索引(排版)
多学科方法
独创性
计算机科学
鉴定(生物学)
相关系数
集合(抽象数据类型)
关系(数据库)
数据科学
数据挖掘
社会学
社会科学
机器学习
定性研究
万维网
植物
生物
程序设计语言
作者
Jie Li,Xueying Qiao,Jing M. Chen,Junhua Luo,Haoxuan Zhang,Junhua Ding,Haihua Chen
出处
期刊:The Electronic Library
[Emerald (MCB UP)]
日期:2024-04-08
卷期号:42 (4): 536-552
被引量:2
标识
DOI:10.1108/el-06-2023-0141
摘要
Purpose This study aims to establish a reliable index to identify interdisciplinary breakthrough innovation effectively. We constructed a new index, the D Div index, for this purpose. Design/methodology/approach The D Div index incorporates the degree of interdisciplinarity in the breakthrough index. To validate the index, a data set combining the publication records and citations of Nobel Prize laureates was divided into experimental and control groups. The validation methods included sensitivity analysis, correlation analysis and effectiveness analysis. Findings The sensitivity analysis demonstrated the D Div index’s ability to differentiate interdisciplinary breakthrough papers from various categories of papers. This index not only retains the strengths of the existing index in identifying breakthrough innovation but also captures interdisciplinary characteristics. The correlation analysis revealed a significant correlation (correlation coefficient = 0.555) between the interdisciplinary attributes of scientific research and the occurrence of breakthrough innovation. The effectiveness analysis showed that the D Div index reached the highest prediction accuracy of 0.8. Furthermore, the D Div index outperforms the traditional DI index in terms of accuracy when it comes to identifying interdisciplinary breakthrough innovation. Originality/value This study proposed a practical and effective index that combines interdisciplinary and disruptive dimensions for detecting interdisciplinary breakthrough innovation. The identification and measurement of interdisciplinary breakthrough innovation play a crucial role in facilitating the integration of multidisciplinary knowledge, thereby accelerating the scientific breakthrough process.
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