Shelia X. Wei , Howell Y. Wang , Sanhong Deng , Wanru Wang , Fred Y. Ye
{"title":"Measuring the university–industry–government relations synthesized by the Triple Helix and the diversity","authors":"Shelia X. Wei , Howell Y. Wang , Sanhong Deng , Wanru Wang , Fred Y. Ye","doi":"10.1016/j.joi.2025.101686","DOIUrl":null,"url":null,"abstract":"<div><div>Synthesizing the triple helix model and diversity, we introduce two novel indicators, <em>involvement</em> (<em>IV</em>) and <em>interaction</em> (<em>IA</em>), which are established upon the fusion of the triple helix concept and three extended attributes of diversity: proportion, balance, and disparity. These indicators are designed to evaluate one-dimensional involvement and two-dimensional and three-dimensional interaction within university-industry-government (U-I-G) relations. The empirical examination is conducted using two datasets related to CRISPR and fullerene, derived from the Web of Science. Our findings highlight a markedly higher level of involvement within universities compared to industries and governments, attributed to the dominant proportion of universities. We observe that different two-dimensional interactions render distinct performances on the three attributes. The interaction within U-I-G remains relatively low due to the low proportion. We further contrast <em>IV</em> and <em>IA</em> with the triple helix and transmission efficiency metrics, observing distinct differences among them. Consequently, we suggest that through the synthesis of the triple helix and diversity, <em>IV</em> and <em>IA</em> provide a more thorough understanding of involvement and interaction within U-I-G relations, and can inform strategies for their enhancement. The application of <em>IV</em> and <em>IA</em> can potentially extend to examining varying collaborative innovations within other triple or quadruple relations.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 3","pages":"Article 101686"},"PeriodicalIF":3.4000,"publicationDate":"2025-05-19","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/S1751157725000501","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
Synthesizing the triple helix model and diversity, we introduce two novel indicators, involvement (IV) and interaction (IA), which are established upon the fusion of the triple helix concept and three extended attributes of diversity: proportion, balance, and disparity. These indicators are designed to evaluate one-dimensional involvement and two-dimensional and three-dimensional interaction within university-industry-government (U-I-G) relations. The empirical examination is conducted using two datasets related to CRISPR and fullerene, derived from the Web of Science. Our findings highlight a markedly higher level of involvement within universities compared to industries and governments, attributed to the dominant proportion of universities. We observe that different two-dimensional interactions render distinct performances on the three attributes. The interaction within U-I-G remains relatively low due to the low proportion. We further contrast IV and IA with the triple helix and transmission efficiency metrics, observing distinct differences among them. Consequently, we suggest that through the synthesis of the triple helix and diversity, IV and IA provide a more thorough understanding of involvement and interaction within U-I-G relations, and can inform strategies for their enhancement. The application of IV and IA can potentially extend to examining varying collaborative innovations within other triple or quadruple relations.
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.