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

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dc.contributor.authorLi, Jiexun
dc.contributor.authorChen, Jiyao
dc.date.accessioned2016-12-29T01:41:18Z
dc.date.available2016-12-29T01:41:18Z
dc.date.issued2017-01-04
dc.description.abstractCitation 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.extent10 pages
dc.identifier.doi10.24251/HICSS.2017.541
dc.identifier.isbn978-0-9981331-0-2
dc.identifier.urihttp://hdl.handle.net/10125/41703
dc.language.isoeng
dc.relation.ispartofProceedings of the 50th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectknowledge evolution
dc.subjectdisruptiveness index
dc.subjectcitation network
dc.titleA Dynamic Network Measure of Knowledge Evolution: A Case Study of MIS Quarterly
dc.typeConference Paper
dc.type.dcmiText

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