based on the theories of similarity-attraction and cognitive diversity, the reasons for the differences between female and male scientists may be team atmosphere and their roles in collaboration. This study can serve as a reference for policymakers and funders when building teams to achieve disruptive discoveries.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-02-22","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/S1751157724000336","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
Intergender collaboration is becoming increasingly common in academia. However, the impact of team gender structures on innovation remains unknown. Using data from the American Physical Society, this study applies the disruption index to measure the relationship between gender composition and innovation performance. The results show that compared with single-gender teams, moderate inter-gender collaboration has a greater potential to produce disruptive knowledge and must be adopted by scientific teams. Specifically, the types of innovation in mixed-gender teams are affected by the gender composition. If the proportion of female scholars and their participation increase in a mixed-gender team, it can positively contribute to disruptive performance. If female scientists are placed on a male-dominated team, they may function as consolidation representatives. The robustness results indicate that the conclusions also apply to male scientists. The results suggest that males and females have no significant physiological differences in innovation and that the key is to find a gender balance in collaboration. Based on the theories of similarity-attraction and cognitive diversity, the reasons for the differences between female and male scientists may be team atmosphere and their roles in collaboration. This study can serve as a reference for policymakers and funders when building teams to achieve disruptive discoveries.
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.