Understanding Collective Reflection in Crowdsourcing for Innovation: A Semantic Network Approach

dc.contributor.author Sun, Yao
dc.contributor.author Majchrzak , Ann
dc.contributor.author Malhotra , Arvind
dc.date.accessioned 2020-12-24T20:04:40Z
dc.date.available 2020-12-24T20:04:40Z
dc.date.issued 2021-01-05
dc.description.abstract Empowered by the wisdom of crowds, innovation nowadays is increasingly relying on diverse individuals’ knowledge collaboration. Research on crowdsourcing and open innovation has demonstrated that through deliberate understanding and reflective thinking, members of the online crowd collectively manage their knowledge to generate innovative ideas. However, the semantic patterns of how online crowd’s collective reflection ultimately leads up to innovation remains unclear. Employing semantic network approach, this study analyzed a total of 1,116 posts contributed by online crowds responding to two organization-sponsored crowdsourcing open innovation challenges. Findings show that the semantic patterns of online crowds’ knowledge collaboration evolve from one phase to another in accordance with crowd members’ collective reflection on their diverse knowledge. Theoretical and practical implications are discussed.
dc.format.extent 11 pages
dc.identifier.doi 10.24251/HICSS.2021.627
dc.identifier.isbn 978-0-9981331-4-0
dc.identifier.uri http://hdl.handle.net/10125/71245
dc.language.iso English
dc.relation.ispartof Proceedings of the 54th 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 Flow, Transfer, Sharing, and Exchange
dc.subject crowdsourcing
dc.subject innovation
dc.subject knowledge
dc.subject semantic network
dc.title Understanding Collective Reflection in Crowdsourcing for Innovation: A Semantic Network Approach
prism.startingpage 5151
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