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A Dynamic Network Measure of Knowledge Evolution: A Case Study of MIS Quarterly

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dc.contributor.author Li, Jiexun
dc.contributor.author Chen, Jiyao
dc.date.accessioned 2016-12-29T01:41:18Z
dc.date.available 2016-12-29T01:41:18Z
dc.date.issued 2017-01-04
dc.identifier.isbn 978-0-9981331-0-2
dc.identifier.uri http://hdl.handle.net/10125/41703
dc.description.abstract Citation measures are the central metrics to assessing the impact of an article, the viability of research streams, the career success of scholars, as well as the quality and status of journals and academic units. While measuring the magnitude of the future usage, they cannot capture the substantial effects that an article may have on the subsequent use of its predecessors - whether it amplifies or disrupts the existing literature. We embrace that it is imperative to not only assess its impact but also assess how an article reinforces the existing research streams or breaks into a new stream to understand its true effect. Accordingly, we introduce a new, dynamic measure, and conduct a case study using all articles published between 1979-2016 at MIS Quarterly to illustrate the validity of the new measure, and conclude with some future research topics and implications.
dc.format.extent 10 pages
dc.language.iso eng
dc.relation.ispartof Proceedings of the 50th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject knowledge evolution
dc.subject disruptiveness index
dc.subject citation network
dc.title A Dynamic Network Measure of Knowledge Evolution: A Case Study of MIS Quarterly
dc.type Conference Paper
dc.type.dcmi Text
dc.identifier.doi 10.24251/HICSS.2017.541
Appears in Collections: Knowledge Flows, Transfer, Sharing and Exchange Minitrack


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